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Lu B, Chen X, Xavier Castellanos F, Thompson PM, Zuo XN, Zang YF, Yan CG. The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration. Sci Bull (Beijing) 2024; 69:1536-1555. [PMID: 38519398 DOI: 10.1016/j.scib.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 12/12/2023] [Accepted: 02/27/2024] [Indexed: 03/24/2024]
Abstract
Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.
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Affiliation(s)
- Bin Lu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Francisco Xavier Castellanos
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York 10016, USA; Nathan Kline Institute for Psychiatric Research, Orangeburg 10962, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles 90033, USA
| | - Xi-Nian Zuo
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; National Basic Science Data Center, Beijing 100190, China
| | - Yu-Feng Zang
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310004, China; Institute of Psychological Science, Hangzhou Normal University, Hangzhou 310030, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment, Hangzhou 311121, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China; International Big-Data Center for Depression Research, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.
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2
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Voineskos AN, Hawco C, Neufeld NH, Turner JA, Ameis SH, Anticevic A, Buchanan RW, Cadenhead K, Dazzan P, Dickie EW, Gallucci J, Lahti AC, Malhotra AK, Öngür D, Lencz T, Sarpal DK, Oliver LD. Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions. World Psychiatry 2024; 23:26-51. [PMID: 38214624 PMCID: PMC10786022 DOI: 10.1002/wps.21159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2024] Open
Abstract
Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.
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Affiliation(s)
- Aristotle N Voineskos
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Nicholas H Neufeld
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH, USA
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Cundill Centre for Child and Youth Depression and McCain Centre for Child, Youth and Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Alan Anticevic
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kristin Cadenhead
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anil K Malhotra
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Dost Öngür
- McLean Hospital/Harvard Medical School, Belmont, MA, USA
| | - Todd Lencz
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Deepak K Sarpal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
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3
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An L, Zhang C, Wulan N, Zhang S, Chen P, Ji F, Ng KK, Chen C, Zhou JH, Thomas Yeo BT. DeepResBat: deep residual batch harmonization accounting for covariate distribution differences. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.18.574145. [PMID: 38293022 PMCID: PMC10827218 DOI: 10.1101/2024.01.18.574145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Pooling MRI data from multiple datasets requires harmonization to reduce undesired inter-site variabilities, while preserving effects of biological variables (or covariates). The popular harmonization approach ComBat uses a mixed effect regression framework that explicitly accounts for covariate distribution differences across datasets. There is also significant interest in developing harmonization approaches based on deep neural networks (DNNs), such as conditional variational autoencoder (cVAE). However, current DNN approaches do not explicitly account for covariate distribution differences across datasets. Here, we provide mathematical results, suggesting that not accounting for covariates can lead to suboptimal harmonization outcomes. We propose two DNN-based harmonization approaches that explicitly account for covariate distribution differences across datasets: covariate VAE (coVAE) and DeepResBat. The coVAE approach is a natural extension of cVAE by concatenating covariates and site information with site- and covariate-invariant latent representations. DeepResBat adopts a residual framework inspired by ComBat. DeepResBat first removes the effects of covariates with nonlinear regression trees, followed by eliminating site differences with cVAE. Finally, covariate effects are added back to the harmonized residuals. Using three datasets from three different continents with a total of 2787 participants and 10085 anatomical T1 scans, we find that DeepResBat and coVAE outperformed ComBat, CovBat and cVAE in terms of removing dataset differences, while enhancing biological effects of interest. However, coVAE hallucinates spurious associations between anatomical MRI and covariates even when no association exists. Therefore, future studies proposing DNN-based harmonization approaches should be aware of this false positive pitfall. Overall, our results suggest that DeepResBat is an effective deep learning alternative to ComBat.
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Affiliation(s)
- Lijun An
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Chen Zhang
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Naren Wulan
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Shaoshi Zhang
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Pansheng Chen
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Fang Ji
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Christopher Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
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4
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Kochunov P, Ma Y, Hatch KS, Gao S, Acheson A, Jahanshad N, Thompson PM, Adhikari BM, Bruce H, Van der Vaart A, Chiappelli J, Du X, Sotiras A, Kvarta MD, Ma T, Chen S, Hong LE. Ancestral, Pregnancy, and Negative Early-Life Risks Shape Children's Brain (Dis)similarity to Schizophrenia. Biol Psychiatry 2023; 94:332-340. [PMID: 36948435 PMCID: PMC10511664 DOI: 10.1016/j.biopsych.2023.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 03/24/2023]
Abstract
BACKGROUND Familial, obstetric, and early-life environmental risks for schizophrenia spectrum disorder (SSD) alter normal cerebral development, leading to the formation of characteristic brain deficit patterns prior to onset of symptoms. We hypothesized that the insidious effects of these risks may increase brain similarity to adult SSD deficit patterns in prepubescent children. METHODS We used data collected by the Adolescent Brain Cognitive Development (ABCD) Study (N = 8940, age = 9.9 ± 0.1 years, 4307/4633 female/male), including 727 (age = 9.9 ± 0.1 years, 351/376 female/male) children with family history of SSD, to evaluate unfavorable cerebral effects of ancestral SSD history, pre/perinatal environment, and negative early-life environment. We used a regional vulnerability index to measure the alignment of a child's cerebral patterns with the adult SSD pattern derived from a large meta-analysis of case-control differences. RESULTS In children with a family history of SSD, the regional vulnerability index captured significantly more variance in ancestral history than traditional whole-brain and regional brain measurements. In children with and without family history of SSD, the regional vulnerability index also captured more variance associated with negative pre/perinatal environment and early-life experiences than traditional brain measurements. CONCLUSIONS In summary, in a cohort in which most children will not develop SSD, familial, pre/perinatal, and early developmental risks can alter brain patterns in the direction observed in adult patients with SSD. Individual similarity to adult SSD patterns may provide an early biomarker of the effects of genetic and developmental risks on the brain prior to psychotic or prodromal symptom onset.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland.
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Ashley Acheson
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of the Sunshine Coast, Marina del Rey, California
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of the Sunshine Coast, Marina del Rey, California
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Andrew Van der Vaart
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Aris Sotiras
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, University of Maryland, College Park, Maryland
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
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5
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van de Groep IH, Bos MGN, Popma A, Crone EA, Jansen LMC. A neurocognitive model of early onset persistent and desistant antisocial behavior in early adulthood. Front Hum Neurosci 2023; 17:1100277. [PMID: 37533586 PMCID: PMC10392129 DOI: 10.3389/fnhum.2023.1100277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 06/22/2023] [Indexed: 08/04/2023] Open
Abstract
It remains unclear which functional and neurobiological mechanisms are associated with persistent and desistant antisocial behavior in early adulthood. We reviewed the empirical literature and propose a neurocognitive social information processing model for early onset persistent and desistant antisocial behavior in early adulthood, focusing on how young adults evaluate, act upon, monitor, and learn about their goals and self traits. Based on the reviewed literature, we propose that persistent antisocial behavior is characterized by domain-general impairments in self-relevant and goal-related information processing, regulation, and learning, which is accompanied by altered activity in fronto-limbic brain areas. We propose that desistant antisocial development is associated with more effortful information processing, regulation and learning, that possibly balances self-relevant goals and specific situational characteristics. The proposed framework advances insights by considering individual differences such as psychopathic personality traits, and specific emotional characteristics (e.g., valence of social cues), to further illuminate functional and neural mechanisms underlying heterogenous developmental pathways. Finally, we address important open questions and offer suggestions for future research to improve scientific knowledge on general and context-specific expression and development of antisocial behavior in early adulthood.
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Affiliation(s)
- Ilse H. van de Groep
- Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
- Department of Child and Adolescent Psychiatry and Psychosocial Care, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Marieke G. N. Bos
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, Netherlands
| | - Arne Popma
- Department of Child and Adolescent Psychiatry and Psychosocial Care, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Public Health, Mental Health, Amsterdam, Netherlands
| | - Eveline A. Crone
- Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, Netherlands
| | - Lucres M. C. Jansen
- Department of Child and Adolescent Psychiatry and Psychosocial Care, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Public Health, Mental Health, Amsterdam, Netherlands
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6
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Walton E, Baltramonaityte V, Calhoun V, Heijmans BT, Thompson PM, Cecil CAM. A systematic review of neuroimaging epigenetic research: calling for an increased focus on development. Mol Psychiatry 2023; 28:2839-2847. [PMID: 37185958 PMCID: PMC10615743 DOI: 10.1038/s41380-023-02067-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/03/2023] [Accepted: 04/03/2023] [Indexed: 05/17/2023]
Abstract
Epigenetic mechanisms, such as DNA methylation (DNAm), have gained increasing attention as potential biomarkers and mechanisms underlying risk for neurodevelopmental, psychiatric and other brain-based disorders. Yet, surprisingly little is known about the extent to which DNAm is linked to individual differences in the brain itself, and how these associations may unfold across development - a time of life when many of these disorders emerge. Here, we systematically review evidence from the nascent field of Neuroimaging Epigenetics, combining structural or functional neuroimaging measures with DNAm, and the extent to which the developmental period (birth to adolescence) is represented in these studies. We identified 111 articles published between 2011-2021, out of which only a minority (21%) included samples under 18 years of age. Most studies were cross-sectional (85%), employed a candidate-gene approach (67%), and examined DNAm-brain associations in the context of health and behavioral outcomes (75%). Nearly half incorporated genetic data, and a fourth investigated environmental influences. Overall, studies support a link between peripheral DNAm and brain imaging measures, but there is little consistency in specific findings and it remains unclear whether DNAm markers present a cause, correlate or consequence of brain alterations. Overall, there is large heterogeneity in sample characteristics, peripheral tissue and brain outcome examined as well as the methods used. Sample sizes were generally low to moderate (median nall = 98, ndevelopmental = 80), and attempts at replication or meta-analysis were rare. Based on the strengths and weaknesses of existing studies, we propose three recommendations on how advance the field of Neuroimaging Epigenetics. We advocate for: (1) a greater focus on developmentally oriented research (i.e. pre-birth to adolescence); (2) the analysis of large, prospective, pediatric cohorts with repeated measures of DNAm and imaging to assess directionality; and (3) collaborative, interdisciplinary science to identify robust signals, triangulate findings and enhance translational potential.
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Affiliation(s)
- Esther Walton
- Department of Psychology, University of Bath, Bath, UK.
| | | | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Dept. of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Charlotte A M Cecil
- Molecular Epidemiology, Dept. of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
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7
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Martin D, Basodi S, Panta S, Rootes-Murdy K, Prae P, Sarwate AD, Kelly R, Romero J, Baker BT, Gazula H, Bockholt J, Turner JA, Esper NB, Franco AR, Plis S, Calhoun VD. Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. Front Neuroinform 2023; 17:1207721. [PMID: 37404336 PMCID: PMC10315678 DOI: 10.3389/fninf.2023.1207721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/02/2023] [Indexed: 07/06/2023] Open
Abstract
Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC (The Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation) is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration, and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.
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Affiliation(s)
- Dylan Martin
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Sunitha Basodi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Sandeep Panta
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Paul Prae
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Anand D. Sarwate
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
- Department of Electrical and Computer Engineering, Rutgers University–New Brunswick, Piscataway, NJ, United States
| | - Ross Kelly
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Javier Romero
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Bradley T. Baker
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Harshvardhan Gazula
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Jeremy Bockholt
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Jessica A. Turner
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Nathalia B. Esper
- Center for the Developing Brain, Child Mind Institute, New York, NY, United States
| | - Alexandre R. Franco
- Center for the Developing Brain, Child Mind Institute, New York, NY, United States
- Center for Brain Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, United States
| | - Sergey Plis
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
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8
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Martin D, Basodi S, Panta S, Rootes-Murdy K, Prae P, Sarwate AD, Kelly R, Romero J, Baker BT, Gazula H, Bockholt J, Turner J, Esper NB, Franco AR, Plis S, Calhoun VD. Enhancing Collaborative Neuroimaging Research: Introducing COINSTAC Vaults for Federated Analysis and Reproducibility. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.08.539852. [PMID: 37214791 PMCID: PMC10197552 DOI: 10.1101/2023.05.08.539852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies.
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9
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Schijven D, Postema MC, Fukunaga M, Matsumoto J, Miura K, de Zwarte SMC, van Haren NEM, Cahn W, Hulshoff Pol HE, Kahn RS, Ayesa-Arriola R, Ortiz-García de la Foz V, Tordesillas-Gutierrez D, Vázquez-Bourgon J, Crespo-Facorro B, Alnæs D, Dahl A, Westlye LT, Agartz I, Andreassen OA, Jönsson EG, Kochunov P, Bruggemann JM, Catts SV, Michie PT, Mowry BJ, Quidé Y, Rasser PE, Schall U, Scott RJ, Carr VJ, Green MJ, Henskens FA, Loughland CM, Pantelis C, Weickert CS, Weickert TW, de Haan L, Brosch K, Pfarr JK, Ringwald KG, Stein F, Jansen A, Kircher TTJ, Nenadić I, Krämer B, Gruber O, Satterthwaite TD, Bustillo J, Mathalon DH, Preda A, Calhoun VD, Ford JM, Potkin SG, Chen J, Tan Y, Wang Z, Xiang H, Fan F, Bernardoni F, Ehrlich S, Fuentes-Claramonte P, Garcia-Leon MA, Guerrero-Pedraza A, Salvador R, Sarró S, Pomarol-Clotet E, Ciullo V, Piras F, Vecchio D, Banaj N, Spalletta G, Michielse S, van Amelsvoort T, Dickie EW, Voineskos AN, Sim K, Ciufolini S, Dazzan P, Murray RM, Kim WS, Chung YC, Andreou C, Schmidt A, Borgwardt S, McIntosh AM, Whalley HC, Lawrie SM, du Plessis S, Luckhoff HK, Scheffler F, Emsley R, Grotegerd D, Lencer R, Dannlowski U, Edmond JT, Rootes-Murdy K, Stephen JM, Mayer AR, Antonucci LA, Fazio L, Pergola G, Bertolino A, Díaz-Caneja CM, Janssen J, Lois NG, Arango C, Tomyshev AS, Lebedeva I, Cervenka S, Sellgren CM, Georgiadis F, Kirschner M, Kaiser S, Hajek T, Skoch A, Spaniel F, Kim M, Kwak YB, Oh S, Kwon JS, James A, Bakker G, Knöchel C, Stäblein M, Oertel V, Uhlmann A, Howells FM, Stein DJ, Temmingh HS, Diaz-Zuluaga AM, Pineda-Zapata JA, López-Jaramillo C, Homan S, Ji E, Surbeck W, Homan P, Fisher SE, Franke B, Glahn DC, Gur RC, Hashimoto R, Jahanshad N, Luders E, Medland SE, Thompson PM, Turner JA, van Erp TGM, Francks C. Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium. Proc Natl Acad Sci U S A 2023; 120:e2213880120. [PMID: 36976765 PMCID: PMC10083554 DOI: 10.1073/pnas.2213880120] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 02/03/2023] [Indexed: 03/29/2023] Open
Abstract
Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
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Affiliation(s)
- Dick Schijven
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
| | - Merel C. Postema
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam1081 HZ, The Netherlands
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki444-8585, Japan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Sonja M. C. de Zwarte
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - Neeltje E. M. van Haren
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center Sophia Children's Hospital, Rotterdam3015 CN, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - Hilleke E. Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - René S. Kahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY10029
- The Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, New York, NY10468
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, Instituto de Investigación Marqués de Valdecilla, University Hospital Marqués de Valdecilla, Santander39008, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander39011, Spain
| | - Víctor Ortiz-García de la Foz
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, Instituto de Investigación Sanitaria Valdecilla, School of Medicine, University of Cantabria, Santander39011, Spain
| | - Diana Tordesillas-Gutierrez
- Department of Radiology, Instituto de Investigación Marqués de Valdecilla, Marqués de Valdecilla University Hospital, Santander39011, Spain
- Advanced Computing and e-Science, Instituto de Física de Cantabria, Universidad de Cantabria - Consejo Superior de Investigaciones Científicas, Santander39005, Spain
| | - Javier Vázquez-Bourgon
- Department of Psychiatry, Instituto de Investigación Marqués de Valdecilla, University Hospital Marqués de Valdecilla, Santander39008, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
| | - Benedicto Crespo-Facorro
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Psychiatry, School of Medicine, University of Sevilla, University Hospital Virgen del Rocío, Consejo Superior de Investigaciones Científicas - Instituto de Biomedicina de Sevilla, Sevilla41013, Spain
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychology, University of Oslo, Oslo0373, Norway
- Bjørknes College, Oslo0456, Norway
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo0373, Norway
| | - Lars T. Westlye
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychology, University of Oslo, Oslo0373, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo0372, Norway
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo0450, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo0373, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo0372, Norway
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD21201
| | - Jason M. Bruggemann
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Edith Collins Centre (Translational Research in Alcohol, Drugs & Toxicology), Sydney Local Health District, Sydney2050, Australia
- Specialty of Addiction Medicine, Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney2006, Australia
| | - Stanley V. Catts
- School of Medicine, The University of Queensland, Brisbane4006, Australia
| | - Patricia T. Michie
- School of Psychological Sciences, University of Newcastle, Newcastle2308, Australia
| | - Bryan J. Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane4072, Australia
- Queensland Centre for Mental Health Research, The University of Queensland, Brisbane4076, Australia
| | - Yann Quidé
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Paul E. Rasser
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle2308, Australia
- Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Newcastle2308, Australia
- Hunter Medical Research Institute, Newcastle2305, Australia
| | - Ulrich Schall
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle2308, Australia
| | - Rodney J. Scott
- School of Biomedical Science and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle2308, Australia
| | - Vaughan J. Carr
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Melissa J. Green
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Frans A. Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle2308, Australia
- PRC for Health Behaviour, Hunter Medical Research Institute, Newcastle2305, Australia
| | - Carmel M. Loughland
- School of Medicine and Public Health, University of Newcastle, Newcastle2308, Australia
- Hunter New England Mental Health Service, Newcastle2305, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne3053, Australia
| | - Cynthia Shannon Weickert
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY13210
| | - Thomas W. Weickert
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY13210
| | - Lieuwe de Haan
- Early Psychosis Department, Department of Psychiatry, Amsterdam UMC (location AMC), Amsterdam1105 AZ, The Netherlands
- Arkin Institute for Mental Health, Amsterdam1033 NN, The Netherlands
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Kai G. Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
- Core-Facility Brainimaging, Faculty of Medicine, Philipps-Universität Marburg, Marburg35032, Germany
| | - Tilo T. J. Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Bernd Krämer
- Department of General Psychiatry, Section for Experimental Psychopathology and Neuroimaging, Heidelberg University, Heidelberg69115, Germany
| | - Oliver Gruber
- Department of General Psychiatry, Section for Experimental Psychopathology and Neuroimaging, Heidelberg University, Heidelberg69115, Germany
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, PA19104
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Juan Bustillo
- Department of Psychiatry and Neuroscience, University of New Mexico, Albuquerque, NM87106
| | - Daniel H. Mathalon
- Department of Psychiatry and Behavioral Sciences and Weill Institute for Neurosciences, University of California, San Francisco, CA94143
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA94121
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
| | - Vince D. Calhoun
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA30303
| | - Judith M. Ford
- San Francisco VA Medical Center, University of California, San Francisco, CA94121
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
- Long Beach VA Health Care System, Long Beach, CA90822
| | - Jingxu Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Hong Xiang
- Chongqing University Three Gorges Hospital, Chongqing404188, P.R. China
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Fabio Bernardoni
- Division of Psychological and Social Medicine and Developmental Neurosciences, Translational Developmental Neuroscience Section, Technische Universität Dresden, University Hospital C.G. Carus, Dresden01307, Germany
- Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden01307, Germany
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Translational Developmental Neuroscience Section, Technische Universität Dresden, University Hospital C.G. Carus, Dresden01307, Germany
- Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden01307, Germany
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Maria Angeles Garcia-Leon
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Benito Menni Complex Assistencial en Salut Mental, Barcelona08830, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Valentina Ciullo
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX77030
| | - Stijn Michielse
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Erin W. Dickie
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoM5S 2S1, Canada
- Department of Psychiatry, University of Toronto, TorontoM5T 1R8, Canada
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoM5S 2S1, Canada
- Department of Psychiatry, University of Toronto, TorontoM5T 1R8, Canada
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore539747, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore119228, Singapore
| | - Simone Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Robin M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju54896, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University-Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju54896, Republic of Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju54896, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University-Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju54896, Republic of Korea
| | - Christina Andreou
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
| | - André Schmidt
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
| | - Stefan Borgwardt
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
| | - Andrew M. McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Heather C. Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Stephen M. Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Stefan du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
- Stellenbosch University Genomics of Brain Disorders Research Unit, South African Medical Research Council, Cape Town7505, South Africa
| | - Hilmar K. Luckhoff
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
| | - Freda Scheffler
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
| | - Robin Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Jesse T. Edmond
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
| | - Kelly Rootes-Murdy
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
| | | | | | - Linda A. Antonucci
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari70121, Italy
| | - Leonardo Fazio
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
- Psychiatry Unit, Bari University Hospital, Bari70121, Italy
| | - Covadonga M. Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
- School of Medicine, Universidad Complutense, Madrid28040, Spain
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
| | - Noemi G. Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
- School of Medicine, Universidad Complutense, Madrid28040, Spain
| | - Alexander S. Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow115522, Russian Federation
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow115522, Russian Federation
| | - Simon Cervenka
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala751 85, Sweden
| | - Carl M. Sellgren
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm171 65, Sweden
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Montreal Neurological Institute, McGill University, MontrealH3A 2B4, Canada
| | - Stefan Kaiser
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Department of Psychiatry, Division of Adult Psychiatry, Geneva University Hospitals, Geneva1202, Switzerland
| | - Tomas Hajek
- National Institute of Mental Health, Klecany250 67, Czech Republic
- Department of Psychiatry, Dalhousie University, HalifaxB3H 2E2, Canada
| | - Antonin Skoch
- National Institute of Mental Health, Klecany250 67, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague140 21, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany250 67, Czech Republic
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul08826, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul08826, Republic of Korea
| | - Sanghoon Oh
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul08826, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Anthony James
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
| | - Geor Bakker
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Christian Knöchel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Michael Stäblein
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Viola Oertel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Department of Child and Adolescent Psychiatry, Technische Universität Dresden, Dresden01187, Germany
| | - Fleur M. Howells
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
| | - Dan J. Stein
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
- SA MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town, Cape Town7505, South Africa
| | - Henk S. Temmingh
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
| | - Ana M. Diaz-Zuluaga
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Julian A. Pineda-Zapata
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Carlos López-Jaramillo
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Zurich8050, Switzerland
| | - Ellen Ji
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Werner Surbeck
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY11030
- Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, New York, NY11004
- Department of Psychiatry, Zucker School of Medicine at Northwell/Hofstra, New York, NY11549
| | - Simon E. Fisher
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
| | - Barbara Franke
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
| | - David C. Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA02115
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT06102
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, PA19104
- Department of Radiology, Perelman School of Medicine, Philadelphia, PA19104
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA19104
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Eileen Luders
- School of Psychology, University of Auckland, Auckland1010, New Zealand
- Department of Women’s and Children’s Health, Uppsala University, Uppsala752 37, Sweden
- Laboratory of Neuro Imaging, School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane4006, Australia
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Jessica A. Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA30303
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA92697
| | - Clyde Francks
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
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10
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Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature. Neuropsychol Rev 2023; 33:42-121. [PMID: 33721207 DOI: 10.1007/s11065-021-09485-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 02/09/2021] [Indexed: 12/14/2022]
Abstract
There is evidence that diffusion-weighted imaging (DWI) is able to detect tissue alterations following mild traumatic brain injury (mTBI) that may not be observed on conventional neuroimaging; however, findings are often inconsistent between studies. This systematic review assesses patterns of differences in DWI metrics between those with and without a history of mTBI. A PubMed literature search was performed using relevant indexing terms for articles published prior to May 14, 2020. Findings were limited to human studies using DWI in mTBI. Articles were excluded if they were not full-length, did not contain original data, if they were case studies, pertained to military populations, had inadequate injury severity classification, or did not report post-injury interval. Findings were reported independently for four subgroups: acute/subacute pediatric mTBI, acute/subacute adult mTBI, chronic adult mTBI, and sport-related concussion, and all DWI acquisition and analysis methods used were included. Patterns of findings between studies were reported, along with strengths and weaknesses of the current state of the literature. Although heterogeneity of sample characteristics and study methods limited the consistency of findings, alterations in DWI metrics were most commonly reported in the corpus callosum, corona radiata, internal capsule, and long association pathways. Many acute/subacute pediatric studies reported higher FA and lower ADC or MD in various regions. In contrast, acute/subacute adult studies most commonly indicate lower FA within the context of higher MD and RD. In the chronic phase of recovery, FA may remain low, possibly indicating overall demyelination or Wallerian degeneration over time. Longitudinal studies, though limited, generally indicate at least a partial normalization of DWI metrics over time, which is often associated with functional improvement. We conclude that DWI is able to detect structural mTBI-related abnormalities that may persist over time, although future DWI research will benefit from larger samples, improved data analysis methods, standardized reporting, and increasing transparency.
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11
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Wu X, Yang Q, Xu C, Huo H, Seger CA, Peng Z, Chen Q. Connectome-based predictive modeling of compulsion in obsessive-compulsive disorder. Cereb Cortex 2023; 33:1412-1425. [PMID: 35443038 DOI: 10.1093/cercor/bhac145] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 11/13/2022] Open
Abstract
Compulsion is one of core symptoms of obsessive-compulsive disorder (OCD). Although many studies have investigated the neural mechanism of compulsion, no study has used brain-based measures to predict compulsion. Here, we used connectome-based predictive modeling (CPM) to identify networks that could predict the levels of compulsion based on whole-brain functional connectivity in 57 OCD patients. We then applied a computational lesion version of CPM to examine the importance of specific brain areas. We also compared the predictive network strength in OCD with unaffected first-degree relatives (UFDR) of patients and healthy controls. CPM successfully predicted individual level of compulsion and identified networks positively (primarily subcortical areas of the striatum and limbic regions of the hippocampus) and negatively (primarily frontoparietal regions) correlated with compulsion. The prediction power of the negative model significantly decreased when simulating lesions to the prefrontal cortex and cerebellum, supporting the importance of these regions for compulsion prediction. We found a similar pattern of network strength in the negative predictive network for OCD patients and their UFDR, demonstrating the potential of CPM to identify vulnerability markers for psychopathology.
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Affiliation(s)
- Xiangshu Wu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, 510631, China.,School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Qiong Yang
- Affiliated Brain Hospital of Guangzhou Medical University, 510370 Guangzhou, China
| | - Chuanyong Xu
- Department of Child Psychiatry and Rehabilitation, Institute of Maternity and Child Medical Research, Affiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen 518047, China
| | - Hangfeng Huo
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, 510631, China.,School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Carol A Seger
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, 510631, China.,School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China.,Department of Psychology, Colorado State University, Fort Collins, CO 80523, United States
| | - Ziwen Peng
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, 510631, China.,School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China.,Department of Child Psychiatry, Shenzhen Kangning Hospital, Shenzhen University School of Medicine, Shenzhen 518061, China
| | - Qi Chen
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, 510631, China.,School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
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12
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Zhang-James Y, Razavi AS, Hoogman M, Franke B, Faraone SV. Machine Learning and MRI-based Diagnostic Models for ADHD: Are We There Yet? J Atten Disord 2023; 27:335-353. [PMID: 36651494 DOI: 10.1177/10870547221146256] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Machine learning (ML) has been applied to develop magnetic resonance imaging (MRI)-based diagnostic classifiers for attention-deficit/hyperactivity disorder (ADHD). This systematic review examines this literature to clarify its clinical significance and to assess the implications of the various analytic methods applied. METHODS A comprehensive literature search on MRI-based diagnostic classifiers for ADHD was performed and data regarding the utilized models and samples were gathered. RESULTS We found that, although most studies reported the classification accuracies, they varied in choice of MRI modalities, ML models, cross-validation and testing methods, and sample sizes. We found that the accuracies of cross-validation methods inflated the performance estimation compared with those of a held-out test, compromising the model generalizability. Test accuracies have increased with publication year but were not associated with training sample sizes. Improved test accuracy over time was likely due to the use of better ML methods along with strategies to deal with data imbalances. CONCLUSION Ultimately, large multi-modal imaging datasets, and potentially the combination with other types of data, like cognitive data and/or genetics, will be essential to achieve the goal of developing clinically useful imaging classification tools for ADHD in the future.
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Affiliation(s)
| | | | - Martine Hoogman
- Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
| | - Barbara Franke
- Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
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13
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Abstract
BACKGROUND A number of recent investigations have focused on the neurobiology of obsessive-compulsive personality disorder (OCPD). However, there have been few reviews of this literature with no detailed model proposed. We therefore undertook a systematic review of these investigations, aiming to map the available evidence and investigate whether it is possible to formulate a detailed model of the neurobiology of OCPD. METHODS OCPD can be considered from both categorical and dimensional perspectives. An electronic search was therefore conducted using terms that would address not only OCPD as a category, but also related constructs, such as perfectionism, that would capture research on neuropsychology, neuroimaging, neurochemistry, and neurogenetics. RESULTS A total of 1059 articles were retrieved, with 87 ultimately selected for abstract screening, resulting in a final selection of 49 articles focusing on neurobiological investigations relevant to OCPD. Impaired executive function and cognitive inflexibility are common neuropsychological traits in this condition, and suggest that obsessive-compulsive disorder (OCD) and OCPD may lie on a continuum. However, neuroimaging studies in OCPD indicate the involvement of specific neurocircuitry, including the precuneus and amygdala, and so suggest that OCD and OCPD may have important differences. Although OCPD has a heritable component, we found no well-powered genetic studies of OCPD. CONCLUSION Although knowledge in this area has advanced, there are insufficient data on which to base a comprehensive model of the neurobiology of OCPD. Given the clinical importance of OCPD, further work to understand the mechanisms that underpin this condition is warranted.
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14
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Liu J, Chen Y, Shan X, Wang H. Association between CILP and IL-1α polymorphisms and phenotype-dependent intervertebral disc degeneration susceptibility: A meta-analysis. Front Genet 2022; 13:1005393. [PMID: 36276953 PMCID: PMC9582649 DOI: 10.3389/fgene.2022.1005393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/15/2022] [Indexed: 11/13/2022] Open
Abstract
Background: The relationship between CILP (1184T>C) and IL-1α(+889C/T) polymorphisms and intervertebral disc degeneration (IDD) have been explored in several studies but the results were conflicting. The aim of the study was to evaluate and synthesize the currently available data on the association between CILP (1184T>C) and IL-1α(+889C/T) polymorphisms and susceptibility of phenotype-dependent radiologic IDD (RIDD) and symptomatic intervertebral disk herniation (SIDH).Methods: A computerized literature search was in PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure database, and Web of Science. The pooled results were presented as odds ratios (ORs) with 95% confidence intervals (CIs). Moreover, the false-positive report probability (FPRP) test and trial sequential analysis (TSA) were applied to estimate the significant results.Results: Our evidence demonstrated that IL-1α(+889C/T) was significant associated with RIDD (allele model: OR = 1.34, 95%CI 1.03–1.74, p = 0.029) and SIDH (allele model: OR = 1.28, 95% CI 1.03–1.60, p = 0.028). However, the results were not noteworthy under the FPRP test and TSA analysis. Additionally, CILP (1184T>C) polymorphism was significantly associated with RIDD with adequate evidence (allele model: OR = 1.27, 95% CI 1.09–1.48, p = 0.002) instead of SIDH.Conclusion: The current meta-analysis illustrated firm evidence that CILP (1184T>C) polymorphism was significantly associated with the susceptibility of RIDD. However, the significant associations between IL-1α(+889C/T) and RIDD and SIDH were less credible. Thus, more multi-center studies with diverse populations were required to verify the results.
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Affiliation(s)
- Jiachen Liu
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yunxia Chen
- Department of Endocrinology, Cangzhou People’s Hospital, Cangzhou, China
| | - Xiuqi Shan
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Huan Wang
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, China
- *Correspondence: Huan Wang,
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15
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Stillman CM, Jakicic JM, Rogers RJ, Roecklein KA, Barrett G, Kang C, Erickson KI. The relationship between fat mass and obesity associated gene polymorphism rs9939609 and resting cerebral blood flow in a midlife sample with overweight and obesity. Front Hum Neurosci 2022; 16:904545. [PMID: 36072887 PMCID: PMC9443082 DOI: 10.3389/fnhum.2022.904545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity associated fat mass and obesity associated gene (FTO) gene has been linked with increased BMI in adults. Higher BMI has been associated with poor brain health and may exert deleterious effects on neurocognitive health through cerebral hypoperfusion. However, it is unclear if there is a relationship between the FTO genotype and cerebral perfusion, or whether FTO genotype moderates the effects of weight loss on cerebral perfusion. Using data from a randomized controlled behavioral weight loss trial in adults with overweight and obesity, we tested (1) whether carriers of the A allele for FTO rs9939609 demonstrate different patterns of resting cerebral blood flow (rCBF) compared to T carriers, and (2) whether the FTO genotype moderates the effects of weight loss on rCBF. We hypothesized that carriers of the A allele would exhibit lower resting CBF in frontal brain areas compared to T/T homozygotes at baseline, and that intervention-induced weight loss may partially remediate these differences.Methods and resultsOne hundred and five adults (75.2% female, mean age 44.9 years) with overweight or obesity were included in the analyses. These participants represent a subsample of participants in a larger randomized controlled trial (NCT01500356). A resting pseudo-continuous arterial spin labeling (pCASL) scan was acquired to examine rCBF. Age, sex, and BMI were included as covariates. At baseline, A carriers had greater rCBF in a diffuse cluster extending into the brainstem, motor cortex, and occipital lobe, but lower perfusion in the temporal lobe. We found no evidence that FTO moderated the effect of the intervention group assignment on rCBF changes.ConclusionOverall, these results indicate that (a) individual variation in rCBF within a sample with overweight and obesity may be attributed to a common FTO variant, but (b) a weight loss intervention is effective at increasing rCBF, regardless of FTO genotype.
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Affiliation(s)
- Chelsea M. Stillman
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Chelsea M. Stillman,
| | - John M. Jakicic
- Division of Physical Activity and Weight Management, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, MO, United States
| | | | - Kathryn A. Roecklein
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Grant Barrett
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Chaeryon Kang
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Kirk I. Erickson
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States
- PROFITH “PROmoting FITness and Health Through Physical Activity” Research Group, Sport and Health University Research Institute (iMUDS), Department of Physical and Sports Education, Faculty of Sport Sciences, University of Granada, Granada, Spain
- AdventHealth Research Institute, Neuroscience Institute, Orlando, FL, United States
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16
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An L, Chen J, Chen P, Zhang C, He T, Chen C, Zhou JH, Yeo BTT. Goal-specific brain MRI harmonization. Neuroimage 2022; 263:119570. [PMID: 35987490 DOI: 10.1016/j.neuroimage.2022.119570] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 08/05/2022] [Accepted: 08/15/2022] [Indexed: 11/19/2022] Open
Abstract
There is significant interest in pooling magnetic resonance image (MRI) data from multiple datasets to enable mega-analysis. Harmonization is typically performed to reduce heterogeneity when pooling MRI data across datasets. Most MRI harmonization algorithms do not explicitly consider downstream application performance during harmonization. However, the choice of downstream application might influence what might be considered as study-specific confounds. Therefore, ignoring downstream applications during harmonization might potentially limit downstream performance. Here we propose a goal-specific harmonization framework that utilizes downstream application performance to regularize the harmonization procedure. Our framework can be integrated with a wide variety of harmonization models based on deep neural networks, such as the recently proposed conditional variational autoencoder (cVAE) harmonization model. Three datasets from three different continents with a total of 2787 participants and 10,085 anatomical T1 scans were used for evaluation. We found that cVAE removed more dataset differences than the widely used ComBat model, but at the expense of removing desirable biological information as measured by downstream prediction of mini mental state examination (MMSE) scores and clinical diagnoses. On the other hand, our goal-specific cVAE (gcVAE) was able to remove as much dataset differences as cVAE, while improving downstream cross-sectional prediction of MMSE scores and clinical diagnoses.
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Affiliation(s)
- Lijun An
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Jianzhong Chen
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Pansheng Chen
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Chen Zhang
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Tong He
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore
| | - Christopher Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
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17
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Cheon EJ, Bearden CE, Sun D, Ching CRK, Andreassen OA, Schmaal L, Veltman DJ, Thomopoulos SI, Kochunov P, Jahanshad N, Thompson PM, Turner JA, van Erp TG. Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings. Psychiatry Clin Neurosci 2022; 76:140-161. [PMID: 35119167 PMCID: PMC9098675 DOI: 10.1111/pcn.13337] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 11/29/2021] [Accepted: 01/21/2022] [Indexed: 12/25/2022]
Abstract
This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.
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Affiliation(s)
- Eun-Jin Cheon
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Department of Psychiatry, Yeungnam University College of Medicine, Yeungnam University Medical Center, Daegu, Republic of Korea
| | - Carrie E. Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Daqiang Sun
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
- Department of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ole A. Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, Parkville, Australia
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlant, GA, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
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18
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Zhang F, Daducci A, He Y, Schiavi S, Seguin C, Smith RE, Yeh CH, Zhao T, O'Donnell LJ. Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review. Neuroimage 2022; 249:118870. [PMID: 34979249 PMCID: PMC9257891 DOI: 10.1016/j.neuroimage.2021.118870] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 12/03/2021] [Accepted: 12/31/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
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Affiliation(s)
- Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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19
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Bostami B, Hillary FG, van der Horn HJ, van der Naalt J, Calhoun VD, Vergara VM. A Decentralized ComBat Algorithm and Applications to Functional Network Connectivity. Front Neurol 2022; 13:826734. [PMID: 35370895 PMCID: PMC8965063 DOI: 10.3389/fneur.2022.826734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/09/2022] [Indexed: 11/13/2022] Open
Abstract
Recent studies showed that working with neuroimage data collected from different research facilities or locations may incur additional source dependency, affecting the overall statistical power. This problem can be mitigated with data harmonization approaches. Recently, the ComBat method has become commonly adopted for various neuroimage modalities. While open neuroimaging datasets are becoming more common, a substantial amount of data is still unable to be shared for various reasons. In addition, current approaches require moving all the data to a central location, which requires additional resources and creates redundant copies of the same datasets. To address these issues, we propose a decentralized harmonization approach that does not create redundant copies of the original datasets and performs remote operations on the datasets separately without sharing any individual subject data, ensuring a certain level of privacy and reducing regulatory hurdles. We proposed a novel approach called "Decentralized ComBat" which can harmonize datasets separately without combining the datasets. We tested our model by harmonizing functional network connectivity datasets from two traumatic brain injury studies in a decentralized way. Also, we used simulations to analyze the performance and scalability of our model when the number of data collection sites increases. We compare the output with centralized ComBat and show that the proposed approach produces similar results, increasing the sensitivity of the functional network connectivity analysis and validating our approach. Simulations show that our model can be easily scaled to many more datasets based on the requirement. In sum, we believe this provides a powerful tool, further complementing open data and allowing for integrating public and private datasets.
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Affiliation(s)
- Biozid Bostami
- Department of Computer Science, Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
- Department of Computer Science, Emory University, Atlanta, GA, United States
| | - Frank G. Hillary
- Department of Psychology, Penn State University, State College, PA, United States
| | - Harm Jan van der Horn
- Department of Developmental Neurology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Joukje van der Naalt
- Department of Medical Sciences, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Vince D. Calhoun
- Department of Computer Science, Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
- Department of Computer Science, Emory University, Atlanta, GA, United States
| | - Victor M. Vergara
- Department of Computer Science, Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
- Department of Computer Science, Emory University, Atlanta, GA, United States
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20
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Rabinowitz JA, Campos AI, Ong JS, García-Marín LM, Alcauter S, Mitchell BL, Grasby KL, Cuéllar-Partida G, Gillespie NA, Huhn AS, Martin NG, Thompson PM, Medland SE, Maher BS, Rentería ME. Shared Genetic Etiology between Cortical Brain Morphology and Tobacco, Alcohol, and Cannabis Use. Cereb Cortex 2022; 32:796-807. [PMID: 34379727 PMCID: PMC8841600 DOI: 10.1093/cercor/bhab243] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 06/23/2021] [Accepted: 06/24/2021] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified genetic variants associated with brain morphology and substance use behaviors (SUB). However, the genetic overlap between brain structure and SUB has not been well characterized. We leveraged GWAS summary data of 71 brain imaging measures and alcohol, tobacco, and cannabis use to investigate their genetic overlap using linkage disequilibrium score regression. We used genomic structural equation modeling to model a "common SUB genetic factor" and investigated its genetic overlap with brain structure. Furthermore, we estimated SUB polygenic risk scores (PRS) and examined whether they predicted brain imaging traits using the Adolescent Behavior and Cognitive Development (ABCD) study. We identified 8 significant negative genetic correlations, including between (1) alcoholic drinks per week and average cortical thickness, and (2) intracranial volume with age of smoking initiation. We observed 5 positive genetic correlations, including those between (1) insula surface area and lifetime cannabis use, and (2) the common SUB genetic factor and pericalcarine surface area. SUB PRS were associated with brain structure variation in ABCD. Our findings highlight a shared genetic etiology between cortical brain morphology and SUB and suggest that genetic variants associated with SUB may be causally related to brain structure differences.
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Affiliation(s)
- Jill A Rabinowitz
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Adrian I Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Jue-Sheng Ong
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Luis M García-Marín
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Sarael Alcauter
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro 76230, México
| | - Brittany L Mitchell
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Science, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Queensland 4059, Australia
| | - Katrina L Grasby
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Gabriel Cuéllar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Queensland 4102, Australia
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Andrew S Huhn
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Baltimore, MD 21205, USA
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA 90007, USA
| | - Sarah E Medland
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Brion S Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4072, Australia
- School of Biomedical Science, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Queensland 4059, Australia
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21
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Dima D, Modabbernia A, Papachristou E, Doucet GE, Agartz I, Aghajani M, Akudjedu TN, Albajes‐Eizagirre A, Alnæs D, Alpert KI, Andersson M, Andreasen NC, Andreassen OA, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur‐Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Buckner RL, Calhoun V, Canales‐Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Cervenka S, Chaim‐Avancini TM, Ching CRK, Chubar V, Clark VP, Conrod P, Conzelmann A, Crespo‐Facorro B, Crivello F, Crone EA, Dannlowski U, Dale AM, Davey C, de Geus EJC, de Haan L, de Zubicaray GI, den Braber A, Dickie EW, Di Giorgio A, Doan NT, Dørum ES, Ehrlich S, Erk S, Espeseth T, Fatouros‐Bergman H, Fisher SE, Fouche J, Franke B, Frodl T, Fuentes‐Claramonte P, Glahn DC, Gotlib IH, Grabe H, Grimm O, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Hahn T, Harrison BJ, Hartman CA, Hatton SN, Heinz A, Heslenfeld DJ, Hibar DP, Hickie IB, Ho B, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James A, Jernigan TL, Jiang J, Jönsson EG, Joska JA, Kahn R, Kalnin A, Kanai R, Klein M, Klyushnik TP, Koenders L, Koops S, Krämer B, Kuntsi J, Lagopoulos J, Lázaro L, Lebedeva I, Lee WH, Lesch K, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez‐Zalacaín I, Mataix‐Cols D, Mazoyer B, McDonald C, McDonald BC, McIntosh AM, McMahon KL, McPhilemy G, Meinert S, Menchón JM, Medland SE, Meyer‐Lindenberg A, Naaijen J, Najt P, Nakao T, Nordvik JE, Nyberg L, Oosterlaan J, de la Foz VO, Paloyelis Y, Pauli P, Pergola G, Pomarol‐Clotet E, Portella MJ, Potkin SG, Radua J, Reif A, Rinker DA, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sánchez‐Juan P, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Schmaal L, Schnell K, Schumann G, Sim K, Smoller JW, Sommer I, Soriano‐Mas C, Stein DJ, Strike LT, Swagerman SC, Tamnes CK, Temmingh HS, Thomopoulos SI, Tomyshev AS, Tordesillas‐Gutiérrez D, Trollor JN, Turner JA, Uhlmann A, van den Heuvel OA, van den Meer D, van der Wee NJA, van Haren NEM, van't Ent D, van Erp TGM, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Walton E, Wang L, Wang Y, Wassink TH, Weber B, Wen W, West JD, Westlye LT, Whalley H, Wierenga LM, Williams SCR, Wittfeld K, Wolf DH, Worker A, Wright MJ, Yang K, Yoncheva Y, Zanetti MV, Ziegler GC, Thompson PM, Frangou S. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years. Hum Brain Mapp 2022; 43:452-469. [PMID: 33570244 PMCID: PMC8675429 DOI: 10.1002/hbm.25320] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 11/27/2020] [Accepted: 12/06/2020] [Indexed: 12/25/2022] Open
Abstract
Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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Affiliation(s)
- Danai Dima
- Department of Psychology, School of Arts and Social SciencesCity University of LondonLondonUK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | | | | | | | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam University Medical CentreLocation VUmcAmsterdamNetherlands
- Institute of Education & Child StudiesSection Forensic Family & Youth Care, Leiden UniversityNetherlands
| | - Theophilus N. Akudjedu
- Institute of Medical Imaging and Visualisation, Department of Medical Science and Public Health, Faculty of Health and Social SciencesBournemouth UniversityPooleUK
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandDublinIreland
| | - Anton Albajes‐Eizagirre
- FIDMAG Germanes HospitalàriesMadridSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Division of Mental Health and Addiction, Institute of Clinical MedicineUniversity of OsloOsloNorway
| | | | - Micael Andersson
- Department of Integrative Medical BiologyUmeå UniversityUmeåSweden
| | - Nancy C. Andreasen
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Philip Asherson
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityMannheimGermany
| | - Nuria Bargallo
- Imaging Diagnostic Centre, Hospital ClinicBarcelona University ClinicBarcelonaSpain
- August Pi i Sunyer Biomedical Research Institut (IDIBAPS)BarcelonaSpain
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityMannheimGermany
| | - Ramona Baur‐Streubel
- Department of Psychology, Biological Psychology, Clinical Psychology and PsychotherapyUniversity of WürzburgWurzburgGermany
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari Aldo MoroBariItaly
| | - Aurora Bonvino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari Aldo MoroBariItaly
| | - Dorret I. Boomsma
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Stefan Borgwardt
- Department of Psychiatry & PsychotherapyUniversity of LübeckLubeckGermany
| | - Josiane Bourque
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityMannheimGermany
| | - Alan Breier
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesSydneyAustralia
| | - Rachel M. Brouwer
- Rudolf Magnus Institute of NeuroscienceUniversity Medical Center UtrechtUtrechtNetherlands
| | - Jan K. Buitelaar
- Donders Center of Medical NeurosciencesRadboud UniversityNijmegenNetherlands
- Donders Centre for Cognitive NeuroimagingRadboud UniversityNijmegenNetherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
| | - Geraldo F. Busatto
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Randy L. Buckner
- Department of Psychology, Center for Brain ScienceHarvard UniversityCambridgeMassachusettsUSA
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Vincent Calhoun
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, USA Neurology, Radiology, Psychiatry and Biomedical EngineeringEmory UniversityAtlantaGeorgiaUSA
| | | | - Dara M. Cannon
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandDublinIreland
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUK
| | | | - Simon Cervenka
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
- Stockholm Health Care ServicesStockholm RegionStockholmSweden
| | - Tiffany M. Chaim‐Avancini
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Victoria Chubar
- Department of NeuroscienceKU Leuven, Mind‐Body Research GroupLeuvenBelgium
| | - Vincent P. Clark
- Department of PsychologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
- Mind Research NetworkAlbuquerqueNew MexicoUSA
| | - Patricia Conrod
- Department of PsychiatryUniversité de MontréalMontrealCanada
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and PsychotherapyUniversity of TübingenTubingenGermany
| | - Benedicto Crespo‐Facorro
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- HU Virgen del Rocio, IBiS, University of SevillaSevillaSpain
| | - Fabrice Crivello
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxTalenceFrance
| | - Eveline A. Crone
- Erasmus School of Social and Behavioural SciencesErasmus University RotterdamRotterdamNetherlands
- Faculteit der Sociale Wetenschappen, Instituut PsychologieUniversiteit LeidenLeidenNetherlands
| | - Udo Dannlowski
- Department of Psychiatry and PsychotherapyUniversity of MünsterMunsterGermany
| | - Anders M. Dale
- Center for Multimodal Imaging and Genetics, Department of Neuroscience and Department of RadiologyUniversity of California‐San DiegoLa JollaCaliforniaUSA
| | | | - Eco J. C. de Geus
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Lieuwe de Haan
- Academisch Medisch CentrumUniversiteit van AmsterdamAmsterdamNetherlands
| | - Greig I. de Zubicaray
- Faculty of Health, Institute of Health and Biomedical InnovationQueensland University of TechnologyBrisbaneAustralia
| | - Anouk den Braber
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Erin W. Dickie
- Kimel Family Translational Imaging Genetics LaboratoryCampbell Family Mental Health Research Institute, CAMHTorontoCanada
- Department of PsychiatryUniversity of TorontoTorontoCanada
| | - Annabella Di Giorgio
- Biological Psychiatry Lab, Fondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (FG)Italy
| | - Nhat Trung Doan
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Erlend S. Dørum
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
- Sunnaas Rehabilitation Hospital HTNesoddenNorway
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental NeurosciencesTechnische Universität DresdenDresdenGermany
- Faculty of MedicineUniversitätsklinikum Carl Gustav Carus an der TU DresdenDresdenGermany
| | - Susanne Erk
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Thomas Espeseth
- Department of PsychologyUniversity of OsloOsloNorway
- Bjørknes CollegeOsloNorway
| | - Helena Fatouros‐Bergman
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
- Stockholm Health Care ServicesStockholm RegionStockholmSweden
| | - Simon E. Fisher
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenNetherlands
| | - Jean‐Paul Fouche
- Department of Psychiatry and Mental HealthUniversity of Cape TownRondeboschSouth Africa
| | - Barbara Franke
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Human GeneticsRadboud University Medical CenterNijmegenNetherlands
- Department of PsychiatryRadboud University Medical CenterNijmegenNetherlands
| | - Thomas Frodl
- Department of Psychiatry and PsychotherapyOtto von Guericke University MagdeburgMagdeburgGermany
| | - Paola Fuentes‐Claramonte
- FIDMAG Germanes HospitalàriesMadridSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - David C. Glahn
- Department of Psychiatry, Tommy Fuss Center for Neuropsychiatric Disease Research Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Ian H. Gotlib
- Department of PsychologyStanford UniversityStanfordCaliforniaUSA
| | - Hans‐Jörgen Grabe
- Department of Psychiatry and PsychotherapyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Oliver Grimm
- Department for Psychiatry, Psychosomatics and Psychotherapy, Universitätsklinikum FrankfurtGoethe UniversitatFrankfurtGermany
| | - Nynke A. Groenewold
- Department of Psychiatry and Mental HealthUniversity of Cape TownRondeboschSouth Africa
- Neuroscience InstituteUniversity of Cape TownRondeboschSouth Africa
| | | | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryHeidelberg UniversityHeidelbergGermany
| | - Patricia Gruner
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
- Learning Based Recovery CenterVA Connecticut Health SystemNew HavenConnecticutUSA
| | - Rachel E. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Lifespan Brain Institute, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Children's Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ruben C. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Lifespan Brain Institute, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Children's Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Tim Hahn
- Department of Psychiatry and PsychotherapyUniversity of MünsterMunsterGermany
| | - Ben J. Harrison
- Melbourne Neuropsychiatry CenterUniversity of MelbourneMelbourneAustralia
| | - Catharine A. Hartman
- Interdisciplinary Center Psychopathology and Emotion regulationUniversity Medical Center Groningen, University of GroningenGroningenNetherlands
| | - Sean N. Hatton
- Brain and Mind CentreUniversity of SydneySydneyAustralia
| | - Andreas Heinz
- Faculty of MedicineUniversitätsklinikum Carl Gustav Carus an der TU DresdenDresdenGermany
| | - Dirk J. Heslenfeld
- Departments of Experimental and Clinical PsychologyVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Derrek P. Hibar
- Personalized HealthcareGenentech, IncSouth San FranciscoCaliforniaUSA
| | - Ian B. Hickie
- Brain and Mind CentreUniversity of SydneySydneyAustralia
| | - Beng‐Choon Ho
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Pieter J. Hoekstra
- Department of PsychiatryUniversity Medical Center Groningen, University of GroningenGroningenNetherlands
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityMannheimGermany
| | - Avram J. Holmes
- Department of PsychologyYale UniversityNew HavenConnecticutUSA
| | - Martine Hoogman
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Psychiatry and Mental HealthUniversity of Cape TownRondeboschSouth Africa
| | - Norbert Hosten
- Norbert Institute of Diagnostic Radiology and NeuroradiologyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
| | - Fleur M. Howells
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenNetherlands
- Department for Psychiatry, Psychosomatics and Psychotherapy, Universitätsklinikum FrankfurtGoethe UniversitatFrankfurtGermany
| | | | - Chaim Huyser
- Bascule, Academic Centre for Children and Adolescent PsychiatryDuivendrechtNetherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Terry L. Jernigan
- Center for Human Development, Departments of Cognitive Science, Psychiatry, and RadiologyUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesSydneyAustralia
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
- Stockholm Health Care ServicesStockholm RegionStockholmSweden
| | - John A. Joska
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenNetherlands
| | - Rene Kahn
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Andrew Kalnin
- Department of RadiologyOhio State University College of MedicineColumbusOhioUSA
| | - Ryota Kanai
- Department of NeuroinformaticsAraya, IncTokyoJapan
| | - Marieke Klein
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Psychiatry and Mental HealthUniversity of Cape TownRondeboschSouth Africa
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | | | - Laura Koenders
- Department of PsychiatryUniversity of MelbourneMelbourneAustralia
| | - Sanne Koops
- Rudolf Magnus Institute of NeuroscienceUniversity Medical Center UtrechtUtrechtNetherlands
| | - Bernd Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryHeidelberg UniversityHeidelbergGermany
| | - Jonna Kuntsi
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Jim Lagopoulos
- Sunshine Coast Mind and Neuroscience, Thompson InstituteUniversity of the Sunshine CoastSunshine CoastAustralia
| | - Luisa Lázaro
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of Child and Adolescent Psychiatry and PsychologyHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Irina Lebedeva
- Mental Health Research CenterRussian Academy of Medical SciencesMoskvaRussia
| | - Won Hee Lee
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Klaus‐Peter Lesch
- Department of Psychiatry, Psychosomatics and PsychotherapyJulius‐Maximilians Universität WürzburgWurzburgGermany
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of PsychiatryStellenbosch UniversityStellenboschSouth Africa
| | | | - Sophie Maingault
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxTalenceFrance
| | - Nicholas G. Martin
- Queensland Institute of Medical ResearchBerghofer Medical Research InstituteBrisbaneAustralia
| | - Ignacio Martínez‐Zalacaín
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - David Mataix‐Cols
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
- Stockholm Health Care ServicesStockholm RegionStockholmSweden
| | - Bernard Mazoyer
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxTalenceFrance
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandDublinIreland
| | - Brenna C. McDonald
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Katie L. McMahon
- School of Clinical Sciences, Institute of Health and Biomedical InnovationQueensland University of TechnologyBrisbaneAustralia
| | - Genevieve McPhilemy
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandDublinIreland
| | - Susanne Meinert
- Department of Psychiatry and PsychotherapyUniversity of MünsterMunsterGermany
| | - José M. Menchón
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - Sarah E. Medland
- Queensland Institute of Medical ResearchBerghofer Medical Research InstituteBrisbaneAustralia
| | - Andreas Meyer‐Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Jilly Naaijen
- Donders Centre for Cognitive NeuroimagingRadboud UniversityNijmegenNetherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
| | - Pablo Najt
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandDublinIreland
| | - Tomohiro Nakao
- Department of Clinical MedicineKyushu UniversityKyushuJapan
| | | | - Lars Nyberg
- Department of Integrative Medical BiologyUmeå UniversityUmeåSweden
- Department of Radiation Sciences, Umeå Center for Functional Brain ImagingUmeå UniversityUmeåSweden
| | - Jaap Oosterlaan
- Department of Clinical NeuropsychologyAmsterdam University Medical Centre, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Víctor Ortiz‐García de la Foz
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of Psychiatry, University Hospital “Marques de Valdecilla”Instituto de Investigación Valdecilla (IDIVAL)SantanderSpain
- Instituto de Salud Carlos IIIMadridSpain
| | - Yannis Paloyelis
- Department of Neuroimaging, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Paul Pauli
- Department of Psychology, Biological Psychology, Clinical Psychology and PsychotherapyUniversity of WürzburgWurzburgGermany
- Centre of Mental HealthUniversity of WürzburgWurzburgGermany
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari Aldo MoroBariItaly
| | - Edith Pomarol‐Clotet
- FIDMAG Germanes HospitalàriesMadridSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Maria J. Portella
- FIDMAG Germanes HospitalàriesMadridSpain
- Department of Psychiatry, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant PauUniversitat Autònoma de BarcelonaBarcelonaSpain
| | - Steven G. Potkin
- Department of PsychiatryUniversity of California at IrvineIrvineCaliforniaUSA
| | - Joaquim Radua
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
- August Pi i Sunyer Biomedical Research Institut (IDIBAPS)BarcelonaSpain
- Department of Psychosis Studies, Institute of PsychiatryPsychology & Neuroscience, King's College LondonLondonUK
| | - Andreas Reif
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Daniel A. Rinker
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Joshua L. Roffman
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Pedro G. P. Rosa
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Matthew D. Sacchet
- Center for Depression, Anxiety, and Stress ResearchMcLean Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesSydneyAustralia
| | | | - Pascual Sánchez‐Juan
- Department of Psychiatry, University Hospital “Marques de Valdecilla”Instituto de Investigación Valdecilla (IDIVAL)SantanderSpain
- Centro de Investigacion Biomedica en Red en Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | | | | | - Andrew J. Saykin
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Mauricio H. Serpa
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental HealthParkvilleAustralia
- Centre for Youth Mental HealthThe University of MelbourneMelbourneAustralia
| | - Knut Schnell
- Department of Psychiatry and PsychotherapyUniversity Medical Center GöttingenGöttingenGermany
| | - Gunter Schumann
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
- Centre for Population Neuroscience and Precision Medicine, Institute of PsychiatryPsychology & Neuroscience, King's College LondonLondonUK
| | - Kang Sim
- Institute of Mental HealthSingaporeSingapore
| | - Jordan W. Smoller
- Center for Genomic MedicineMassachusetts General HospitalBostonMassachusettsUSA
| | - Iris Sommer
- Department of Biomedical Sciences of Cells and Systems, Rijksuniversiteit GroningenUniversity Medical Center GroningenGöttingenNetherlands
| | - Carles Soriano‐Mas
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - Dan J. Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of PsychiatryStellenbosch UniversityStellenboschSouth Africa
| | | | | | - Christian K. Tamnes
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- PROMENTA Research Center, Department of PsychologyUniversity of OsloOsloNorway
| | - Henk S. Temmingh
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenNetherlands
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Diana Tordesillas‐Gutiérrez
- FIDMAG Germanes HospitalàriesMadridSpain
- Neuroimaging Unit, Technological FacilitiesValdecilla Biomedical Research Institute IDIVALSantanderSpain
| | - Julian N. Trollor
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesSydneyAustralia
| | - Jessica A. Turner
- College of Arts and SciencesGeorgia State UniversityAtlantaGeorgiaUSA
| | - Anne Uhlmann
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenNetherlands
| | - Odile A. van den Heuvel
- Department of Psychiatry, Amsterdam University Medical CentreLocation VUmcAmsterdamNetherlands
| | - Dennis van den Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical MedicineUniversity of OsloOsloNorway
- Division of Mental Health and Addiction, Institute of Clinical MedicineUniversity of OsloOsloNorway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life SciencesMaastricht UniversityMaastrichtNetherlands
| | - Nic J. A. van der Wee
- Department of PsychiatryLeiden University Medical CenterLeidenNetherlands
- Leiden Institute for Brain and CognitionLeidenNetherlands
| | - Neeltje E. M. van Haren
- Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center, Sophia Children's HospitalRotterdamThe Netherlands
| | - Dennis van't Ent
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Theo G. M. van Erp
- Department of PsychiatryUniversity of California at IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
- Institute of Community MedicineUniversity Medicine, Greifswald, University of GreifswaldGreifswaldGermany
| | - Ilya M. Veer
- Faculty of MedicineUniversitätsklinikum Carl Gustav Carus an der TU DresdenDresdenGermany
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam University Medical CentreLocation VUmcAmsterdamNetherlands
| | - Aristotle Voineskos
- Faculty of Health, Institute of Health and Biomedical InnovationQueensland University of TechnologyBrisbaneAustralia
- Kimel Family Translational Imaging Genetics LaboratoryCampbell Family Mental Health Research Institute, CAMHTorontoCanada
| | - Henry Völzke
- Institute of Community MedicineUniversity Medicine, Greifswald, University of GreifswaldGreifswaldGermany
- German Centre for Cardiovascular Research (DZHK), partner site GreifswaldGreifswaldGermany
- German Center for Diabetes Research (DZD), partner site GreifswaldGreifswaldGermany
| | - Henrik Walter
- Faculty of MedicineUniversitätsklinikum Carl Gustav Carus an der TU DresdenDresdenGermany
| | | | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Yang Wang
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Thomas H. Wassink
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Bernd Weber
- Institute for Experimental Epileptology and Cognition ResearchUniversity of BonnBonnGermany
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesSydneyAustralia
| | - John D. West
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Lars T. Westlye
- Biological Psychiatry Lab, Fondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (FG)Italy
| | | | - Lara M. Wierenga
- Developmental and Educational Psychology UnitInstitute of Psychology, Leiden UniversityLeidenNetherlands
| | - Steven C. R. Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Katharina Wittfeld
- Department of PsychologyStanford UniversityStanfordCaliforniaUSA
- Department of Psychiatry and PsychotherapyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
| | - Daniel H. Wolf
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Amanda Worker
- Department of Neuroimaging, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | | | - Kun Yang
- National High Magnetic Field LaboratoryFlorida State UniversityTallahasseeFloridaUSA
| | - Yulyia Yoncheva
- Department of Child and Adolescent PsychiatryChild Study Center, NYU Langone HealthNew YorkNew YorkUSA
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
- Instituto de Ensino e Pesquisa, Hospital Sírio‐LibanêsSão PauloBrazil
| | - Georg C. Ziegler
- Division of Molecular Psychiatry, Center of Mental HealthUniversity of WürzburgWurzburgGermany
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverCanada
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22
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Xiao J, Hornburg KJ, Cofer G, Cook JJ, Pratson F, Qi Y, Johnson GA. A time-course study of actively stained mouse brains: Diffusion tensor imaging parameters and connectomic stability over 1 year. NMR IN BIOMEDICINE 2022; 35:e4611. [PMID: 34558744 PMCID: PMC10461792 DOI: 10.1002/nbm.4611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 07/21/2021] [Accepted: 08/10/2021] [Indexed: 06/13/2023]
Abstract
While the application of diffusion tensor imaging (DTI), tractography, and connectomics to fixed tissue is a common practice today, there have been limited studies examining the effects of fixation on brain microstructure over extended periods. This mouse model time-course study reports the changes of regional brain volumes and diffusion scalar parameters, such as fractional anisotropy, across 12 representative brain regions as measures of brain structural stability. The scalar DTI parameters and regional volumes were highly variable over the first 2 weeks after fixation. The same parameters were consistent over a 2-8-week window after fixation, which means confounds from tissue stability over that scanning window were minimal. Quantitative connectomes were analyzed over the same time with extension out to 1 year. While there was some change in the scalar metrics at 1 year after fixation, these changes were sufficiently small, particularly in white matter, to support reproducible connectomes over a period ranging from 2-weeks to 1-year post-fixation. These findings delineate a scanning period, during which brain volumes, diffusion scalar metrics, and connectomes are remarkably consistent.
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Affiliation(s)
- Jaclyn Xiao
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Kathryn J. Hornburg
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Gary Cofer
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - James J. Cook
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Forrest Pratson
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Yi Qi
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - G. Allan Johnson
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
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23
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Frangou S, Modabbernia A, Williams SCR, Papachristou E, Doucet GE, Agartz I, Aghajani M, Akudjedu TN, Albajes‐Eizagirre A, Alnæs D, Alpert KI, Andersson M, Andreasen NC, Andreassen OA, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur‐Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Buckner RL, Calhoun V, Canales‐Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Cervenka S, Chaim‐Avancini TM, Ching CRK, Chubar V, Clark VP, Conrod P, Conzelmann A, Crespo‐Facorro B, Crivello F, Crone EA, Dale AM, Dannlowski U, Davey C, de Geus EJC, de Haan L, de Zubicaray GI, den Braber A, Dickie EW, Di Giorgio A, Doan NT, Dørum ES, Ehrlich S, Erk S, Espeseth T, Fatouros‐Bergman H, Fisher SE, Fouche J, Franke B, Frodl T, Fuentes‐Claramonte P, Glahn DC, Gotlib IH, Grabe H, Grimm O, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Hahn T, Harrison BJ, Hartman CA, Hatton SN, Heinz A, Heslenfeld DJ, Hibar DP, Hickie IB, Ho B, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James A, Jernigan TL, Jiang J, Jönsson EG, Joska JA, Kahn R, Kalnin A, Kanai R, Klein M, Klyushnik TP, Koenders L, Koops S, Krämer B, Kuntsi J, Lagopoulos J, Lázaro L, Lebedeva I, Lee WH, Lesch K, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez‐Zalacaín I, Mataix‐Cols D, Mazoyer B, McDonald C, McDonald BC, McIntosh AM, McMahon KL, McPhilemy G, Meinert S, Menchón JM, Medland SE, Meyer‐Lindenberg A, Naaijen J, Najt P, Nakao T, Nordvik JE, Nyberg L, Oosterlaan J, de la Foz VO, Paloyelis Y, Pauli P, Pergola G, Pomarol‐Clotet E, Portella MJ, Potkin SG, Radua J, Reif A, Rinker DA, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sánchez‐Juan P, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Schmaal L, Schnell K, Schumann G, Sim K, Smoller JW, Sommer I, Soriano‐Mas C, Stein DJ, Strike LT, Swagerman SC, Tamnes CK, Temmingh HS, Thomopoulos SI, Tomyshev AS, Tordesillas‐Gutiérrez D, Trollor JN, Turner JA, Uhlmann A, van den Heuvel OA, van den Meer D, van der Wee NJA, van Haren NEM, van 't Ent D, van Erp TGM, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Walton E, Wang L, Wang Y, Wassink TH, Weber B, Wen W, West JD, Westlye LT, Whalley H, Wierenga LM, Wittfeld K, Wolf DH, Worker A, Wright MJ, Yang K, Yoncheva Y, Zanetti MV, Ziegler GC, Thompson PM, Dima D. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years. Hum Brain Mapp 2022; 43:431-451. [PMID: 33595143 PMCID: PMC8675431 DOI: 10.1002/hbm.25364] [Citation(s) in RCA: 103] [Impact Index Per Article: 51.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 01/02/2021] [Accepted: 01/21/2021] [Indexed: 12/25/2022] Open
Abstract
Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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Affiliation(s)
- Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew York CityNew YorkUSA
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverCanada
| | | | - Steven C. R. Williams
- Department of NeuroimagingInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Efstathios Papachristou
- Psychology and Human DevelopmentInstitute of Education, University College LondonLondonUnited Kingdom
| | - Gaelle E. Doucet
- Institute for Human NeuroscienceBoys Town National Research HospitalOmahaNebraskaUSA
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
| | - Moji Aghajani
- Department of PsychiatryAmsterdam University Medical Centre, Vrije UniversiteitAmsterdamNetherlands
- Section Forensic Family & Youth CareInstitute of Education & Child StudiesLeiden UniversityNetherlands
| | - Theophilus N. Akudjedu
- Institute of Medical Imaging and Visualisation, Department of Medical Science and Public Health, Faculty of Health and Social SciencesBournemouth UniversityPooleUnited Kingdom
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Anton Albajes‐Eizagirre
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Division of Mental Health and AddictionInstitute of Clinical Medicine, University of OsloOsloNorway
| | | | - Micael Andersson
- Department of Integrative Medical BiologyUmeå UniversityUmeåSweden
| | - Nancy C. Andreasen
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - Philip Asherson
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Nuria Bargallo
- Imaging Diagnostic CentreHospital Clinic, Barcelona University ClinicBarcelonaSpain
- August Pi i Sunyer Biomedical Research Institut (IDIBAPS)BarcelonaSpain
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Ramona Baur‐Streubel
- Department of Psychology, Biological Psychology, Clinical Psychology and PsychotherapyUniversity of WürzburgWürzburgGermany
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari Aldo MoroBariItaly
| | - Aurora Bonvino
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Dorret I. Boomsma
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Stefan Borgwardt
- Department of Psychiatry & PsychotherapyUniversity of LübeckLübeckGermany
| | - Josiane Bourque
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Alan Breier
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - Rachel M. Brouwer
- Rudolf Magnus Institute of NeuroscienceUniversity Medical Center UtrechtUtrechtNetherlands
| | - Jan K. Buitelaar
- Donders Center of Medical NeurosciencesRadboud UniversityNijmegenNetherlands
- Donders Centre for Cognitive NeuroimagingRadboud UniversityNijmegenNetherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
| | - Geraldo F. Busatto
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Randy L. Buckner
- Department of Psychology, Center for Brain ScienceHarvard UniversityCambridgeMassachusettsUSA
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Vincent Calhoun
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of TechnologyEmory University, USA Neurology, Radiology, Psychiatry and Biomedical Engineering, Emory UniversityAtlantaGeorgiaUSA
| | - Erick J. Canales‐Rodríguez
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Dara M. Cannon
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUnited Kingdom
| | | | - Simon Cervenka
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- Stockholm Health Care ServicesStockholmSweden
| | - Tiffany M. Chaim‐Avancini
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Victoria Chubar
- Mind‐Body Research Group, Department of NeuroscienceKU LeuvenLeuvenBelgium
| | - Vincent P. Clark
- Department of PsychologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
- Mind Research NetworkAlbuquerqueNew MexicoUSA
| | - Patricia Conrod
- Department of PsychiatryUniversité de MontréalMontrealCanada
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and PsychotherapyUniversity of TübingenTübingenGermany
| | - Benedicto Crespo‐Facorro
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- HU Virgen del Rocio, IBiSUniversity of SevillaSevillaSpain
| | - Fabrice Crivello
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxBordeauxFrance
| | - Eveline A. Crone
- Erasmus School of Social and Behavioural SciencesErasmus University RotterdamRotterdamNetherlands
- Faculteit der Sociale Wetenschappen, Instituut PsychologieUniversiteit LeidenLeidenNetherlands
| | - Anders M. Dale
- Center for Multimodal Imaging and Genetics, Department of NeuroscienceUniversity of California‐San DiegoSan DiegoCaliforniaUSA
- Department of RadiologyUniversity of California‐San DiegoSan DiegoCaliforniaUSA
| | - Udo Dannlowski
- Department of Psychiatry and PsychotherapyUniversity of MünsterGermany
| | | | - Eco J. C. de Geus
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Lieuwe de Haan
- Academisch Medisch CentrumUniversiteit van AmsterdamAmsterdamNetherlands
| | - Greig I. de Zubicaray
- Faculty of Health, Institute of Health and Biomedical InnovationQueensland University of TechnologyQueenslandAustralia
| | - Anouk den Braber
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Erin W. Dickie
- Kimel Family Translational Imaging Genetics Laboratory, Campbell Family Mental Health Research InstituteCAMHCampbellCanada
- Department of PsychiatryUniversity of TorontoTorontoCanada
| | - Annabella Di Giorgio
- Biological Psychiatry LabFondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (FG)Italy
| | - Nhat Trung Doan
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - Erlend S. Dørum
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
- Sunnaas Rehabilitation Hospital HTNesoddenNorway
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental NeurosciencesTechnische Universität DresdenDresdenGermany
- Faculty of MedicineUniversitätsklinikum Carl Gustav Carus an der TU DresdenDresdenGermany
| | - Susanne Erk
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Thomas Espeseth
- Biological Psychiatry LabFondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (FG)Italy
- Bjørknes CollegeOsloNorway
| | - Helena Fatouros‐Bergman
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- Stockholm Health Care ServicesStockholmSweden
| | - Simon E. Fisher
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenNetherlands
| | - Jean‐Paul Fouche
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Barbara Franke
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Human GeneticsRadboud University Medical CenterNijmegenNetherlands
- Department of PsychiatryRadboud University Medical CenterNijmegenNetherlands
| | - Thomas Frodl
- Department of Psychiatry and PsychotherapyOtto von Guericke University MagdeburgMagdeburgGermany
| | - Paola Fuentes‐Claramonte
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - David C. Glahn
- Department of PsychiatryTommy Fuss Center for Neuropsychiatric Disease Research Boston Children's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Ian H. Gotlib
- Department of PsychologyStanford UniversityStanfordCaliforniaUSA
| | - Hans‐Jörgen Grabe
- Department of Psychiatry and PsychotherapyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Oliver Grimm
- Department for Psychiatry, Psychosomatics and PsychotherapyUniversitätsklinikum Frankfurt, Goethe UniversitatFrankfurtGermany
| | - Nynke A. Groenewold
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
- Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | | | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryHeidelberg UniversityHeidelbergGermany
| | - Patricia Gruner
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
- Learning Based Recovery CenterVA Connecticut Health SystemWest HavenConnecticutUSA
| | - Rachel E. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Lifespan Brain Institute, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Children's Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ruben C. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Lifespan Brain Institute, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Children's Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Tim Hahn
- Department of Psychiatry and PsychotherapyUniversity of MünsterGermany
| | - Ben J. Harrison
- Melbourne Neuropsychiatry CenterUniversity of MelbourneMelbourneAustralia
| | - Catharine A. Hartman
- Interdisciplinary Center Psychopathology and Emotion regulationUniversity Medical Center Groningen, University of GroningenGroningenNetherlands
| | - Sean N. Hatton
- Brain and Mind CentreUniversity of SydneySydneyAustralia
| | - Andreas Heinz
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Dirk J. Heslenfeld
- Departments of Experimental and Clinical PsychologyVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Derrek P. Hibar
- Personalized Healthcare, Genentech, Inc.South San FranciscoCaliforniaUSA
| | - Ian B. Hickie
- Brain and Mind CentreUniversity of SydneySydneyAustralia
| | - Beng‐Choon Ho
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Pieter J. Hoekstra
- Department of PsychiatryUniversity Medical Center Groningen, University of GroningenGroningenNetherlands
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Avram J. Holmes
- Department of PsychologyYale UniversityNew HavenConnecticutUSA
| | - Martine Hoogman
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Human GeneticsRadboud University Medical CenterNijmegenNetherlands
| | - Norbert Hosten
- Norbert Institute of Diagnostic Radiology and NeuroradiologyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
| | - Fleur M. Howells
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
- Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | | | - Chaim Huyser
- De Bascule, Academic Centre for Children and Adolescent PsychiatryAmsterdamNetherlands
| | - Neda Jahanshad
- Mind‐Body Research Group, Department of NeuroscienceKU LeuvenLeuvenBelgium
| | - Anthony James
- Department of PsychiatryOxford UniversityOxfordUnited Kingdom
| | - Terry L. Jernigan
- Center for Human Development, Departments of Cognitive Science, Psychiatry, and RadiologyUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - John A. Joska
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Rene Kahn
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew York CityNew YorkUSA
| | - Andrew Kalnin
- Department of RadiologyOhio State University College of MedicineColumbusOhioUSA
| | - Ryota Kanai
- Department of NeuroinformaticsAraya, Inc.TokyoJapan
| | - Marieke Klein
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Human GeneticsRadboud University Medical CenterNijmegenNetherlands
- Department of PsychiatryUniversity of California San DiegoSan DiegoCaliforniaUSA
| | | | - Laura Koenders
- Academisch Medisch CentrumUniversiteit van AmsterdamAmsterdamNetherlands
| | - Sanne Koops
- Rudolf Magnus Institute of NeuroscienceUniversity Medical Center UtrechtUtrechtNetherlands
| | - Bernd Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryHeidelberg UniversityHeidelbergGermany
| | - Jonna Kuntsi
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Jim Lagopoulos
- Sunshine Coast Mind and NeuroscienceThompson Institute, University of the Sunshine CoastQueenslandAustralia
| | - Luisa Lázaro
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of Child and Adolescent Psychiatry and PsychologyHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Irina Lebedeva
- Mental Health Research CenterRussian Academy of Medical SciencesMoscowRussia
| | - Won Hee Lee
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew York CityNew YorkUSA
| | - Klaus‐Peter Lesch
- Department of Psychiatry, Psychosomatics and PsychotherapyJulius‐Maximilians Universität WürzburgWürzburgGermany
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of PsychiatryStellenbosch UniversityStellenboschSouth Africa
| | | | - Sophie Maingault
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxBordeauxFrance
| | - Nicholas G. Martin
- Queensland Institute of Medical ResearchBerghofer Medical Research InstituteQueenslandAustralia
| | - Ignacio Martínez‐Zalacaín
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - David Mataix‐Cols
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- Stockholm Health Care ServicesStockholmSweden
| | - Bernard Mazoyer
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxBordeauxFrance
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Brenna C. McDonald
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Katie L. McMahon
- School of Clinical Sciences, Institute of Health and Biomedical InnovationQueensland University of TechnologyQueenslandAustralia
| | - Genevieve McPhilemy
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Susanne Meinert
- Department of Psychiatry and PsychotherapyUniversity of MünsterGermany
| | - José M. Menchón
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - Sarah E. Medland
- Queensland Institute of Medical ResearchBerghofer Medical Research InstituteQueenslandAustralia
| | - Andreas Meyer‐Lindenberg
- Department of Psychiatry and PsychotherapyCentral Institute of Mental Health, Heidelberg UniversityHeidelbergGermany
| | - Jilly Naaijen
- Donders Centre for Cognitive NeuroimagingRadboud UniversityNijmegenNetherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
| | - Pablo Najt
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Tomohiro Nakao
- Department of Clinical MedicineKyushu UniversityFukuokaJapan
| | | | - Lars Nyberg
- Department of Integrative Medical BiologyUmeå UniversityUmeåSweden
- Department of Radiation SciencesUmeå Center for Functional Brain Imaging, Umeå UniversityUmeåSweden
| | - Jaap Oosterlaan
- Department of Clinical NeuropsychologyAmsterdam University Medical Centre, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Víctor Ortiz‐García de la Foz
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryUniversity Hospital “Marques de Valdecilla”, Instituto de Investigación Valdecilla (IDIVAL)SantanderSpain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM)Instituto de Salud Carlos IIIMadridSpain
| | - Yannis Paloyelis
- Department of NeuroimagingInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Paul Pauli
- Department of Psychology, Biological Psychology, Clinical Psychology and PsychotherapyUniversity of WürzburgWürzburgGermany
- Centre of Mental HealthUniversity of WürzburgWürzburgGermany
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari Aldo MoroBariItaly
| | - Edith Pomarol‐Clotet
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Maria J. Portella
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Department of PsychiatryHospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Steven G. Potkin
- Department of PsychiatryUniversity of California at IrvineIrvineCaliforniaUSA
| | - Joaquim Radua
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- August Pi i Sunyer Biomedical Research Institut (IDIBAPS)BarcelonaSpain
- Department of Psychosis StudiesInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUnited Kingdom
| | - Andreas Reif
- Department for Psychiatry, Psychosomatics and PsychotherapyUniversitätsklinikum Frankfurt, Goethe UniversitatFrankfurtGermany
| | - Daniel A. Rinker
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - Joshua L. Roffman
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Pedro G. P. Rosa
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Matthew D. Sacchet
- Center for Depression, Anxiety, and Stress ResearchMcLean Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | | | - Pascual Sánchez‐Juan
- Department of PsychiatryUniversity Hospital “Marques de Valdecilla”, Instituto de Investigación Valdecilla (IDIVAL)SantanderSpain
- Centro de Investigacion Biomedica en Red en Enfermedades Neurodegenerativas (CIBERNED)ValderrebolloSpain
| | | | | | - Andrew J. Saykin
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Mauricio H. Serpa
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Lianne Schmaal
- OrygenThe National Centre of Excellence in Youth Mental HealthMelbourneAustralia
- Centre for Youth Mental HealthThe University of MelbourneMelbourneAustralia
| | - Knut Schnell
- Department of Psychiatry and PsychotherapyUniversity Medical Center GöttingenGöttingenGermany
| | - Gunter Schumann
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
- Centre for Population Neuroscience and Precision MedicineInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUnited Kingdom
| | - Kang Sim
- Department of General PsychiatryInstitute of Mental HealthSingaporeSingapore
| | - Jordan W. Smoller
- Center for Genomic MedicineMassachusetts General HospitalBostonMassachusettsUSA
| | - Iris Sommer
- Department of Biomedical Sciences of Cells and Systems, Rijksuniversiteit GroningenUniversity Medical Center GroningenGroningenNetherlands
| | - Carles Soriano‐Mas
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - Dan J. Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of PsychiatryStellenbosch UniversityStellenboschSouth Africa
| | - Lachlan T. Strike
- Queensland Brain InstituteUniversity of QueenslandQueenslandAustralia
| | | | - Christian K. Tamnes
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- PROMENTA Research Center, Department of PsychologyUniversity of OsloOsloNorway
| | - Henk S. Temmingh
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | | | - Diana Tordesillas‐Gutiérrez
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Neuroimaging Unit, Technological FacilitiesValdecilla Biomedical Research Institute IDIVALCantabriaSpain
| | - Julian N. Trollor
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - Jessica A. Turner
- College of Arts and SciencesGeorgia State UniversityAtlantaGeorgiaUSA
| | - Anne Uhlmann
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Odile A. van den Heuvel
- Department of PsychiatryAmsterdam University Medical Centre, Vrije UniversiteitAmsterdamNetherlands
| | - Dennis van den Meer
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Division of Mental Health and AddictionInstitute of Clinical Medicine, University of OsloOsloNorway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life SciencesMaastricht UniversityMaastrichtNetherlands
| | - Nic J. A. van der Wee
- Department of PsychiatryLeiden University Medical CenterLeidenNetherlands
- Leiden Institute for Brain and CognitionLeiden University Medical CenterLeidenNetherlands
| | - Neeltje E. M. van Haren
- Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center, Sophia Children's HospitalRotterdamThe Netherlands
| | - Dennis van 't Ent
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Theo G. M. van Erp
- Department of PsychiatryUniversity of California at IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
- Institute of Community MedicineUniversity Medicine, Greifswald, University of GreifswaldGreifswaldGermany
| | - Ilya M. Veer
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Dick J. Veltman
- Department of PsychiatryAmsterdam University Medical Centre, Vrije UniversiteitAmsterdamNetherlands
| | - Aristotle Voineskos
- Kimel Family Translational Imaging Genetics Laboratory, Campbell Family Mental Health Research InstituteCAMHCampbellCanada
- Department of PsychiatryUniversity of TorontoTorontoCanada
| | - Henry Völzke
- Institute of Community MedicineUniversity Medicine, Greifswald, University of GreifswaldGreifswaldGermany
- German Centre for Cardiovascular Research (DZHK), partner site GreifswaldGreifswaldGermany
- German Center for Diabetes Research (DZD), partner site GreifswaldGreifswaldGermany
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Esther Walton
- Department of PsychologyUniversity of BathBathUnited Kingdom
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of MedicineNorthwestern UniversityEvanstonIllinoisUSA
| | - Yang Wang
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Thomas H. Wassink
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Bernd Weber
- Institute for Experimental Epileptology and Cognition ResearchUniversity of BonnBonnGermany
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - John D. West
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Heather Whalley
- Division of PsychiatryUniversity of EdinburghEdinburghUnited Kingdom
| | - Lara M. Wierenga
- Developmental and Educational Psychology Unit, Institute of PsychologyLeiden UniversityLeidenNetherlands
| | - Katharina Wittfeld
- Department of Psychiatry and PsychotherapyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Daniel H. Wolf
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Amanda Worker
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverCanada
| | | | - Kun Yang
- National High Magnetic Field LaboratoryFlorida State UniversityTallahasseeFloridaUSA
| | - Yulyia Yoncheva
- Department of Child and Adolescent Psychiatry, Child Study CenterNYU Langone HealthNew York CityNew YorkUSA
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
- Instituto de Ensino e PesquisaHospital Sírio‐LibanêsSão PauloBrazil
| | - Georg C. Ziegler
- Division of Molecular Psychiatry, Center of Mental HealthUniversity of WürzburgWürzburgGermany
| | | | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Danai Dima
- Department of NeuroimagingInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
- Department of Psychology, School of Arts and Social SciencesCity University of LondonLondonUnited Kingdom
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24
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Hosten N, Bülow R, Völzke H, Domin M, Schmidt CO, Teumer A, Ittermann T, Nauck M, Felix S, Dörr M, Markus MRP, Völker U, Daboul A, Schwahn C, Holtfreter B, Mundt T, Krey KF, Kindler S, Mksoud M, Samietz S, Biffar R, Hoffmann W, Kocher T, Chenot JF, Stahl A, Tost F, Friedrich N, Zylla S, Hannemann A, Lotze M, Kühn JP, Hegenscheid K, Rosenberg C, Wassilew G, Frenzel S, Wittfeld K, Grabe HJ, Kromrey ML. SHIP-MR and Radiology: 12 Years of Whole-Body Magnetic Resonance Imaging in a Single Center. Healthcare (Basel) 2021; 10:33. [PMID: 35052197 PMCID: PMC8775435 DOI: 10.3390/healthcare10010033] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/17/2021] [Accepted: 12/20/2021] [Indexed: 12/16/2022] Open
Abstract
The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.
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Affiliation(s)
- Norbert Hosten
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
| | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Carsten Oliver Schmidt
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
| | - Matthias Nauck
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Stephan Felix
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Department of Internal Medicine B, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Marcus Dörr
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Department of Internal Medicine B, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Marcello Ricardo Paulista Markus
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Department of Internal Medicine B, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Uwe Völker
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Amro Daboul
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Christian Schwahn
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Birte Holtfreter
- Department of Restorative Dentistry, Periodontology, Endodontology, and Preventive and Pediatric Dentistry, University Medicine Greifswald, 17475 Greifswald, Germany; (B.H.); (T.K.)
| | - Torsten Mundt
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Karl-Friedrich Krey
- Department of Orthodontics, University Medicine Greifswald, 17475 Greifswald, Germany;
| | - Stefan Kindler
- Department of Oral and Maxillofacial Surgery/Plastic Surgery, University Medicine Greifswald, 17475 Greifswald, Germany; (S.K.); (M.M.)
| | - Maria Mksoud
- Department of Oral and Maxillofacial Surgery/Plastic Surgery, University Medicine Greifswald, 17475 Greifswald, Germany; (S.K.); (M.M.)
| | - Stefanie Samietz
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Reiner Biffar
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Wolfgang Hoffmann
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- German Centre for Neurodegenerative Diseases (DZNE), Partner Site Rostock/Greifswald, 17489 Greifswald, Germany
| | - Thomas Kocher
- Department of Restorative Dentistry, Periodontology, Endodontology, and Preventive and Pediatric Dentistry, University Medicine Greifswald, 17475 Greifswald, Germany; (B.H.); (T.K.)
| | - Jean-Francois Chenot
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
| | - Andreas Stahl
- Clinic of Ophthalmology, University Medicine Greifswald, 17475 Greifswald, Germany; (A.S.); (F.T.)
| | - Frank Tost
- Clinic of Ophthalmology, University Medicine Greifswald, 17475 Greifswald, Germany; (A.S.); (F.T.)
| | - Nele Friedrich
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Stephanie Zylla
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Anke Hannemann
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Martin Lotze
- Functional Imaging Unit, Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany;
| | - Jens-Peter Kühn
- Institute and Policlinic of Diagnostic and Interventional Radiology, Medical University, Carl-Gustav Carus, 01307 Dresden, Germany;
| | - Katrin Hegenscheid
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Christian Rosenberg
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Georgi Wassilew
- Clinic of Orthopedics, University Medicine Greifswald, 17475 Greifswald, Germany;
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; (S.F.); (K.W.); (H.J.G.)
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; (S.F.); (K.W.); (H.J.G.)
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Site Greifswald, 17489 Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; (S.F.); (K.W.); (H.J.G.)
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Site Greifswald, 17489 Greifswald, Germany
| | - Marie-Luise Kromrey
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
- Correspondence:
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25
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Axelrud LK, Simioni AR, Pine DS, Winkler AM, Pan PM, Sato JR, Zugman A, Parker N, Picon F, Jackowski A, Hoexter MQ, Barker G, Martinot JL, Martinot MLP, Satterthwaite T, Rohde LA, Milham M, Barker ED, Salum GA. Neuroimaging Association Scores: reliability and validity of aggregate measures of brain structural features linked to mental disorders in youth. Eur Child Adolesc Psychiatry 2021; 30:1895-1906. [PMID: 33030612 PMCID: PMC9077631 DOI: 10.1007/s00787-020-01653-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 09/21/2020] [Indexed: 10/23/2022]
Abstract
In genetics, aggregation of many loci with small effect sizes into a single score improved prediction. Nevertheless, studies applying easily replicable weighted scores to neuroimaging data are lacking. Our aim was to assess the reliability and validity of the Neuroimaging Association Score (NAS), which combines information from structural brain features previously linked to mental disorders. Participants were 726 youth (aged 6-14) from two cities in Brazil who underwent MRI and psychopathology assessment at baseline and 387 at 3-year follow-up. Results were replicated in two samples: IMAGEN (n = 1627) and the Healthy Brain Network (n = 843). NAS were derived by summing the product of each standardized brain feature by the effect size of the association of that brain feature with seven psychiatric disorders documented by previous meta-analyses. NAS were calculated for surface area, cortical thickness and subcortical volumes using T1-weighted scans. NAS reliability, temporal stability and psychopathology and cognition prediction were analyzed. NAS for surface area showed high internal consistency and 3-year stability and predicted general psychopathology and cognition with higher replicability than specific symptomatic domains for all samples. They also predicted general psychopathology with higher replicability than single structures alone, accounting for 1-3% of the variance, but without directionality. The NAS for cortical thickness and subcortical volumes showed lower internal consistency and less replicable associations with behavioural phenotypes. These findings indicate the NAS based on surface area might be replicable markers of general psychopathology, but these links are unlikely to be causal or clinically useful yet.
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Affiliation(s)
- Luiza Kvitko Axelrud
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil.
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil.
| | - André Rafael Simioni
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
| | - Daniel Samuel Pine
- National Institute of Mental Health Intramural Research Program, Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Anderson Marcelo Winkler
- National Institute of Mental Health Intramural Research Program, Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Pedro Mario Pan
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - João Ricardo Sato
- Centro de Matemática, Computação E Cognição, Universidade Federal Do ABC, Santo André, Brazil
| | - André Zugman
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Nadine Parker
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Felipe Picon
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
| | - Andrea Jackowski
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Marcelo Queiroz Hoexter
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Gareth Barker
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Jean-Luc Martinot
- Institut National de La Santé Et de La Recherche Médicale, INSERM Unit 1000 "Neuroimaging and Psychiatry", University Paris Saclay, University Paris Descartes, Paris, France
| | - Marie Laure Paillère Martinot
- Institut National de La Santé Et de La Recherche Médicale, INSERM Unit 1000 "Neuroimaging and Psychiatry", University Paris Saclay, University Paris Descartes, Paris, France
| | - Theodore Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Luis Augusto Rohde
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
| | | | - Edward Dylan Barker
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Giovanni Abrahão Salum
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
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26
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Federated Analysis of Neuroimaging Data: A Review of the Field. Neuroinformatics 2021; 20:377-390. [PMID: 34807353 PMCID: PMC9124226 DOI: 10.1007/s12021-021-09550-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2021] [Indexed: 10/19/2022]
Abstract
The field of neuroimaging has embraced sharing data to collaboratively advance our understanding of the brain. However, data sharing, especially across sites with large amounts of protected health information (PHI), can be cumbersome and time intensive. Recently, there has been a greater push towards collaborative frameworks that enable large-scale federated analysis of neuroimaging data without the data having to leave its original location. However, there still remains a need for a standardized federated approach that not only allows for data sharing adhering to the FAIR (Findability, Accessibility, Interoperability, Reusability) data principles, but also streamlines analyses and communication while maintaining subject privacy. In this paper, we review a non-exhaustive list of neuroimaging analytic tools and frameworks currently in use. We then provide an update on our federated neuroimaging analysis software system, the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC). In the end, we share insights on future research directions for federated analysis of neuroimaging data.
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27
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Imtiaz H, Mohammadi J, Silva R, Baker B, Plis SM, Sarwate AD, Calhoun VD. A Correlated Noise-assisted Decentralized Differentially Private Estimation Protocol, and its application to fMRI Source Separation. IEEE TRANSACTIONS ON SIGNAL PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2021; 69:6355-6370. [PMID: 35755147 PMCID: PMC9232162 DOI: 10.1109/tsp.2021.3126546] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Blind source separation algorithms such as independent component analysis (ICA) are widely used in the analysis of neuroimaging data. To leverage larger sample sizes, different data holders/sites may wish to collaboratively learn feature representations. However, such datasets are often privacy-sensitive, precluding centralized analyses that pool the data at one site. In this work, we propose a differentially private algorithm for performing ICA in a decentralized data setting. Due to the high dimension and small sample size, conventional approaches to decentralized differentially private algorithms suffer in terms of utility. When centralizing the data is not possible, we investigate the benefit of enabling limited collaboration in the form of generating jointly distributed random noise. We show that such (anti) correlated noise improves the privacy-utility trade-off, and can reach the same level of utility as the corresponding non-private algorithm for certain parameter choices. We validate this benefit using synthetic and real neuroimaging datasets. We conclude that it is possible to achieve meaningful utility while preserving privacy, even in complex signal processing systems.
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Affiliation(s)
- Hafiz Imtiaz
- Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | | | - Rogers Silva
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, 55 Park Place NE, Atlanta, GA 30303
| | - Bradley Baker
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, 55 Park Place NE, Atlanta, GA 30303
| | - Sergey M Plis
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, 55 Park Place NE, Atlanta, GA 30303
| | - Anand D Sarwate
- Department of Electrical and Computer Engineering, Rutgers University, 94 Brett Road, Piscataway, NJ 08854
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, 55 Park Place NE, Atlanta, GA 30303
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28
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Szejko N, Dunalska A, Lombroso A, McGuire JF, Piacentini J. Genomics of Obsessive-Compulsive Disorder-Toward Personalized Medicine in the Era of Big Data. Front Pediatr 2021; 9:685660. [PMID: 34746045 PMCID: PMC8564378 DOI: 10.3389/fped.2021.685660] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 09/20/2021] [Indexed: 01/11/2023] Open
Abstract
Pathogenesis of obsessive-compulsive disorder (OCD) mainly involves dysregulation of serotonergic neurotransmission, but a number of other factors are involved. Genetic underprints of OCD fall under the category of "common disease common variant hypothesis," that suggests that if a disease that is heritable is common in the population (a prevalence >1-5%), then the genetic contributors-specific variations in the genetic code-will also be common in the population. Therefore, the genetic contribution in OCD is believed to come from multiple genes simultaneously and it is considered a polygenic disorder. Genomics offers a number of advanced tools to determine causal relationship between the exposure and the outcome of interest. Particularly, methods such as polygenic risk score (PRS) or Mendelian Randomization (MR) enable investigation of new pathways involved in OCD pathogenesis. This premise is also facilitated by the existence of publicly available databases that include vast study samples. Examples include population-based studies such as UK Biobank, China Kadoorie Biobank, Qatar Biobank, All of US Program sponsored by National Institute of Health or Generations launched by Yale University, as well as disease-specific databases, that include patients with OCD and co-existing pathologies, with the following examples: Psychiatric Genomics Consortium (PGC), ENIGMA OCD, The International OCD Foundation Genetics Collaborative (IOCDF-GC) or OCD Collaborative Genetic Association Study. The aim of this review is to present a comprehensive overview of the available Big Data resources for the study of OCD pathogenesis in the context of genomics and demonstrate that OCD should be considered a disorder which requires the approaches offered by personalized medicine.
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Affiliation(s)
- Natalia Szejko
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
- Department of Neurology, Medical University of Warsaw, Warsaw, Poland
- Department of Bioethics, Medical University of Warsaw, Warsaw, Poland
| | - Anna Dunalska
- Department of Neurology, Medical University of Warsaw, Warsaw, Poland
| | - Adam Lombroso
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
| | - Joseph F. McGuire
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MS, United States
- Semel Institute of Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - John Piacentini
- Semel Institute of Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
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29
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Gordon RL, Ravignani A, Hyland Bruno J, Robinson CM, Scartozzi A, Embalabala R, Niarchou M, Cox NJ, Creanza N. Linking the genomic signatures of human beat synchronization and learned song in birds. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200329. [PMID: 34420388 DOI: 10.1098/rstb.2020.0329] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
The development of rhythmicity is foundational to communicative and social behaviours in humans and many other species, and mechanisms of synchrony could be conserved across species. The goal of the current paper is to explore evolutionary hypotheses linking vocal learning and beat synchronization through genomic approaches, testing the prediction that genetic underpinnings of birdsong also contribute to the aetiology of human interactions with musical beat structure. We combined state-of-the-art-genomic datasets that account for underlying polygenicity of these traits: birdsong genome-wide transcriptomics linked to singing in zebra finches, and a human genome-wide association study of beat synchronization. Results of competitive gene set analysis revealed that the genetic architecture of human beat synchronization is significantly enriched for birdsong genes expressed in songbird Area X (a key nucleus for vocal learning, and homologous to human basal ganglia). These findings complement ethological and neural evidence of the relationship between vocal learning and beat synchronization, supporting a framework of some degree of common genomic substrates underlying rhythm-related behaviours in two clades, humans and songbirds (the largest evolutionary radiation of vocal learners). Future cross-species approaches investigating the genetic underpinnings of beat synchronization in a broad evolutionary context are discussed. This article is part of the theme issue 'Synchrony and rhythm interaction: from the brain to behavioural ecology'.
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Affiliation(s)
- Reyna L Gordon
- Department of Otolaryngology - Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Andrea Ravignani
- Comparative Bioacoustics Group, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | | | - Cristina M Robinson
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Alyssa Scartozzi
- Department of Otolaryngology - Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Rebecca Embalabala
- Department of Otolaryngology - Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
| | - Maria Niarchou
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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- 23andMe, Inc., Sunnyvale, CA, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Nicole Creanza
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA.,Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
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30
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McPherson BC, Pestilli F. A single mode of population covariation associates brain networks structure and behavior and predicts individual subjects' age. Commun Biol 2021; 4:943. [PMID: 34354185 PMCID: PMC8342440 DOI: 10.1038/s42003-021-02451-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 06/15/2021] [Indexed: 02/07/2023] Open
Abstract
Multiple human behaviors improve early in life, peaking in young adulthood, and declining thereafter. Several properties of brain structure and function progress similarly across the lifespan. Cognitive and neuroscience research has approached aging primarily using associations between a few behaviors, brain functions, and structures. Because of this, the multivariate, global factors relating brain and behavior across the lifespan are not well understood. We investigated the global patterns of associations between 334 behavioral and clinical measures and 376 brain structural connections in 594 individuals across the lifespan. A single-axis associated changes in multiple behavioral domains and brain structural connections (r = 0.5808). Individual variability within the single association axis well predicted the age of the subject (r = 0.6275). Representational similarity analysis evidenced global patterns of interactions across multiple brain network systems and behavioral domains. Results show that global processes of human aging can be well captured by a multivariate data fusion approach.
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Affiliation(s)
- Brent C McPherson
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA
| | - Franco Pestilli
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA.
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA.
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31
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Smit DJA, Andreassen OA, Boomsma DI, Burwell SJ, Chorlian DB, de Geus EJC, Elvsåshagen T, Gordon RL, Harper J, Hegerl U, Hensch T, Iacono WG, Jawinski P, Jönsson EG, Luykx JJ, Magne CL, Malone SM, Medland SE, Meyers JL, Moberget T, Porjesz B, Sander C, Sisodiya SM, Thompson PM, van Beijsterveldt CEM, van Dellen E, Via M, Wright MJ. Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity. Brain Behav 2021; 11:e02188. [PMID: 34291596 PMCID: PMC8413828 DOI: 10.1002/brb3.2188] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 03/12/2021] [Accepted: 04/30/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND AND PURPOSE The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.
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Affiliation(s)
- Dirk J A Smit
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Scott J Burwell
- Department of Psychology, Minnesota Center for Twin and Family Research, University of Minnesota, Minneapolis, MN, USA.,Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Reyna L Gordon
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jeremy Harper
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Goethe Universität Frankfurt am Main, Frankfurt, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany.,LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,IU International University, Erfurt, Germany
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Philippe Jawinski
- LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Erik G Jönsson
- TOP-Norment, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Outpatient Second Opinion Clinic, GGNet Mental Health, Apeldoorn, The Netherlands
| | - Cyrille L Magne
- Psychology Department, Middle Tennessee State University, Murfreesboro, TN, USA.,Literacy Studies Ph.D. Program, Middle Tennessee State University, Mufreesboro, TN, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA.,Department of Psychiatry, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Torgeir Moberget
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont-St-Peter, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Edwin van Dellen
- Department of Psychiatry, Department of Intensive Care Medicine, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marc Via
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, and Institute of Neurosciences (UBNeuro), Universitat de Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Spain
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
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32
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Demaree JL, Ortiz RJ, Cai X, Aggarwal D, Senthilkumar I, Lawson C, Kulkarni P, Cushing BS, Ferris C. Exposure to methylphenidate during peri-adolescence decouples the prefrontal cortex: a multimodal MRI study. Am J Transl Res 2021; 13:8480-8495. [PMID: 34377346 PMCID: PMC8340152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 05/26/2021] [Indexed: 06/13/2023]
Abstract
This study was designed to assess the effects of daily psychostimulant exposure during juvenility and peri-adolescence on brain morphology and functional connectivity using multimodal magnetic resonance imaging. We hypothesized that long-term exposure to methylphenidate would enhance connectivity with the prefrontal cortex. Male rats were given daily injections of either methylphenidate (n=10), dextroamphetamine (n=10) or saline vehicle (n=10) from postnatal day 21 to 42. They were imaged between postnatal day 43 and 48. Voxel-based morphometry, diffusion weighted imaging, and resting state functional connectivity were used to quantify brain structure and function. Images from each modality were registered and analyzed, using a 3D MRI rat atlas providing site-specific data over 171 different brain areas. Following imaging, rats were tested for cognitive function using novel object preference. Long-lasting psychostimulant treatment was associated with only a few significant changes in brain volume and measures of anisotropy compared to vehicle. Resting state functional connectivity imaging revealed decreased coupling between the prefrontal cortex, basal ganglia and sensory motor cortices. There were no significant differences between experimental groups for cognitive behavior. In this exploratory study, we showed that chronic psychostimulant treatment throughout juvenility and preadolescence has a minimal effect on brain volume and gray matter microarchitecture, but significantly uncouples the connectivity in the cerebral/basal ganglia circuitry.
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Affiliation(s)
- Jack L Demaree
- Center for Translational NeuroImaging, Northeastern UniversityBoston, MA, USA
| | - Richard J Ortiz
- Department of Biological Sciences, University of Texas at El PasoEl Paso, TX 79968, USA
| | - Xuezhu Cai
- Center for Translational NeuroImaging, Northeastern UniversityBoston, MA, USA
| | - Dipak Aggarwal
- Center for Translational NeuroImaging, Northeastern UniversityBoston, MA, USA
| | - Ilakya Senthilkumar
- Center for Translational NeuroImaging, Northeastern UniversityBoston, MA, USA
| | - Christopher Lawson
- Center for Translational NeuroImaging, Northeastern UniversityBoston, MA, USA
| | - Praveen Kulkarni
- Center for Translational NeuroImaging, Northeastern UniversityBoston, MA, USA
| | - Bruce S Cushing
- Department of Biological Sciences, University of Texas at El PasoEl Paso, TX 79968, USA
| | - Craig Ferris
- Center for Translational NeuroImaging, Northeastern UniversityBoston, MA, USA
- Psychology and Pharmaceutical Sciences Northeastern UniversityBoston, MA, USA
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33
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Drakulich S, Thiffault AC, Olafson E, Parent O, Labbe A, Albaugh MD, Khundrakpam B, Ducharme S, Evans A, Chakravarty MM, Karama S. Maturational trajectories of pericortical contrast in typical brain development. Neuroimage 2021; 235:117974. [PMID: 33766753 PMCID: PMC8278832 DOI: 10.1016/j.neuroimage.2021.117974] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 02/27/2021] [Accepted: 03/17/2021] [Indexed: 11/16/2022] Open
Abstract
In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1-3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories.
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Affiliation(s)
- Stefan Drakulich
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada
| | - Anne-Charlotte Thiffault
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada
| | - Emily Olafson
- Douglas Institute, McGill University, 6875 Boulevard LaSalle, Verdun, QC H4H 1R3, Canada
| | - Olivier Parent
- Douglas Institute, McGill University, 6875 Boulevard LaSalle, Verdun, QC H4H 1R3, Canada
| | - Aurelie Labbe
- HEC Montréal, 3000, chemin de la Côte-Sainte-Catherine, Montreal, QC H3T 2A7, Canada
| | - Matthew D Albaugh
- Department of Psychiatry, Larnier College of Medicine, University of Vermont, United States
| | - Budhachandra Khundrakpam
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada
| | - Simon Ducharme
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada
| | - Alan Evans
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada
| | - Mallar M Chakravarty
- Douglas Institute, McGill University, 6875 Boulevard LaSalle, Verdun, QC H4H 1R3, Canada.
| | - Sherif Karama
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Douglas Institute, McGill University, 6875 Boulevard LaSalle, Verdun, QC H4H 1R3, Canada.
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34
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Forsyth JK, Mennigen E, Lin A, Sun D, Vajdi A, Kushan-Wells L, Ching CRK, Villalon-Reina JE, Thompson PM, Bearden CE. Prioritizing Genetic Contributors to Cortical Alterations in 22q11.2 Deletion Syndrome Using Imaging Transcriptomics. Cereb Cortex 2021; 31:3285-3298. [PMID: 33638978 PMCID: PMC8196250 DOI: 10.1093/cercor/bhab008] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 03/13/2020] [Accepted: 05/02/2020] [Indexed: 11/25/2022] Open
Abstract
22q11.2 deletion syndrome (22q11DS) results from a hemizygous deletion that typically spans 46 protein-coding genes and is associated with widespread alterations in brain morphology. The specific genetic mechanisms underlying these alterations remain unclear. In the 22q11.2 ENIGMA Working Group, we characterized cortical alterations in individuals with 22q11DS (n = 232) versus healthy individuals (n = 290) and conducted spatial convergence analyses using gene expression data from the Allen Human Brain Atlas to prioritize individual genes that may contribute to altered surface area (SA) and cortical thickness (CT) in 22q11DS. Total SA was reduced in 22q11DS (Z-score deviance = -1.04), with prominent reductions in midline posterior and lateral association regions. Mean CT was thicker in 22q11DS (Z-score deviance = +0.64), with focal thinning in a subset of regions. Regional expression of DGCR8 was robustly associated with regional severity of SA deviance in 22q11DS; AIFM3 was also associated with SA deviance. Conversely, P2RX6 was associated with CT deviance. Exploratory analysis of gene targets of microRNAs previously identified as down-regulated due to DGCR8 deficiency suggested that DGCR8 haploinsufficiency may contribute to altered corticogenesis in 22q11DS by disrupting cell cycle modulation. These findings demonstrate the utility of combining neuroanatomic and transcriptomic datasets to derive molecular insights into complex, multigene copy number variants.
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Affiliation(s)
- Jennifer K Forsyth
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA 90024, USA
| | - Eva Mennigen
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA 90024, USA
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden 01307, Germany
| | - Amy Lin
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA 90024, USA
- Interdepartmental Neuroscience Program, University of California at Los Angeles, Los Angeles, CA 90095, USA
| | - Daqiang Sun
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA 90024, USA
- Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA 90073, USA
| | - Ariana Vajdi
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA 90024, USA
| | - Leila Kushan-Wells
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA 90024, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Julio E Villalon-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, CA 90024, USA
- Brain Research Institute, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychology, University of California at Los Angeles, Los Angeles, CA 90095, USA
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35
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Zhao L, Batta I, Matloff W, O'Driscoll C, Hobel S, Toga AW. Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies. Neuroinformatics 2021; 19:285-303. [PMID: 32822005 DOI: 10.1007/s12021-020-09486-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Large-scale, case-control genome-wide association studies (GWASs) have revealed genetic variations associated with diverse neurological and psychiatric disorders. Recent advances in neuroimaging and genomic databases of large healthy and diseased cohorts have empowered studies to characterize effects of the discovered genetic factors on brain structure and function, implicating neural pathways and genetic mechanisms in the underlying biology. However, the unprecedented scale and complexity of the imaging and genomic data requires new advanced biomedical data science tools to manage, process and analyze the data. In this work, we introduce Neuroimaging PheWAS (phenome-wide association study): a web-based system for searching over a wide variety of brain-wide imaging phenotypes to discover true system-level gene-brain relationships using a unified genotype-to-phenotype strategy. This design features a user-friendly graphical user interface (GUI) for anonymous data uploading, study definition and management, and interactive result visualizations as well as a cloud-based computational infrastructure and multiple state-of-art methods for statistical association analysis and multiple comparison correction. We demonstrated the potential of Neuroimaging PheWAS with a case study analyzing the influences of the apolipoprotein E (APOE) gene on various brain morphological properties across the brain in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Benchmark tests were performed to evaluate the system's performance using data from UK Biobank. The Neuroimaging PheWAS system is freely available. It simplifies the execution of PheWAS on neuroimaging data and provides an opportunity for imaging genetics studies to elucidate routes at play for specific genetic variants on diseases in the context of detailed imaging phenotypic data.
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Affiliation(s)
- Lu Zhao
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Ishaan Batta
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - William Matloff
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Caroline O'Driscoll
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Samuel Hobel
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA.
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36
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Radonjić NV, Hess JL, Rovira P, Andreassen O, Buitelaar JK, Ching CRK, Franke B, Hoogman M, Jahanshad N, McDonald C, Schmaal L, Sisodiya SM, Stein DJ, van den Heuvel OA, van Erp TGM, van Rooij D, Veltman DJ, Thompson P, Faraone SV. Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders. Mol Psychiatry 2021; 26:2101-2110. [PMID: 33456050 PMCID: PMC8440178 DOI: 10.1038/s41380-020-01002-z] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 12/07/2020] [Accepted: 12/11/2020] [Indexed: 02/06/2023]
Abstract
Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.
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Affiliation(s)
- Nevena V Radonjić
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Jonathan L Hess
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Paula Rovira
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Ole Andreassen
- NORMENT-Institute of Clinical Medicine, Division of Mental Health and Addiction, Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Jan K Buitelaar
- Radboudumc, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina Del Rey, CA, USA
| | - Barbara Franke
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Department of Neurology and Biomedical Engineering, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina Del Rey, CA, USA
| | - Carrie McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics (CMIG), University of California, San Diego, CA, USA
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Orygen, The National Centre of Excellence for Youth Mental Health, Parkville, VIC, Australia
| | - Sanjay M Sisodiya
- UCL Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, University College London, London, UK
- Chalfont Centre for Epilepsy, Epilepsy Society, Bucks, UK
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Odile A van den Heuvel
- Department of Psychiatry and Department of Anatomy & Neurosciences, Amsterdam UMC/VUmc, Amsterdam, The Netherlands
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - Daan van Rooij
- Donders Centre for Cognitive Neuroimaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry and Department of Anatomy & Neurosciences, Amsterdam UMC/VUmc, Amsterdam, The Netherlands
| | - Paul Thompson
- Neuro Imaging Institute for Neuroimaging and Informatics, Keck School of Medicine of the University of Southern California, Marina Del Rey, CA, USA
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA.
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37
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Balestrini S, Lopez SM, Chinthapalli K, Sargsyan N, Demurtas R, Vos S, Altmann A, Suttie M, Hammond P, Sisodiya SM. Increased facial asymmetry in focal epilepsies associated with unilateral lesions. Brain Commun 2021; 3:fcab068. [PMID: 34222868 PMCID: PMC8244637 DOI: 10.1093/braincomms/fcab068] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/20/2021] [Accepted: 03/11/2021] [Indexed: 12/22/2022] Open
Abstract
The epilepsies are now conceptualized as network disruptions: focal epilepsies are considered to have network alterations in the hemisphere of seizure onset, whilst generalized epilepsies are considered to have bi-hemispheric network changes. Increasingly, many epilepsies are also considered to be neurodevelopmental disorders, with early changes in the brain underpinning seizure biology. The development of the structure of the face is influenced by complex molecular interactions between surface ectoderm and underlying developing forebrain and neural crest cells. This influence is likely to continue postnatally, given the evidence of facial growth changes over time in humans until at least 18 years of age. In this case-control study, we hypothesized that people with lateralized focal epilepsies (i.e. unilateral network changes) have an increased degree of facial asymmetry, compared with people with generalized epilepsies or controls without epilepsy. We applied three-dimensional stereophotogrammetry and dense surface models to evaluate facial asymmetry in people with epilepsy, aiming to generate new tools to explore pathophysiological mechanisms in epilepsy. We analysed neuroimaging data to explore the correlation between face and brain asymmetry. We consecutively recruited 859 people with epilepsy attending the epilepsy clinics at a tertiary referral centre. We used dense surface modelling of the full face and signature analyses of three-dimensional facial photographs to analyse facial differences between 378 cases and 205 healthy controls. Neuroimaging around the time of the facial photograph was available for 234 cases. We computed the brain asymmetry index between contralateral regions. Cases with focal symptomatic epilepsy associated with unilateral lesions showed greater facial asymmetry compared to controls (P = 0.0001, two-sample t-test). This finding was confirmed by linear regression analysis after controlling for age and gender. We also found a significant correlation between duration of illness and the brain asymmetry index of total average cortical thickness (r = -0.19, P = 0.0075) but not for total average surface area (r = 0.06, P = 0.3968). There was no significant correlation between facial asymmetry and asymmetry of regional cortical thickness or surface area. We propose that the greater facial asymmetry in cases with focal epilepsy caused by unilateral abnormality might be explained by early unilateral network disruption, and that this is independent of underlying brain asymmetry. Three-dimensional stereophotogrammetry and dense surface modelling are a novel powerful phenotyping tool in epilepsy that may permit greater understanding of pathophysiology in epilepsy, and generate further insights into the development of cerebral networks underlying epilepsy, and the genetics of facial and neural development.
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Affiliation(s)
- Simona Balestrini
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Seymour M Lopez
- Department of Medical Physics, Centre for Medical Image Computing, UCL, London, UK
| | - Krishna Chinthapalli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Narek Sargsyan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Rita Demurtas
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Sjoerd Vos
- Department of Medical Physics, Centre for Medical Image Computing, UCL, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andre Altmann
- Department of Medical Physics, Centre for Medical Image Computing, UCL, London, UK
| | - Michael Suttie
- Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.,Big Data Institute, Old Road Campus, University of Oxford, Oxford, UK
| | - Peter Hammond
- Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.,Big Data Institute, Old Road Campus, University of Oxford, Oxford, UK
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
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38
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Pajavand AM, Sharifi G, Anvari A, Bidari-Zerehpoosh F, Shamsi MA, Nateghinia S, Meybodi TE. Case Report: Chemotherapy Indication in a Case of Neurofibromatosis Type 1 Presenting Optic Pathway Glioma: A One-Year Clinical Case Study Using Differential Tractography Approach. Front Hum Neurosci 2021; 15:620439. [PMID: 33994974 PMCID: PMC8115022 DOI: 10.3389/fnhum.2021.620439] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 03/01/2021] [Indexed: 11/30/2022] Open
Abstract
Neurofibromatosis type 1 (NF1) is associated with peripheral and central nervous system tumors. It is noteworthy that the regions in which these tumors frequently arise are the optic pathways (OPs) and the brainstem. Thus, we decided to trace the procedure of diffusion Magnetic Resonance Imaging (dMRI) alterations along with Short-Wavelength Automated Perimetry (SWAP) examinations of the OPs after surgery and chemotherapy over 1 year, which enabled us to evaluate chemotherapy's efficacy in an NF1 patient with an OP tumor. In this study, a 25-year-old woman with NF1 and left optic radiation (OR) glioma underwent surgery to remove the glioma. Immunohistochemistry (IHC) revealed a Pilocytic Astrocytoma (PA) WHO grade I. Post-operation chemotherapy done using nine treatment cycles of administering Temozolomide (TMZ) for 5 days every 4 weeks. Applying the region of interest (ROI) differential tractography method and SWAP four times every 3 months allowed us to follow the patient's visual acuity alterations longitudinally. The differential deterministic tractography method and statistical analyses enabled us to discover the white matter (WM) tracts anisotropy alterations over time. Furthermore, statistical analyses on the SWAP results along time illustrated possible alterations in visual acuity. Then, we could compare and associate the findings with the SWAP examinations and patient symptoms longitudinally. Statistical analyses of SWAP tests revealed a significant improvement in visual fields, and longitudinal differential tractography showed myelination and dense axonal packing in the left OR after 1 year of treatment. In this study, we examined an old hypothesis suggesting that chemotherapy is more effective than radiotherapy for NF1 patients with OP gliomas (OPGs) because of the radiation side effects on the visual field, cognition, and cerebrovascular complications. Our longitudinal clinical case study involving dMRI and SWAP on a single NF1-OPG patient showed that chemotherapy did not suppress the OP myelination over time. However, it should be noted that this is a clinical case study, and, therefore, the generalization of results is limited. Future investigations might focus on genetic-based imaging, particularly in more cases. Further, meta-analyses are recommended for giving a proper Field Of View (FOV) to researchers as a subtle clue regarding precision medicine.
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Affiliation(s)
- Amir Mohammad Pajavand
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University Government College University, Tehran, Iran.,Skull Base Research Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Guive Sharifi
- Skull Base Research Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amir Anvari
- Department of Radiation Oncology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farahnaz Bidari-Zerehpoosh
- Department of Pathology, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad A Shamsi
- Skull Base Research Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Saeedeh Nateghinia
- Skull Base Research Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Tohid Emami Meybodi
- Functional Neurosurgery Research Center, Shohada Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Lei B, Wu F, Zhou J, Xiong D, Wang K, Kong L, Ke P, Chen J, Ning Y, Li X, Xiang Z, Wu K. NEURO-LEARN: a Solution for Collaborative Pattern Analysis of Neuroimaging Data. Neuroinformatics 2021; 19:79-91. [PMID: 32524429 DOI: 10.1007/s12021-020-09468-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The development of neuroimaging instrumentation has boosted neuroscience researches. Consequently, both the fineness and the cost of data acquisition have profoundly increased, leading to the main bottleneck of this field: limited sample size and high dimensionality of neuroimaging data. Therefore, the emphasis of ideas of data pooling and research collaboration has increased over the past decade. Collaborative analysis techniques emerge as the idea developed. In this paper, we present NEURO-LEARN, a solution for collaborative pattern analysis of neuroimaging data. Its collaboration scheme consists of four parts: projects, data, analysis, and reports. While data preparation workflows defined in projects reduce the high dimensionality of neuroimaging data by collaborative computation, pooling of derived data and sharing of pattern analysis workflows along with generated reports on the Web enlarge the sample size and ensure the reliability and reproducibility of pattern analysis. Incorporating this scheme, NEURO-LEARN provides an easy-to-use Web application that allows users from different sites to share projects and processed data, perform pattern analysis, and obtain result reports. We anticipate that this solution will help neuroscientists to enlarge sample size, conquer the curse of dimensionality and conduct reproducible studies on neuroimaging data with efficiency and validity.
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Affiliation(s)
- Bingye Lei
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, 510006, China
| | - Fengchun Wu
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, 510370, China
| | - Jing Zhou
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
| | - Dongsheng Xiong
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
| | - Kaixi Wang
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Lingyin Kong
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Pengfei Ke
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Jun Chen
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, 510500, China
- National Engineering Research Center for Healthcare Devices, Guangzhou, 510500, China
| | - Yuping Ning
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, 510370, China
| | - Xiaobo Li
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Zhiming Xiang
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, 510500, China
- Department of Radiology, Panyu Central Hospital of Guangzhou, Guangzhou, 511400, China
| | - Kai Wu
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, 510006, China.
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China.
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, 510370, China.
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, 510500, China.
- National Engineering Research Center for Healthcare Devices, Guangzhou, 510500, China.
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, 510006, China.
- Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, 980-8575, Japan.
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40
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Harper J, Liu M, Malone SM, McGue M, Iacono WG, Vrieze SI. Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment. Psychol Med 2021; 52:1-11. [PMID: 33731234 PMCID: PMC8448784 DOI: 10.1017/s0033291721000763] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 02/16/2021] [Accepted: 02/17/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND To better characterize brain-based mechanisms of polygenic liability for psychopathology and psychological traits, we extended our previous report (Liu et al. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychological Medicine, 2017), focused solely on schizophrenia, to test the association between multivariate psychophysiological candidate endophenotypes (including novel measures of θ/δ oscillatory activity) and a range of polygenic scores (PGSs), namely alcohol/cannabis/nicotine use, an updated schizophrenia PGS (containing 52 more genome-wide significant loci than the PGS used in our previous report) and educational attainment. METHOD A large community-based twin/family sample (N = 4893) was genome-wide genotyped and imputed. PGSs were constructed for alcohol use, regular smoking initiation, lifetime cannabis use, schizophrenia, and educational attainment. Eleven endophenotypes were assessed: visual oddball task event-related electroencephalogram (EEG) measures (target-related parietal P3 amplitude, frontal θ, and parietal δ energy/inter-trial phase clustering), band-limited resting-state EEG power, antisaccade error rate. Principal component analysis exploited covariation among endophenotypes to extract a smaller number of meaningful dimensions/components for statistical analysis. RESULTS Endophenotypes were heritable. PGSs showed expected intercorrelations (e.g. schizophrenia PGS correlated positively with alcohol/nicotine/cannabis PGSs). Schizophrenia PGS was negatively associated with an event-related P3/δ component [β = -0.032, nonparametric bootstrap 95% confidence interval (CI) -0.059 to -0.003]. A prefrontal control component (event-related θ/antisaccade errors) was negatively associated with alcohol (β = -0.034, 95% CI -0.063 to -0.006) and regular smoking PGSs (β = -0.032, 95% CI -0.061 to -0.005) and positively associated with educational attainment PGS (β = 0.031, 95% CI 0.003-0.058). CONCLUSIONS Evidence suggests that multivariate endophenotypes of decision-making (P3/δ) and cognitive/attentional control (θ/antisaccade error) relate to alcohol/nicotine, schizophrenia, and educational attainment PGSs and represent promising targets for future research.
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Affiliation(s)
- Jeremy Harper
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Twin Cities, MN, USA
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Stephen M. Malone
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - William G. Iacono
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
| | - Scott I. Vrieze
- Department of Psychology, University of Minnesota, Twin Cities, MN, USA
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White matter microstructure and its relation to clinical features of obsessive-compulsive disorder: findings from the ENIGMA OCD Working Group. Transl Psychiatry 2021; 11:173. [PMID: 33731673 PMCID: PMC7969744 DOI: 10.1038/s41398-021-01276-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 06/15/2020] [Accepted: 10/19/2020] [Indexed: 11/17/2022] Open
Abstract
Microstructural alterations in cortico-subcortical connections are thought to be present in obsessive-compulsive disorder (OCD). However, prior studies have yielded inconsistent findings, perhaps because small sample sizes provided insufficient power to detect subtle abnormalities. Here we investigated microstructural white matter alterations and their relation to clinical features in the largest dataset of adult and pediatric OCD to date. We analyzed diffusion tensor imaging metrics from 700 adult patients and 645 adult controls, as well as 174 pediatric patients and 144 pediatric controls across 19 sites participating in the ENIGMA OCD Working Group, in a cross-sectional case-control magnetic resonance study. We extracted measures of fractional anisotropy (FA) as main outcome, and mean diffusivity, radial diffusivity, and axial diffusivity as secondary outcomes for 25 white matter regions. We meta-analyzed patient-control group differences (Cohen's d) across sites, after adjusting for age and sex, and investigated associations with clinical characteristics. Adult OCD patients showed significant FA reduction in the sagittal stratum (d = -0.21, z = -3.21, p = 0.001) and posterior thalamic radiation (d = -0.26, z = -4.57, p < 0.0001). In the sagittal stratum, lower FA was associated with a younger age of onset (z = 2.71, p = 0.006), longer duration of illness (z = -2.086, p = 0.036), and a higher percentage of medicated patients in the cohorts studied (z = -1.98, p = 0.047). No significant association with symptom severity was found. Pediatric OCD patients did not show any detectable microstructural abnormalities compared to controls. Our findings of microstructural alterations in projection and association fibers to posterior brain regions in OCD are consistent with models emphasizing deficits in connectivity as an important feature of this disorder.
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42
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Comparison of regional brain deficit patterns in common psychiatric and neurological disorders as revealed by big data. NEUROIMAGE-CLINICAL 2021; 29:102574. [PMID: 33530016 PMCID: PMC7851406 DOI: 10.1016/j.nicl.2021.102574] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/08/2020] [Accepted: 01/16/2021] [Indexed: 12/15/2022]
Abstract
RVI for MDD and AD was derived based on large meta-analytical findings. RVI-MDD and AD were significantly elevated in UKBB subjects with respective illnesses. There was no elevation of RVI-MDD in subjects with AD or RVI-AD in subjects with MDD. RVI captures neuroanatomic deviation patterns. RVI is a useful biomarker for assessing similarity to neuropsychiatric illnesses.
Neurological and psychiatric illnesses are associated with regional brain deficit patterns that bear unique signatures and capture illness-specific characteristics. The Regional Vulnerability Index (RVI) was developed to quantify brain similarity by comparing individual white matter microstructure, cortical gray matter thickness and subcortical gray matter structural volume measures with neuroanatomical deficit patterns derived from large-scale meta-analytic studies. We tested the specificity of the RVI approach for major depressive disorder (MDD) and Alzheimer’s disease (AD) in a large epidemiological sample of UK Biobank (UKBB) participants (N = 19,393; 9138 M/10,255F; age = 64.8 ± 7.4 years). Compared to controls free of neuropsychiatric disorders, participants with MDD (N = 2,248; 805 M/1443F; age = 63.4 ± 7.4) had significantly higher RVI-MDD values (t = 5.6, p = 1·10−8), but showed no detectable difference in RVI-AD (t = 2.0, p = 0.10). Subjects with dementia (N = 7; 4 M/3F; age = 68.6 ± 8.6 years) showed significant elevation in RVI-AD (t = 4.2, p = 3·10−5) but not RVI-MDD (t = 2.1, p = 0.10) compared to controls. Even within affective illnesses, participants with bipolar disorder (N = 54) and anxiety disorder (N = 773) showed no significant elevation in whole-brain RVI-MDD. Participants with Parkinson’s disease (N = 37) showed elevation in RVI-AD (t = 2.4, p = 0.01) while subjects with stroke (N = 247) showed no such elevation (t = 1.1, p = 0.3). In summary, we demonstrated elevation in RVI-MDD and RVI-AD measures in the respective illnesses with strong replicability that is relatively specific to the respective diagnoses. These neuroanatomic deviation patterns offer a useful biomarker for population-wide assessments of similarity to neuropsychiatric illnesses.
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43
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Abstract
Anatomical imaging in OCD using magnetic resonance imaging (MRI) has been performed since the late 1980s. MRI research was further stimulated with the advent of automated image processing techniques such as voxel-based morphometry (VBM) and surface-based methods (e.g., FreeSurfer) which allow for detailed whole-brain data analyses. Early studies suggesting involvement of corticostriatal circuitry (particularly orbitofrontal cortex and ventral striatum) have been complemented by meta-analyses and pooled analyses indicating additional involvement of posterior brain regions, in particular parietal cortex. Recent large-scale meta-analyses from the ENIGMA consortium have revealed greater pallidum and smaller hippocampus volume in adult OCD, coupled with parietal cortical thinning. Frontal cortical thinning was only observed in medicated patients. Previous reports of symptom dimension-specific alterations were not confirmed. In paediatric OCD, thalamus enlargement has been a consistent finding. Studies investigating white matter volume (VBM) or integrity (using diffusion tensor imaging (DTI)) have shown mixed results, with recent DTI meta-analyses mainly showing involvement of posterior cortical-subcortical tracts in addition to subcortical-prefrontal connections. To which extent these abnormalities are unique to OCD or common to other psychiatric disorders is unclear, as few comparative studies have been performed. Overall, neuroanatomical alterations in OCD appear to be subtle and may vary with time, stressing the need for adequately powered longitudinal studies. Although multivariate approaches using machine learning methodologies have so far been disappointing in distinguishing individual OCD patients from healthy controls, including multimodal data in such analyses may aid in further establishing a neurobiological profile of OCD.
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Affiliation(s)
- D J Veltman
- Department of Psychiatry, Amsterdam UMC, Amsterdam, The Netherlands.
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44
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Ushakov VL, Malashenkova IK, Kostyuk GP, Zakharova NV, Krynskiy SA, Kartashov SI, Ogurtsov DP, Bravve LV, Kaydan MA, Hailov NA, Chekulaeva EI, Didkovsky NA. [The relationship between inflammation, cognitive disorders and neuroimaging data in schizophrenia]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 120:70-78. [PMID: 33340301 DOI: 10.17116/jnevro202012011170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To search for the relationship between the results of functional imaging, immunological parameters and laboratory markers of inflammation in schizophrenia, taking into account cognitive impairment in patients, and to consider the possibility of using a multidisciplinary approach to diagnosis, treatment and prognosis of schizophrenia. MATERIAL AND METHODS The study included 25 patients with schizophrenia and 13 healthy volunteers. Psychiatric scales were administered to evaluate the patient's condition. The main indicators of humoral immunity, the level of markers of inflammation, key pro-inflammatory and anti-inflammatory cytokines, and growth factor VEGF were determined by ELISA. Brain MRI was performed. All calculated tractographic data are included in the connection database to study the effect of immunological markers and the degree of severity of cognitive impairment. RESULTS AND CONCLUSION Levels of markers of systemic inflammation and growth factor VEGF-A as well as the activation of humoral immunity are increased in patients with schizophrenia compared with controls. For the first time, the relationship of immunological parameters with the coefficient of quantitative anisotropy in the area of the corpus callosum in schizophrenia was revealed. The results indicate the possible value of indicators of the activation of the humoral immune response and systemic inflammation as markers of neurophysiological changes and cognitive dysfunction in schizophrenia.
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Affiliation(s)
- V L Ushakov
- National Researh Center «Kurchatov Institute», Moscow, Russia.,Alekseev Mental-health Hospital No1, Moscow, Russia
| | - I K Malashenkova
- National Researh Center «Kurchatov Institute», Moscow, Russia.,Federal Research and Clinical Center of physical-chemical medicine, Moscow, Russia
| | - G P Kostyuk
- Alekseev Mental-health Hospital No1, Moscow, Russia
| | | | - S A Krynskiy
- National Researh Center «Kurchatov Institute», Moscow, Russia
| | - S I Kartashov
- National Researh Center «Kurchatov Institute», Moscow, Russia
| | - D P Ogurtsov
- National Researh Center «Kurchatov Institute», Moscow, Russia.,Federal Research and Clinical Center of physical-chemical medicine, Moscow, Russia
| | - L V Bravve
- Alekseev Mental-health Hospital No1, Moscow, Russia
| | - M A Kaydan
- Alekseev Mental-health Hospital No1, Moscow, Russia
| | - N A Hailov
- National Researh Center «Kurchatov Institute», Moscow, Russia
| | - E I Chekulaeva
- National Researh Center «Kurchatov Institute», Moscow, Russia
| | - N A Didkovsky
- Federal Research and Clinical Center of physical-chemical medicine, Moscow, Russia
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45
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Sørensen Ø, Walhovd KB, Fjell AM. A recipe for accurate estimation of lifespan brain trajectories, distinguishing longitudinal and cohort effects. Neuroimage 2020; 226:117596. [PMID: 33248257 DOI: 10.1016/j.neuroimage.2020.117596] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/20/2020] [Accepted: 11/17/2020] [Indexed: 12/21/2022] Open
Abstract
We address the problem of estimating how different parts of the brain develop and change throughout the lifespan, and how these trajectories are affected by genetic and environmental factors. Estimation of these lifespan trajectories is statistically challenging, since their shapes are typically highly nonlinear, and although true change can only be quantified by longitudinal examinations, as follow-up intervals in neuroimaging studies typically cover less than 10% of the lifespan, use of cross-sectional information is necessary. Linear mixed models (LMMs) and structural equation models (SEMs) commonly used in longitudinal analysis rely on assumptions which are typically not met with lifespan data, in particular when the data consist of observations combined from multiple studies. While LMMs require a priori specification of a polynomial functional form, SEMs do not easily handle data with unstructured time intervals between measurements. Generalized additive mixed models (GAMMs) offer an attractive alternative, and in this paper we propose various ways of formulating GAMMs for estimation of lifespan trajectories of 12 brain regions, using a large longitudinal dataset and realistic simulation experiments. We show that GAMMs are able to more accurately fit lifespan trajectories, distinguish longitudinal and cross-sectional effects, and estimate effects of genetic and environmental exposures. Finally, we discuss and contrast questions related to lifespan research which strictly require repeated measures data and questions which can be answered with a single measurement per participant, and in the latter case, which simplifying assumptions that need to be made. The examples are accompanied with R code, providing a tutorial for researchers interested in using GAMMs.
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Affiliation(s)
- Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
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Garcia-Dias R, Scarpazza C, Baecker L, Vieira S, Pinaya WHL, Corvin A, Redolfi A, Nelson B, Crespo-Facorro B, McDonald C, Tordesillas-Gutiérrez D, Cannon D, Mothersill D, Hernaus D, Morris D, Setien-Suero E, Donohoe G, Frisoni G, Tronchin G, Sato J, Marcelis M, Kempton M, van Haren NEM, Gruber O, McGorry P, Amminger P, McGuire P, Gong Q, Kahn RS, Ayesa-Arriola R, van Amelsvoort T, Ortiz-García de la Foz V, Calhoun V, Cahn W, Mechelli A. Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners. Neuroimage 2020; 220:117127. [PMID: 32634595 PMCID: PMC7573655 DOI: 10.1016/j.neuroimage.2020.117127] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 06/08/2020] [Accepted: 06/30/2020] [Indexed: 02/05/2023] Open
Abstract
•We present Neuroharmony, a harmonization tool for images from unseen scanners. •We developed Neuroharmony using a total of 15,026 sMRI images. •The tool was able to reduce scanner-related bias from unseen scans. •Neuroharmony represents a significant step towards imaging-based clinical tools. •Neuroharmony is available at https://github.com/garciadias/Neuroharmony .
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Affiliation(s)
- Rafael Garcia-Dias
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom.
| | - Cristina Scarpazza
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom; Department of General Psychology, University of Padova, Via Venezia 8, Padova, Italy
| | - Lea Baecker
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom
| | - Sandra Vieira
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom
| | - Walter H L Pinaya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom; Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil
| | - Aiden Corvin
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Alberto Redolfi
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Barnaby Nelson
- Orygen, The National Centre of Excellence in Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Benedicto Crespo-Facorro
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Departamento de Psiquiatria, Universidad de Sevilla, Instituto de Biomedicina de Sevilla (IBIS), Spain; Hospital Universitario Virgen del Rocío, Sevilla, Spain; Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, School of Medicine & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - Diana Tordesillas-Gutiérrez
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Neuroimaging Unit, Technological Facilities, Valdecilla Biomedical Research Institute IDIVAL, Spain
| | - Dara Cannon
- Clinical Neuroimaging Laboratory, School of Medicine & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - David Mothersill
- School of Psychology & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - Dennis Hernaus
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht, the Netherlands
| | - Derek Morris
- Discipline of Biochemistry & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - Esther Setien-Suero
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Gary Donohoe
- School of Psychology & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - Giovanni Frisoni
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Ageing, University Hospitals and University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology - LANE, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giulia Tronchin
- Clinical Neuroimaging Laboratory, School of Medicine & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - João Sato
- Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil
| | - Machteld Marcelis
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht, the Netherlands
| | - Matthew Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre - Sophia Children's Hospital, Rotterdam, Netherlands
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Germany; Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Germany
| | - Patrick McGorry
- Orygen, The National Centre of Excellence in Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Paul Amminger
- Orygen, The National Centre of Excellence in Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - René S Kahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rosa Ayesa-Arriola
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht, the Netherlands
| | - Victor Ortiz-García de la Foz
- Centro Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia; State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, the Netherlands
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, United Kingdom
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Sørensen Ø, Brandmaier AM, Macià D, Ebmeier K, Ghisletta P, Kievit RA, Mowinckel AM, Walhovd KB, Westerhausen R, Fjell A. Meta-analysis of generalized additive models in neuroimaging studies. Neuroimage 2020; 224:117416. [PMID: 33017652 DOI: 10.1016/j.neuroimage.2020.117416] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 09/23/2020] [Accepted: 09/25/2020] [Indexed: 12/15/2022] Open
Abstract
Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to systematically investigate between-study differences. Restrictions due to privacy or proprietary data as well as more practical concerns can make it hard to share neuroimaging datasets, such that analyzing all data in a common location might be impractical or impossible. Meta-analytic methods provide a way to overcome this issue, by combining aggregated quantities like model parameters or risk ratios. Most meta-analytic tools focus on parametric statistical models, and methods for meta-analyzing semi-parametric models like generalized additive models have not been well developed. Parametric models are often not appropriate in neuroimaging, where for instance age-brain relationships may take forms that are difficult to accurately describe using such models. In this paper we introduce meta-GAM, a method for meta-analysis of generalized additive models which does not require individual participant data, and hence is suitable for increasing statistical power while upholding privacy and other regulatory concerns. We extend previous works by enabling the analysis of multiple model terms as well as multivariate smooth functions. In addition, we show how meta-analytic p-values can be computed for smooth terms. The proposed methods are shown to perform well in simulation experiments, and are demonstrated in a real data analysis on hippocampal volume and self-reported sleep quality data from the Lifebrain consortium. We argue that application of meta-GAM is especially beneficial in lifespan neuroscience and imaging genetics. The methods are implemented in an accompanying R package metagam, which is also demonstrated.
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Affiliation(s)
- Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Pb. 1094 Blindern, Oslo 0317, Norway.
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Dídac Macià
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Spain
| | | | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Switzerland; Swiss Distance University Institute, Switzerland; Swiss National Centre of Competence in Research LIVES, University of Geneva, Switzerland
| | - Rogier A Kievit
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Pb. 1094 Blindern, Oslo 0317, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Pb. 1094 Blindern, Oslo 0317, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Rene Westerhausen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Pb. 1094 Blindern, Oslo 0317, Norway
| | - Anders Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Pb. 1094 Blindern, Oslo 0317, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
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48
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Popuri K, Ma D, Wang L, Beg MF. Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases. Hum Brain Mapp 2020; 41:4127-4147. [PMID: 32614505 PMCID: PMC7469784 DOI: 10.1002/hbm.25115] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Revised: 04/15/2020] [Accepted: 06/08/2020] [Indexed: 12/29/2022] Open
Abstract
Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1-weighted magnetic resonance imaging (MRI) is a commonly used neuroimaging modality for measuring brain structure in vivo, potentially providing information enabling the design of biomarkers for DAT. We propose a novel biomarker using structural MRI volume-based features to compute a similarity score for the individual's structural patterns relative to those observed in the DAT group. We employed ensemble-learning framework that combines structural features in most discriminative ROIs to create an aggregate measure of neurodegeneration in the brain. This classifier is trained on 423 stable normal control (NC) and 330 DAT subjects, where clinical diagnosis is likely to have the highest certainty. Independent validation on 8,834 unseen images from ADNI, AIBL, OASIS, and MIRIAD Alzheimer's disease (AD) databases showed promising potential to predict the development of DAT depending on the time-to-conversion (TTC). Classification performance on stable versus progressive mild cognitive impairment (MCI) groups achieved an AUC of 0.81 for TTC of 6 months and 0.73 for TTC of up to 7 years, achieving state-of-the-art results. The output score, indicating similarity to patterns seen in DAT, provides an intuitive measure of how closely the individual's brain features resemble the DAT group. This score can be used for assessing the presence of AD structural atrophy patterns in normal aging and MCI stages, as well as monitoring the progression of the individual's brain along with the disease course.
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Affiliation(s)
- Karteek Popuri
- School of Engineering ScienceSimon Fraser UniversityBarnabyBritish ColumbiaCanada
| | - Da Ma
- School of Engineering ScienceSimon Fraser UniversityBarnabyBritish ColumbiaCanada
| | - Lei Wang
- Feinberg School of MedicineNorthwestern UniversityEvanstonIllinoisUSA
| | - Mirza Faisal Beg
- School of Engineering ScienceSimon Fraser UniversityBarnabyBritish ColumbiaCanada
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49
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Zhang F, Cetin Karayumak S, Hoffmann N, Rathi Y, Golby AJ, O'Donnell LJ. Deep white matter analysis (DeepWMA): Fast and consistent tractography segmentation. Med Image Anal 2020; 65:101761. [PMID: 32622304 PMCID: PMC7483951 DOI: 10.1016/j.media.2020.101761] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 06/16/2020] [Accepted: 06/18/2020] [Indexed: 02/07/2023]
Abstract
White matter tract segmentation, i.e. identifying tractography fibers (streamline trajectories) belonging to anatomically meaningful fiber tracts, is an essential step to enable tract quantification and visualization. In this study, we present a deep learning tractography segmentation method (DeepWMA) that allows fast and consistent identification of 54 major deep white matter fiber tracts from the whole brain. We create a large-scale training tractography dataset of 1 million labeled fiber samples, and we propose a novel 2D multi-channel feature descriptor (FiberMap) that encodes spatial coordinates of points along each fiber. We learn a convolutional neural network (CNN) fiber classification model based on FiberMap and obtain a high fiber classification accuracy of 90.99% on the training tractography data with ground truth fiber labels. Then, the method is evaluated on a test dataset of 597 diffusion MRI scans from six independently acquired populations across genders, the lifespan (1 day - 82 years), and different health conditions (healthy control, neuropsychiatric disorders, and brain tumor patients). We perform comparisons with two state-of-the-art tract segmentation methods. Experimental results show that our method obtains a highly consistent tract segmentation result, where on average over 99% of the fiber tracts are successfully identified across all subjects under study, most importantly, including neonates and patients with space-occupying brain tumors. We also demonstrate good generalization of the method to tractography data from multiple different fiber tracking methods. The proposed method leverages deep learning techniques and provides a fast and efficient tool for brain white matter segmentation in large diffusion MRI tractography datasets.
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Affiliation(s)
- Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | | | - Nico Hoffmann
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexandra J Golby
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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50
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Sun D, Ching CRK, Lin A, Forsyth JK, Kushan L, Vajdi A, Jalbrzikowski M, Hansen L, Villalon-Reina JE, Qu X, Jonas RK, van Amelsvoort T, Bakker G, Kates WR, Antshel KM, Fremont W, Campbell LE, McCabe KL, Daly E, Gudbrandsen M, Murphy CM, Murphy D, Craig M, Vorstman J, Fiksinski A, Koops S, Ruparel K, Roalf DR, Gur RE, Schmitt JE, Simon TJ, Goodrich-Hunsaker NJ, Durdle CA, Bassett AS, Chow EWC, Butcher NJ, Vila-Rodriguez F, Doherty J, Cunningham A, van den Bree MB, Linden DEJ, Moss H, Owen MJ, Murphy KC, McDonald-McGinn DM, Emanuel B, van Erp TGM, Turner JA, Thompson PM, Bearden CE. Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size. Mol Psychiatry 2020; 25:1822-1834. [PMID: 29895892 PMCID: PMC6292748 DOI: 10.1038/s41380-018-0078-5] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 04/15/2018] [Accepted: 04/23/2018] [Indexed: 11/11/2022]
Abstract
The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion size. To address these issues, we developed the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta-Analysis) 22q11.2 Working Group, representing the largest analysis of brain structural alterations in 22q11DS to date. The imaging data were collected from 10 centers worldwide, including 474 subjects with 22q11DS (age = 18.2 ± 8.6; 46.9% female) and 315 typically developing, matched controls (age = 18.0 ± 9.2; 45.9% female). Compared to controls, 22q11DS individuals showed thicker cortical gray matter overall (left/right hemispheres: Cohen's d = 0.61/0.65), but focal thickness reduction in temporal and cingulate cortex. Cortical surface area (SA), however, showed pervasive reductions in 22q11DS (left/right hemispheres: d = -1.01/-1.02). 22q11DS cases vs. controls were classified with 93.8% accuracy based on these neuroanatomic patterns. Comparison of 22q11DS-psychosis to idiopathic schizophrenia (ENIGMA-Schizophrenia Working Group) revealed significant convergence of affected brain regions, particularly in fronto-temporal cortex. Finally, cortical SA was significantly greater in 22q11DS cases with smaller 1.5 Mb deletions, relative to those with typical 3 Mb deletions. We found a robust neuroanatomic signature of 22q11DS, and the first evidence that deletion size impacts brain structure. Psychotic illness in this highly penetrant deletion was associated with similar neuroanatomic abnormalities to idiopathic schizophrenia. These consistent cross-site findings highlight the homogeneity of this single genetic etiology, and support the suitability of 22q11DS as a biological model of schizophrenia.
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Affiliation(s)
- Daqiang Sun
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA ,0000 0001 0384 5381grid.417119.bDepartment of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA USA
| | - Christopher R. K. Ching
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA ,0000 0001 2156 6853grid.42505.36Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA USA ,0000 0000 9632 6718grid.19006.3eInterdepartmental Neuroscience Program, University of California, Los Angeles, Los Angeles, CA USA
| | - Amy Lin
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA ,0000 0000 9632 6718grid.19006.3eInterdepartmental Neuroscience Program, University of California, Los Angeles, Los Angeles, CA USA
| | - Jennifer K. Forsyth
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA ,0000 0000 9632 6718grid.19006.3eDepartment of Psychology, University of California, Los Angeles, Los Angeles, CA USA
| | - Leila Kushan
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA
| | - Ariana Vajdi
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA
| | - Maria Jalbrzikowski
- 0000 0004 1936 9000grid.21925.3dDepartment of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Laura Hansen
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA
| | - Julio E. Villalon-Reina
- 0000 0001 2156 6853grid.42505.36Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA USA
| | - Xiaoping Qu
- 0000 0001 2156 6853grid.42505.36Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA USA
| | - Rachel K. Jonas
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA ,0000 0000 9632 6718grid.19006.3eInterdepartmental Neuroscience Program, University of California, Los Angeles, Los Angeles, CA USA
| | - Therese van Amelsvoort
- 0000 0001 0481 6099grid.5012.6Department of Psychiatry & Neuropsychology, Maastricht University, Maastricht, Netherlands
| | - Geor Bakker
- 0000 0001 0481 6099grid.5012.6Department of Psychiatry & Neuropsychology, Maastricht University, Maastricht, Netherlands
| | - Wendy R. Kates
- 0000 0000 9159 4457grid.411023.5Department of Psychiatry and Behavioral Sciences, State University of New York, Upstate Medical University, Syracuse, NY USA
| | - Kevin M. Antshel
- 0000 0001 2189 1568grid.264484.8Department of Psychology, Syracuse University, Syracuse, NY USA
| | - Wanda Fremont
- 0000 0000 9159 4457grid.411023.5Department of Psychiatry and Behavioral Sciences, State University of New York, Upstate Medical University, Syracuse, NY USA
| | - Linda E. Campbell
- 0000 0000 8831 109Xgrid.266842.cPRC GrowUpWell, University of Newcastle, Newcastle, Australia ,0000 0000 8831 109Xgrid.266842.cSchool of Psychology, University of Newcastle, Newcastle, Australia
| | - Kathryn L. McCabe
- 0000 0000 8831 109Xgrid.266842.cSchool of Psychology, University of Newcastle, Newcastle, Australia ,0000 0004 1936 9684grid.27860.3bUC Davis MIND Institute and Department of Psychiatry and Behavioral Sciences, Davis, CA USA
| | - Eileen Daly
- 0000 0001 2322 6764grid.13097.3cSackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King’s College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Maria Gudbrandsen
- 0000 0001 2322 6764grid.13097.3cSackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King’s College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Clodagh M. Murphy
- 0000 0001 2322 6764grid.13097.3cSackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King’s College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK ,0000 0004 0581 2008grid.451052.7Behavioural Genetics Clinic, Adult Autism Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, UK
| | - Declan Murphy
- 0000 0001 2322 6764grid.13097.3cSackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King’s College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK ,0000 0004 0581 2008grid.451052.7Behavioural Genetics Clinic, Adult Autism Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, UK
| | - Michael Craig
- 0000 0001 2322 6764grid.13097.3cSackler Institute for Translational Neurodevelopment and Department of Forensic and Neurodevelopmental Sciences, King’s College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK ,0000 0004 0581 2008grid.451052.7National Autism Unit, Bethlem Royal Hospital, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, UK
| | - Jacob Vorstman
- 0000 0004 0473 9646grid.42327.30Hospital for Sick Children, Toronto, ON Canada ,0000000090126352grid.7692.aDepartment of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands ,0000 0001 2157 2938grid.17063.33Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Ania Fiksinski
- 0000 0004 0473 9646grid.42327.30Hospital for Sick Children, Toronto, ON Canada ,0000 0000 8793 5925grid.155956.bClinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario Canada ,0000 0001 2157 2938grid.17063.33Department of Psychiatry, University of Toronto, Toronto, ON Canada ,0000 0004 0474 0428grid.231844.8The Dalglish Family 22q Clinic, Department of Psychiatry, and Toronto General Research Institute, University Health Network, Toronto, ON Canada ,0000 0000 8793 5925grid.155956.bCampbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada
| | - Sanne Koops
- 0000000090126352grid.7692.aDepartment of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kosha Ruparel
- 0000 0001 0680 8770grid.239552.aDepartment of Psychiatry, University of Pennsylvania, and the Lifespan Brain Institute, Penn Medicine and the Children’s Hospital of Philadelphia, Philadelphia, PA USA
| | - David R. Roalf
- 0000 0001 0680 8770grid.239552.aDepartment of Psychiatry, University of Pennsylvania, and the Lifespan Brain Institute, Penn Medicine and the Children’s Hospital of Philadelphia, Philadelphia, PA USA
| | - Raquel E. Gur
- 0000 0004 1936 8972grid.25879.31Department of Radiology, Division of Neuroradiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA ,0000 0001 0680 8770grid.239552.aDepartment of Psychiatry, University of Pennsylvania, and the Lifespan Brain Institute, Penn Medicine and the Children’s Hospital of Philadelphia, Philadelphia, PA USA
| | - J. Eric Schmitt
- 0000 0004 1936 8972grid.25879.31Department of Radiology, Division of Neuroradiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA ,0000 0001 0680 8770grid.239552.aDepartment of Psychiatry, University of Pennsylvania, and the Lifespan Brain Institute, Penn Medicine and the Children’s Hospital of Philadelphia, Philadelphia, PA USA
| | - Tony J. Simon
- 0000 0004 1936 9684grid.27860.3bUC Davis MIND Institute and Department of Psychiatry and Behavioral Sciences, Davis, CA USA
| | - Naomi J. Goodrich-Hunsaker
- 0000 0004 1936 9684grid.27860.3bUC Davis MIND Institute and Department of Psychiatry and Behavioral Sciences, Davis, CA USA ,0000 0004 1936 9115grid.253294.bDepartment of Psychology, Brigham Young University, Provo, UT USA
| | - Courtney A. Durdle
- 0000 0004 1936 9684grid.27860.3bUC Davis MIND Institute and Department of Psychiatry and Behavioral Sciences, Davis, CA USA
| | - Anne S. Bassett
- 0000 0000 8793 5925grid.155956.bClinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario Canada ,0000 0001 2157 2938grid.17063.33Department of Psychiatry, University of Toronto, Toronto, ON Canada ,0000 0004 0474 0428grid.231844.8The Dalglish Family 22q Clinic, Department of Psychiatry, and Toronto General Research Institute, University Health Network, Toronto, ON Canada ,0000 0000 8793 5925grid.155956.bCampbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada
| | - Eva W. C. Chow
- 0000 0000 8793 5925grid.155956.bClinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario Canada ,0000 0001 2157 2938grid.17063.33Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Nancy J. Butcher
- 0000 0004 0473 9646grid.42327.30Hospital for Sick Children, Toronto, ON Canada ,0000 0000 8793 5925grid.155956.bClinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario Canada
| | - Fidel Vila-Rodriguez
- 0000 0001 2288 9830grid.17091.3eDepartment of Psychiatry, University of British Columbia, Vancouver, British Columbia Canada
| | - Joanne Doherty
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Adam Cunningham
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Marianne B.M. van den Bree
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - David E. J. Linden
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Hayley Moss
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael J. Owen
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Kieran C. Murphy
- 0000 0004 0488 7120grid.4912.eDepartment of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Donna M. McDonald-McGinn
- 0000 0001 0680 8770grid.239552.aDivision of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania USA ,0000 0004 1936 8972grid.25879.31Department of Pediatrics, The Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania USA ,0000 0001 0680 8770grid.239552.aDivision of Clinical Genetics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania USA
| | - Beverly Emanuel
- 0000 0004 1936 8972grid.25879.31Department of Pediatrics, The Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania USA ,0000 0001 0680 8770grid.239552.aDivision of Clinical Genetics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania USA
| | - Theo G. M. van Erp
- 0000 0001 0668 7243grid.266093.8Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA USA
| | - Jessica A. Turner
- 0000 0004 1936 7400grid.256304.6Imaging Genetics and Neuroinformatics Lab, Department of Psychology, Georgia State University, Atlanta, GA USA ,0000 0004 0409 4614grid.280503.cMind Research Network, Albuquerque, NM USA
| | - Paul M. Thompson
- 0000 0001 2156 6853grid.42505.36Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA USA ,0000 0001 2156 6853grid.42505.36Departments of Neurology, Psychiatry, Radiology, Engineering, Pediatrics and Ophthalmology, University of Southern California, California, CA USA
| | - Carrie E. Bearden
- 0000 0000 9632 6718grid.19006.3eDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA USA ,0000 0000 9632 6718grid.19006.3eDepartment of Psychology, University of California, Los Angeles, Los Angeles, CA USA
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