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Zhang R, Chen L, Oliver LD, Voineskos AN, Park JY. SAN: Mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites. Hum Brain Mapp 2024; 45:e26692. [PMID: 38712767 PMCID: PMC11075170 DOI: 10.1002/hbm.26692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/27/2024] [Accepted: 04/08/2024] [Indexed: 05/08/2024] Open
Abstract
In neuroimaging studies, combining data collected from multiple study sites or scanners is becoming common to increase the reproducibility of scientific discoveries. At the same time, unwanted variations arise by using different scanners (inter-scanner biases), which need to be corrected before downstream analyses to facilitate replicable research and prevent spurious findings. While statistical harmonization methods such as ComBat have become popular in mitigating inter-scanner biases in neuroimaging, recent methodological advances have shown that harmonizing heterogeneous covariances results in higher data quality. In vertex-level cortical thickness data, heterogeneity in spatial autocorrelation is a critical factor that affects covariance heterogeneity. Our work proposes a new statistical harmonization method called spatial autocorrelation normalization (SAN) that preserves homogeneous covariance vertex-level cortical thickness data across different scanners. We use an explicit Gaussian process to characterize scanner-invariant and scanner-specific variations to reconstruct spatially homogeneous data across scanners. SAN is computationally feasible, and it easily allows the integration of existing harmonization methods. We demonstrate the utility of the proposed method using cortical thickness data from the Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) study. SAN is publicly available as an R package.
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Affiliation(s)
- Rongqian Zhang
- Department of Statistical SciencesUniversity of TorontoTorontoOntarioCanada
| | - Linxi Chen
- Department of Statistical SciencesUniversity of TorontoTorontoOntarioCanada
| | | | - Aristotle N. Voineskos
- Centre for Addiction and Mental HealthTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioCanada
| | - Jun Young Park
- Department of Statistical SciencesUniversity of TorontoTorontoOntarioCanada
- Department of PsychologyUniversity of TorontoTorontoOntarioCanada
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Benavidez SM, Abaryan Z, Kim GS, Laltoo E, McCracken JT, Thompson PM, Lawrence KE. Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.02.578712. [PMID: 38352346 PMCID: PMC10862784 DOI: 10.1101/2024.02.02.578712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.
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Affiliation(s)
- Sebastian M Benavidez
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA
| | - Zvart Abaryan
- Children's Hospital of Los Angeles, Los Angeles, CA, USA
| | - Gaon S Kim
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA
| | - Emily Laltoo
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA
| | - James T McCracken
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA
| | - Katherine E Lawrence
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA
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McGhee CA, Honari H, Siqueiros-Sanchez M, Serur Y, van Staalduinen EK, Stevenson D, Bruno JL, Raman MM, Green T. RASopathies influences on neuroanatomical variation in children. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00103-4. [PMID: 38621478 DOI: 10.1016/j.bpsc.2024.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 03/09/2024] [Accepted: 04/04/2024] [Indexed: 04/17/2024]
Abstract
BACKGROUND RASopathies are a group of disorders characterized by pathogenic mutations in the Ras-mitogen-activated protein kinase (Ras/MAPK) signaling pathway. Distinct pathogenic variants in genes encoding proteins in the Ras/MAPK pathway cause Noonan syndrome (NS) and neurofibromatosis type 1 (NF1), which are associated with increased risk for autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD). METHODS This study examines the effect RASopathies (NS and NF1) has on human neuroanatomy, specifically on surface area (SA), cortical thickness (CT), and subcortical volumes. We compared structural T1-weighted images, using vertex-based analysis for cortical measures and Desikan ROI parcellation for subcortical volumes on children with RASopathies (n=91, mean age = 8.81, SD = 2.12) to sex- and age-matched TD (n=74, mean age=9.07, SD = 1.77). RESULTS Compared to TD, RASopathies had convergent effects on SA and CT, exhibiting increased SA in the precentral gyrus, decreased SA in occipital regions, and thinner CT in the precentral gyrus. RASopathies exhibit divergent effects on subcortical volumes, with syndrome-specific influences from NS and NF1. Overall children with NS display decreased volumes in striatal and thalamic structures and children with NF1 display increased volumes in the hippocampus, amygdala, and thalamus. CONCLUSIONS Our study reveals the converging and diverging neuroanatomical effects of RASopathies on human neurodevelopment. The convergence of cortical effects on SA and CT indicates a shared influence of Ras/MAPK hyperactivation on the human brain. Therefore, considering these measures as objective outcome indicators for targeted treatments is imperative.
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Affiliation(s)
| | | | | | - Yaffa Serur
- Department of Psychiatry & Behavioral Sciences
| | | | | | | | | | - Tamar Green
- Department of Psychiatry & Behavioral Sciences
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4
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Quidé Y, Watkeys OJ, Tonini E, Grotegerd D, Dannlowski U, Nenadić I, Kircher T, Krug A, Hahn T, Meinert S, Goltermann J, Gruber M, Stein F, Brosch K, Wroblewski A, Thomas-Odenthal F, Usemann P, Straube B, Alexander N, Leehr EJ, Bauer J, Winter NR, Fisch L, Dohm K, Rössler W, Smigielski L, DeRosse P, Moyett A, Houenou J, Leboyer M, Gilleen J, Thomopoulos SI, Thompson PM, Aleman A, Modinos G, Green MJ. Childhood trauma moderates schizotypy-related brain morphology: analyses of 1182 healthy individuals from the ENIGMA schizotypy working group. Psychol Med 2024; 54:1215-1227. [PMID: 37859592 DOI: 10.1017/s0033291723003045] [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] [Indexed: 10/21/2023]
Abstract
BACKGROUND Schizotypy represents an index of psychosis-proneness in the general population, often associated with childhood trauma exposure. Both schizotypy and childhood trauma are linked to structural brain alterations, and it is possible that trauma exposure moderates the extent of brain morphological differences associated with schizotypy. METHODS We addressed this question using data from a total of 1182 healthy adults (age range: 18-65 years old, 647 females/535 males), pooled from nine sites worldwide, contributing to the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Schizotypy working group. All participants completed both the Schizotypal Personality Questionnaire Brief version (SPQ-B), and the Childhood Trauma Questionnaire (CTQ), and underwent a 3D T1-weighted brain MRI scan from which regional indices of subcortical gray matter volume and cortical thickness were determined. RESULTS A series of multiple linear regressions revealed that differences in cortical thickness in four regions-of-interest were significantly associated with interactions between schizotypy and trauma; subsequent moderation analyses indicated that increasing levels of schizotypy were associated with thicker left caudal anterior cingulate gyrus, right middle temporal gyrus and insula, and thinner left caudal middle frontal gyrus, in people exposed to higher (but not low or average) levels of childhood trauma. This was found in the context of morphological changes directly associated with increasing levels of schizotypy or increasing levels of childhood trauma exposure. CONCLUSIONS These results suggest that alterations in brain regions critical for higher cognitive and integrative processes that are associated with schizotypy may be enhanced in individuals exposed to high levels of trauma.
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Affiliation(s)
- Yann Quidé
- NeuroRecovery Research Hub, School of Psychology, UNSW Sydney, Sydney, NSW, Australia
- Neuroscience Research Australia, Randwick, NSW, Australia
| | - Oliver J Watkeys
- Neuroscience Research Australia, Randwick, NSW, Australia
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Emiliana Tonini
- Neuroscience Research Australia, Randwick, NSW, Australia
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department for Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Nina Alexander
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Elisabeth J Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jochen Bauer
- Clinic for Radiology, University Hospital Münster, Münster, Germany
| | - Nils R Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lukas Fisch
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Wulf Rössler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
- Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, University of São Paulo, São Paulo, Brazil
| | - Lukasz Smigielski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Pamela DeRosse
- Department of Psychology, Stony Brook University, Stony Brook, NY, USA
| | - Ashley Moyett
- Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
| | - Josselin Houenou
- Université Paris Est Créteil, Mondor University Hospitals, DMU IMPACT, APHP, INSERM U955 Team "Translational NeuroPsychiatry", Créteil, France
- Fondation FondaMental, Créteil, France
- NeuroSpin neuroimaging platform, UNIACT Lab, PsyBrain team, CEA Saclay, Gif-Sur-Yvette, France
| | - Marion Leboyer
- Université Paris Est Créteil, Mondor University Hospitals, DMU IMPACT, APHP, INSERM U955 Team "Translational NeuroPsychiatry", Créteil, France
- Fondation FondaMental, Créteil, France
| | - James Gilleen
- Division of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- School of Psychology, University of Roehampton, London, UK
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - 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
| | - André Aleman
- Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Gemma Modinos
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Melissa J Green
- Neuroscience Research Australia, Randwick, NSW, Australia
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
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5
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Konttajärvi T, Haapea M, Huhtaniska S, Björnholm L, Miettunen J, Isohanni M, Penttilä M, Murray GK, Koponen H, Vernon AC, Jääskeläinen E, Lieslehto J. The contribution of first-episode illness characteristics and cumulative antipsychotic usage to progressive structural brain changes over a long-term follow-up in schizophrenia. Psychiatry Res Neuroimaging 2024; 339:111790. [PMID: 38354478 DOI: 10.1016/j.pscychresns.2024.111790] [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: 03/08/2023] [Revised: 11/26/2023] [Accepted: 01/08/2024] [Indexed: 02/16/2024]
Abstract
Exposure to antipsychotics as well as certain first-episode illness characteristics have been associated with greater gray matter (GM) deficits in the early phase of schizophrenia. Whether the first-episode illness characteristics affect the long-term progression of the structural brain changes remain unexplored. We therefore assessed the role of first-episode illness characteristics and life-time antipsychotic use in relation to long-term structural brain GM changes in schizophrenia. Individuals with schizophrenia (SZ, n = 29) and non-psychotic controls (n = 61) from the Northern Finland Birth Cohort 1966 underwent structural MRI at the ages of 34 (baseline) and 43 (follow-up) years. At follow-up, the average duration of illness was 19.8 years. Voxel-based morphometry was used to assess the effects of predictors on longitudinal GM changes in schizophrenia-relevant brain areas. Younger age of onset (AoO), higher cumulative antipsychotic dose and severity of symptoms were associated with greater GM deficits in the SZ group at follow-up. None of the first-episode illness characteristics were associated with longitudinal GM changes during 9-year follow-up period. We conclude that a younger AoO and high life-time antipsychotic use may contribute to progression of structural brain changes in schizophrenia. Apart from AoO, other first-episode illness characteristics may not contribute to longitudinal GM changes in midlife.
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Affiliation(s)
| | - Marianne Haapea
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Psychiatry, Oulu University of Hospital, Finland; Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Sanna Huhtaniska
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Lassi Björnholm
- Department of Psychiatry, Oulu University of Hospital, Finland; Research Unit of Clinical Neuroscience, University of Oulu, Finland
| | - Jouko Miettunen
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland
| | - Matti Isohanni
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Matti Penttilä
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Graham K Murray
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Hannu Koponen
- University of Helsinki, Helsinki University Hospital, Psychiatry, Helsinki, Finland
| | - Anthony C Vernon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London,United Kingdom
| | - Erika Jääskeläinen
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Psychiatry, Oulu University of Hospital, Finland
| | - Johannes Lieslehto
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland; Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, Stockholm, Sweden
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6
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Zhang R, Chen L, Oliver LD, Voineskos AN, Park JY. SAN: mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.04.569619. [PMID: 38105933 PMCID: PMC10723364 DOI: 10.1101/2023.12.04.569619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
In neuroimaging studies, combining data collected from multiple study sites or scanners is becoming common to increase the reproducibility of scientific discoveries. At the same time, unwanted variations arise by using different scanners (inter-scanner biases), which need to be corrected before downstream analyses to facilitate replicable research and prevent spurious findings. While statistical harmonization methods such as ComBat have become popular in mitigating inter-scanner biases in neuroimaging, recent methodological advances have shown that harmonizing heterogeneous covariances results in higher data quality. In vertex-level cortical thickness data, heterogeneity in spatial autocorrelation is a critical factor that affects covariance heterogeneity. Our work proposes a new statistical harmonization method called SAN (Spatial Autocorrelation Normalization) that preserves homogeneous covariance vertex-level cortical thickness data across different scanners. We use an explicit Gaussian process to characterize scanner-invariant and scanner-specific variations to reconstruct spatially homogeneous data across scanners. SAN is computationally feasible, and it easily allows the integration of existing harmonization methods. We demonstrate the utility of the proposed method using cortical thickness data from the Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) study. SAN is publicly available as an R package.
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Affiliation(s)
- Rongqian Zhang
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | - Linxi Chen
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | | | - Aristotle N. Voineskos
- Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Jun Young Park
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
- Department of Psychology, University of Toronto, Toronto, ON, Canada
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7
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Zhu AH, Nir TM, Javid S, Villalon-Reina JE, Rodrigue AL, Strike LT, de Zubicaray GI, McMahon KL, Wright MJ, Medland SE, Blangero J, Glahn DC, Kochunov P, Håberg AK, Thompson PM, Jahanshad N. Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.22.581646. [PMID: 38463962 PMCID: PMC10925090 DOI: 10.1101/2024.02.22.581646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Age-related white matter (WM) microstructure maturation and decline occur throughout the human lifespan, complementing the process of gray matter development and degeneration. Here, we create normative lifespan reference curves for global and regional WM microstructure by harmonizing diffusion MRI (dMRI)-derived data from ten public datasets (N = 40,898 subjects; age: 3-95 years; 47.6% male). We tested three harmonization methods on regional diffusion tensor imaging (DTI) based fractional anisotropy (FA), a metric of WM microstructure, extracted using the ENIGMA-DTI pipeline. ComBat-GAM harmonization provided multi-study trajectories most consistent with known WM maturation peaks. Lifespan FA reference curves were validated with test-retest data and used to assess the effect of the ApoE4 risk factor for dementia in WM across the lifespan. We found significant associations between ApoE4 and FA in WM regions associated with neurodegenerative disease even in healthy individuals across the lifespan, with regional age-by-genotype interactions. Our lifespan reference curves and tools to harmonize new dMRI data to the curves are publicly available as eHarmonize (https://github.com/ahzhu/eharmonize).
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Affiliation(s)
- Alyssa H Zhu
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
| | - Talia M Nir
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Shayan Javid
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
| | - Julio E Villalon-Reina
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Amanda L Rodrigue
- Department of Psychiatry and Behavioral Science, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lachlan T Strike
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Queensland University of Technology, Brisbane, QLD, Australia
| | | | - Katie L McMahon
- Queensland University of Technology, Brisbane, QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Queensland University of Technology, Brisbane, QLD, Australia
- School of Psychology, `, Brisbane, QLD, Australia
| | - John Blangero
- Department of Human Genetics, University of Texas Rio Grande Valley, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - David C Glahn
- Department of Psychiatry and Behavioral Science, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - Peter Kochunov
- Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of MiDtT National Research Center, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Paul M Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA, USA
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8
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Petzold J, Pochon JBF, Ghahremani DG, London ED. Structural indices of brain aging in methamphetamine use disorder. Drug Alcohol Depend 2024; 256:111107. [PMID: 38330525 DOI: 10.1016/j.drugalcdep.2024.111107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 01/01/2024] [Accepted: 01/17/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Methamphetamine use is surging globally. It has been linked to premature stroke, Parkinsonism, and dementia, suggesting that it may accelerate brain aging. METHODS We performed a retrospective study to determine if structural indices of brain aging were more prevalent prior to old age (26 - 54 years) in individuals with Methamphetamine Use Disorder (MUD), who were in early abstinence (M ± SD = 22.1 ± 25.6 days) than in healthy control (HC) participants. We compared T1-weighted MRI brain scans in age- and sex-matched groups (n = 89/group) on three structural features of brain aging: the brain volume/cerebrospinal fluid (BV/CSF) index, volume of white matter hypointensities/lesions, and choroid plexus volume. RESULTS The MUD group had a lower mean BV/CSF index and larger volumes of white matter hypointensities and choroid plexus (p-values < 0.01). Regression analyses showed significant age-by-group effects, indicating different age trajectories of the BV/CSF index and choroid plexus volume, consistent with abnormal global brain atrophy and choroid plexus pathology in the MUD group. Significant age and group main effects reflected a larger volume of white matter hypointensities for older participants across groups and for the MUD group irrespective of age. None of the three measures of brain aging correlated significantly with recent use or duration of recent abstinence from methamphetamine. CONCLUSIONS Premature brain pathology, which may reflect cerebrovascular damage and dysfunction of the choroid plexus, occurs in people with MUD. Such pathology may affect cognition and thereby efficacy of behavioral treatments for MUD.
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Affiliation(s)
- Johannes Petzold
- Jane and Terry Semel Institute of Neuroscience and Human Behavior, and Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA; Department of Psychiatry and Psychotherapy, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Jean-Baptiste F Pochon
- Jane and Terry Semel Institute of Neuroscience and Human Behavior, and Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA
| | - Dara G Ghahremani
- Jane and Terry Semel Institute of Neuroscience and Human Behavior, and Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA
| | - Edythe D London
- Jane and Terry Semel Institute of Neuroscience and Human Behavior, and Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA; The Brain Research Institute, University of California at Los Angeles, Los Angeles, CA, USA; Department of Molecular and Medical Pharmacology, University of California at Los Angeles, Los Angeles, CA, USA.
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9
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Moradi E, Prakash M, Hall A, Solomon A, Strange B, Tohka J. Machine learning prediction of future amyloid beta positivity in amyloid-negative individuals. Alzheimers Res Ther 2024; 16:46. [PMID: 38414035 PMCID: PMC10900722 DOI: 10.1186/s13195-024-01415-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 02/11/2024] [Indexed: 02/29/2024]
Abstract
BACKGROUND The pathophysiology of Alzheimer's disease (AD) involves β -amyloid (A β ) accumulation. Early identification of individuals with abnormal β -amyloid levels is crucial, but A β quantification with positron emission tomography (PET) and cerebrospinal fluid (CSF) is invasive and expensive. METHODS We propose a machine learning framework using standard non-invasive (MRI, demographics, APOE, neuropsychology) measures to predict future A β -positivity in A β -negative individuals. We separately study A β -positivity defined by PET and CSF. RESULTS Cross-validated AUC for 4-year A β conversion prediction was 0.78 for the CSF-based and 0.68 for the PET-based A β definitions. Although not trained for the clinical status-change prediction, the CSF-based model excelled in predicting future mild cognitive impairment (MCI)/dementia conversion in cognitively normal/MCI individuals (AUCs, respectively, 0.76 and 0.89 with a separate dataset). CONCLUSION Standard measures have potential in detecting future A β -positivity and assessing conversion risk, even in cognitively normal individuals. The CSF-based definition led to better predictions than the PET-based definition.
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Affiliation(s)
- Elaheh Moradi
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70150, Finland.
| | - Mithilesh Prakash
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70150, Finland
| | - Anette Hall
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
- Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institute, Stockholm, Sweden
| | - Alina Solomon
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
- Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institute, Stockholm, Sweden
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
| | - Bryan Strange
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, IdISSC, Madrid, Spain
- Reina Sofia Centre for Alzheimer's Research, Madrid, Spain
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70150, Finland
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10
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Zhu Y, Maikusa N, Radua J, Sämann PG, Fusar-Poli P, Agartz I, Andreassen OA, Bachman P, Baeza I, Chen X, Choi S, Corcoran CM, Ebdrup BH, Fortea A, Garani RR, Glenthøj BY, Glenthøj LB, Haas SS, Hamilton HK, Hayes RA, He Y, Heekeren K, Kasai K, Katagiri N, Kim M, Kristensen TD, Kwon JS, Lawrie SM, Lebedeva I, Lee J, Loewy RL, Mathalon DH, McGuire P, Mizrahi R, Mizuno M, Møller P, Nemoto T, Nordholm D, Omelchenko MA, Raghava JM, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Smigielski L, Sugranyes G, Takahashi T, Tamnes CK, Tang J, Theodoridou A, Tomyshev AS, Uhlhaas PJ, Værnes TG, van Amelsvoort TAMJ, Waltz JA, Westlye LT, Zhou JH, Thompson PM, Hernaus D, Jalbrzikowski M, Koike S. Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk. Mol Psychiatry 2024:10.1038/s41380-024-02426-7. [PMID: 38332374 DOI: 10.1038/s41380-024-02426-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 12/22/2023] [Accepted: 01/08/2024] [Indexed: 02/10/2024]
Abstract
Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.
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Affiliation(s)
- Yinghan Zhu
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Norihide Maikusa
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Instituto de Salud Carlos III, Universitat de Barcelona, Barcelona, Spain
| | | | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Peter Bachman
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Xiaogang Chen
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, the Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Sunah Choi
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Cheryl M Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Mental Illness Research, Education, and Clinical Center, James J Peters VA Medical Center, New York City, NY, USA
| | - Bjørn H Ebdrup
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Adriana Fortea
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, Hospital Clinic Barcelona, Fundació Clínic Recerca Biomèdica, Universitat de Barcelona, Barcelona, Spain
| | - Ranjini Rg Garani
- Douglas Research Center; Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Birte Yding Glenthøj
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Louise Birkedal Glenthøj
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, University of Copenhagen Copenhagen, Copenhagen, Denmark
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Holly K Hamilton
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA
| | - Rebecca A Hayes
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Ying He
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, the Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Karsten Heekeren
- Department of Psychiatry and Psychotherapy I, LVR-Hospital Cologne, Cologne, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence at The University of Tokyo Institutes for Advanced Study (WPI-IRCN), The University of Tokyo, Tokyo, Japan
| | - Naoyuki Katagiri
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyok, Japan
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Tina D Kristensen
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | | | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russian Federation
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Daniel H Mathalon
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA
| | - Philip McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Romina Mizrahi
- Douglas Research Center; Department of Psychiatry, McGill University, Montreal, QC, Canada
| | | | - Paul Møller
- Department for Mental Health Research and Development, Division of Mental Health and Addiction, Vestre Viken Hospital Trust, Drammen, Norway
| | - Takahiro Nemoto
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyok, Japan
| | - Dorte Nordholm
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, University of Copenhagen Copenhagen, Copenhagen, Denmark
| | - Maria A Omelchenko
- Department of Youth Psychiatry, Mental Health Research Center, Moscow, Russian Federation
| | - Jayachandra M Raghava
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Physiology, Nuclear Medicine and PET, Functional Imaging, University of Copenhagen Copenhagen, Copenhagen, Denmark
| | - Jan I Røssberg
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Wulf Rössler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Dean F Salisbury
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Lukasz Smigielski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Christian K Tamnes
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Zhejiang, China
- Key Laboratory of Medical Neurobiology of Zhejiang Province, School of Medicine, Zhejiang University, Zhejiang, China
| | - Anastasia Theodoridou
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Alexander S Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russian Federation
| | - Peter J Uhlhaas
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin Berlin, Berlin, Germany
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Tor G Værnes
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Early Intervention in Psychosis Advisory Unit for South-East Norway, TIPS Sør-Øst, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Therese A M J van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - James A Waltz
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore County, Baltimore, MD, USA
| | - Lars T Westlye
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Juan H Zhou
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Dennis Hernaus
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Cambridge, MA, USA
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan.
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, The University of Tokyo, Tokyo, Japan.
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11
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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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12
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Yang J, Huggins AA, Sun D, Baird CL, Haswell CC, Frijling JL, Olff M, van Zuiden M, Koch SBJ, Nawijn L, Veltman DJ, Suarez-Jimenez B, Zhu X, Neria Y, Hudson AR, Mueller SC, Baker JT, Lebois LAM, Kaufman ML, Qi R, Lu GM, Říha P, Rektor I, Dennis EL, Ching CRK, Thomopoulos SI, Salminen LE, Jahanshad N, Thompson PM, Stein DJ, Koopowitz SM, Ipser JC, Seedat S, du Plessis S, van den Heuvel LL, Wang L, Zhu Y, Li G, Sierk A, Manthey A, Walter H, Daniels JK, Schmahl C, Herzog JI, Liberzon I, King A, Angstadt M, Davenport ND, Sponheim SR, Disner SG, Straube T, Hofmann D, Grupe DW, Nitschke JB, Davidson RJ, Larson CL, deRoon-Cassini TA, Blackford JU, Olatunji BO, Gordon EM, May G, Nelson SM, Abdallah CG, Levy I, Harpaz-Rotem I, Krystal JH, Morey RA, Sotiras A. Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods. Neuropsychopharmacology 2024; 49:609-619. [PMID: 38017161 PMCID: PMC10789873 DOI: 10.1038/s41386-023-01763-5] [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: 01/10/2023] [Revised: 10/02/2023] [Accepted: 10/23/2023] [Indexed: 11/30/2023]
Abstract
Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.
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Affiliation(s)
- Jin Yang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Ashley A Huggins
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Delin Sun
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
- Department of Psychology, The Education University of Hong Kong, Hong Kong, China
| | - C Lexi Baird
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Courtney C Haswell
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Jessie L Frijling
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Miranda Olff
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
- ARQ National Psychotrauma Centre, Diemen, The Netherlands
| | - Mirjam van Zuiden
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Saskia B J Koch
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Benjamin Suarez-Jimenez
- Del Monte Institute for Neuroscience, University of Rochester Medical Center, Rochester, NY, USA
| | - Xi Zhu
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Yuval Neria
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Anna R Hudson
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Sven C Mueller
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Justin T Baker
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Institute for Technology in Psychiatry, McLean Hospital, Harvard University, Belmont, MA, USA
| | - Lauren A M Lebois
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA
| | - Milissa L Kaufman
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Division of Women's Mental Health, McLean Hospital, Belmont, MA, USA
| | - Rongfeng Qi
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Jiangsu, China
| | - Guang Ming Lu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Jiangsu, China
| | - Pavel Říha
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
- CEITEC-Central European Institute of Technology, Multimodal and Functional Neuroimaging Research Group, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- CEITEC-Central European Institute of Technology, Multimodal and Functional Neuroimaging Research Group, Masaryk University, Brno, Czech Republic
| | - Emily L Dennis
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sheri M Koopowitz
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Jonathan C Ipser
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Soraya Seedat
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Stefan du Plessis
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | | | - Li Wang
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Ye Zhu
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Gen Li
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Anika Sierk
- University Medical Centre Charité, Berlin, Germany
| | | | | | - Judith K Daniels
- Department of Clinical Psychology, University of Groningen, Groningen, The Netherlands
| | - Christian Schmahl
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Julia I Herzog
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Israel Liberzon
- Department of Psychiatry and Behavioral Science, Texas A&M University, College Station, TX, USA
| | - Anthony King
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Mike Angstadt
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas D Davenport
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Seth G Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - David Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Daniel W Grupe
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
| | - Jack B Nitschke
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Richard J Davidson
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Christine L Larson
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Terri A deRoon-Cassini
- Division of Trauma and Acute Care Surgery, Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
- Comprehensive Injury Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Jennifer U Blackford
- Munroe-Meyer Institute, University of Nebraska Medical Center, Omaha, NE, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bunmi O Olatunji
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Evan M Gordon
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Geoffrey May
- Veterans Integrated Service Network-17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA
- Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
- Department of Psychiatry and Behavioral Science, Texas A&M University Health Science Center, Bryan, TX, USA
| | - Steven M Nelson
- Veterans Integrated Service Network-17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA
- Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
- Department of Psychiatry and Behavioral Science, Texas A&M University Health Science Center, Bryan, TX, USA
| | - Chadi G Abdallah
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry of Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ifat Levy
- Department of Comparative Medicine, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA
| | - Ilan Harpaz-Rotem
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA
| | - John H Krystal
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA
| | - Rajendra A Morey
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA.
| | - Aristeidis Sotiras
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Institute for Informatics, Data Science & Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
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13
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Zhang Y, Xie R, Beheshti I, Liu X, Zheng G, Wang Y, Zhang Z, Zheng W, Yao Z, Hu B. Improving brain age prediction with anatomical feature attention-enhanced 3D-CNN. Comput Biol Med 2024; 169:107873. [PMID: 38181606 DOI: 10.1016/j.compbiomed.2023.107873] [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: 03/31/2023] [Revised: 11/17/2023] [Accepted: 12/17/2023] [Indexed: 01/07/2024]
Abstract
Currently, significant progress has been made in predicting brain age from structural Magnetic Resonance Imaging (sMRI) data using deep learning techniques. However, despite the valuable structural information they contain, the traditional engineering features known as anatomical features have been largely overlooked in this context. To address this issue, we propose an attention-based network design that integrates anatomical and deep convolutional features, leveraging an anatomical feature attention (AFA) module to effectively capture salient anatomical features. In addition, we introduce a fully convolutional network, which simplifies the extraction of deep convolutional features and overcomes the high computational memory requirements associated with deep learning. Our approach outperforms several widely-used models on eight publicly available datasets (n = 2501), with a mean absolute error (MAE) of 2.20 years in predicting brain age. Comparisons with deep learning models lacking the AFA module demonstrate that our fusion model effectively improves overall performance. These findings provide a promising approach for combining anatomical and deep convolutional features from sMRI data to predict brain age, with potential applications in clinical diagnosis and treatment, particularly for populations with age-related cognitive decline or neurological disorders.
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Affiliation(s)
- Yu Zhang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Rui Xie
- Department of Psychiatric, Tianshui Third People's Hospital, Tianshui, 741000, China
| | - Iman Beheshti
- Department of Human Anatomy and Cell Science, University of Manitoba, Canada
| | - Xia Liu
- School of Computer Science, Qinghai Normal University, Xining, Qinghai Province, China
| | - Guowei Zheng
- School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China
| | - Yin Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Zhenwen Zhang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China.
| | - Zhijun Yao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China.
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China; School of Medical Technology, Beijing Institute of Technology, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China; Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors, Chinese Academy of Sciences, China.
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14
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Marzi C, Giannelli M, Barucci A, Tessa C, Mascalchi M, Diciotti S. Efficacy of MRI data harmonization in the age of machine learning: a multicenter study across 36 datasets. Sci Data 2024; 11:115. [PMID: 38263181 PMCID: PMC10805868 DOI: 10.1038/s41597-023-02421-7] [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: 12/06/2022] [Accepted: 07/27/2023] [Indexed: 01/25/2024] Open
Abstract
Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups of subjects, increase statistical power, and promote data reuse with machine learning techniques. The harmonization of multicenter data is necessary to reduce the confounding effect associated with non-biological sources of variability in the data. However, when applied to the entire dataset before machine learning, the harmonization leads to data leakage, because information outside the training set may affect model building, and potentially falsely overestimate performance. We propose a 1) measurement of the efficacy of data harmonization; 2) harmonizer transformer, i.e., an implementation of the ComBat harmonization allowing its encapsulation among the preprocessing steps of a machine learning pipeline, avoiding data leakage by design. We tested these tools using brain T1-weighted MRI data from 1740 healthy subjects acquired at 36 sites. After harmonization, the site effect was removed or reduced, and we showed the data leakage effect in predicting individual age from MRI data, highlighting that introducing the harmonizer transformer into a machine learning pipeline allows for avoiding data leakage by design.
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Affiliation(s)
- Chiara Marzi
- Department of Statistics, Computer Science and Applications "Giuseppe Parenti", University of Florence, 50134, Florence, Italy
- "Nello Carrara" Institute of Applied Physics (IFAC), National Research Council (CNR), 50019, Sesto Fiorentino, Florence, Italy
| | - Marco Giannelli
- Unit of Medical Physics, Pisa University Hospital "Azienda Ospedaliero-Universitaria Pisana", 56126, Pisa, Italy
| | - Andrea Barucci
- "Nello Carrara" Institute of Applied Physics (IFAC), National Research Council (CNR), 50019, Sesto Fiorentino, Florence, Italy
| | - Carlo Tessa
- Radiology Unit Apuane e Lunigiana, Azienda USL Toscana Nord Ovest, 54100, Massa, Italy
| | - Mario Mascalchi
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, 50139, Florence, Italy
- Division of Epidemiology and Clinical Governance, Institute for Study, Prevention and netwoRk in Oncology (ISPRO), 50139, Florence, Italy
| | - Stefano Diciotti
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" - DEI, University of Bologna, 47522, Cesena, Italy.
- Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, 40121, Bologna, Italy.
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15
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Boen R, Kaufmann T, van der Meer D, Frei O, Agartz I, Ames D, Andersson M, Armstrong NJ, Artiges E, Atkins JR, Bauer J, Benedetti F, Boomsma DI, Brodaty H, Brosch K, Buckner RL, Cairns MJ, Calhoun V, Caspers S, Cichon S, Corvin AP, Crespo-Facorro B, Dannlowski U, David FS, de Geus EJC, de Zubicaray GI, Desrivières S, Doherty JL, Donohoe G, Ehrlich S, Eising E, Espeseth T, Fisher SE, Forstner AJ, Fortaner-Uyà L, Frouin V, Fukunaga M, Ge T, Glahn DC, Goltermann J, Grabe HJ, Green MJ, Groenewold NA, Grotegerd D, Grøntvedt GR, Hahn T, Hashimoto R, Hehir-Kwa JY, Henskens FA, Holmes AJ, Håberg AK, Haavik J, Jacquemont S, Jansen A, Jockwitz C, Jönsson EG, Kikuchi M, Kircher T, Kumar K, Le Hellard S, Leu C, Linden DE, Liu J, Loughnan R, Mather KA, McMahon KL, McRae AF, Medland SE, Meinert S, Moreau CA, Morris DW, Mowry BJ, Mühleisen TW, Nenadić I, Nöthen MM, Nyberg L, Ophoff RA, Owen MJ, Pantelis C, Paolini M, Paus T, Pausova Z, Persson K, Quidé Y, Marques TR, Sachdev PS, Sando SB, Schall U, Scott RJ, Selbæk G, Shumskaya E, Silva AI, Sisodiya SM, Stein F, Stein DJ, Straube B, Streit F, Strike LT, Teumer A, Teutenberg L, Thalamuthu A, Tooney PA, Tordesillas-Gutierrez D, Trollor JN, van 't Ent D, van den Bree MBM, van Haren NEM, Vázquez-Bourgon J, Völzke H, Wen W, Wittfeld K, Ching CRK, Westlye LT, Thompson PM, Bearden CE, Selmer KK, Alnæs D, Andreassen OA, Sønderby IE. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers. Biol Psychiatry 2024; 95:147-160. [PMID: 37661008 PMCID: PMC7615370 DOI: 10.1016/j.biopsych.2023.08.018] [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: 04/11/2023] [Revised: 07/25/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
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Affiliation(s)
- Rune Boen
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Germany; German Center for Mental Health (DZPG), partner site Tübingen, Tübingen, Germany
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Research, Diakonhjemmet Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - David Ames
- University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, Victoria, Australia; National Ageing Research Institute, Parkville, Victoria, Australia
| | - Micael Andersson
- Department of Integrative Medical Biology and Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Curtin University, Perth, Western Australia, Australia
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale U1299, École Normale Supérieure Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France; Établissement public de santé (EPS) Barthélemy Durand, Etampes, France
| | - Joshua R Atkins
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jochen Bauer
- University Clinic for Radiology, University of Münster, Münster, Germany
| | - Francesco Benedetti
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Randy L Buckner
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University/Georgia Institute of Technology/Emory University, Atlanta, Georgia
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sven Cichon
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland; University Hospital Basel, Institute of Medical Genetics and Pathology, Basel, Switzerland
| | - Aiden P Corvin
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Benedicto Crespo-Facorro
- Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/Centro superior de investigaciones científicas (CSIC), Sevilla, Spain; Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University of Sevilla, Sevilla, Spain
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Friederike S David
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Greig I de Zubicaray
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Sylvane Desrivières
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Joanne L Doherty
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Gary Donohoe
- School of Psychology and Center for Neuroimaging, Cognition and Genomics, University of Galway, Galway, Ireland
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Else Eising
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Thomas Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway; Department of Psychology, Oslo New University College, Oslo, Norway
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Andreas J Forstner
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Lidia Fortaner-Uyà
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Vincent Frouin
- Neurospin, Commissariat a l'Energie Atomique (CEA), Université Paris-Saclay, Gif-sur-Yvette, France
| | - Masaki Fukunaga
- Section of Brain Function Information, National Institute for Physiological Sciences, Okazaki, Japan
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - David C Glahn
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Melissa J Green
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia; Neuroscience Research Australia, Sydney, New South Wales, Australia
| | - Nynke A Groenewold
- Department of Psychiatry and Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Gøril Rolfseng Grøntvedt
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Jayne Y Hehir-Kwa
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Frans A Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia; Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, New South Wales, Australia
| | - Avram J Holmes
- Department of Psychiatry, Rutgers University, New Brunswick, New Jersey; Brain Health Institute, Rutgers University, Piscataway, New Jersey
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology and Nuclear Medicine, St. Olav's Hospital, Trondheim, Norway
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Sebastien Jacquemont
- Sainte Justine Hospital Research Center, Montreal, Quebec, Canada; Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany; Core-Facility Brainimaging and Department of Psychiatry, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Erik G Jönsson
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Masataka Kikuchi
- Department of Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Kuldeep Kumar
- Sainte Justine Hospital Research Center, Montreal, Quebec, Canada
| | - Stephanie Le Hellard
- Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Costin Leu
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Department of Neurology, McGovern Medical School, UTHealth Houston, Houston, Texas
| | - David E Linden
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Jingyu Liu
- Department of Computer Science and Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, Georgia
| | - Robert Loughnan
- Department of Cognitive Science and Population Neuroscience and Genetics Lab, University of California San Diego, La Jolla, California
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Sarah E Medland
- Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Brisbane, Queensland, Australia; University of Queensland, Brisbane, Queensland, Australia; Queensland University of Technology, Brisbane, Queensland, Australia
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany; Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Clara A Moreau
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics, School of Biological and Chemical Sciences, University of Galway, Galway, Ireland
| | - Bryan J Mowry
- Queensland Brain Institute and Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia
| | - Thomas W Mühleisen
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Lars Nyberg
- Departments of Radiation Sciences, Integrative Medical Biology and Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Roel A Ophoff
- Department of Psychiatry, Erasmus University Medical Center, Rotterdam, the Netherlands; Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, Los Angeles, California
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Carlton South, Victoria, Australia; Western Centre for Health Research and Education, Sunshine Hospital, St Albans, Victoria, Australia
| | - Marco Paolini
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Tomas Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Sainte Justine Hospital Research Center, University of Montreal, Montreal, Quebec, Canada; Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Karin Persson
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Yann Quidé
- Neuroscience Research Australia, Sydney, New South Wales, Australia; School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Tiago Reis Marques
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Sigrid B Sando
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Division of Molecular Medicine, New South Wales Health Pathology, Newcastle, New South Wales, Australia
| | - Geir Selbæk
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Elena Shumskaya
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands; Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ana I Silva
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Dan J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lachlan T Strike
- Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Brisbane, Queensland, Australia; School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Brisbane, Australia
| | - Alexander Teumer
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research, Greifswald, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Paul A Tooney
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Diana Tordesillas-Gutierrez
- Instituto de Física de Cantabria UC-CSIC, Santander, Spain; Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain
| | - Julian N Trollor
- Department of Developmental Disability Neuropsychiatry and Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Marianne B M van den Bree
- Institute of Psychological Medicine and Clinical Neurosciences and Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, the Netherlands; Department of Psychiatry, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Javier Vázquez-Bourgon
- Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University Hospital Maqués de Valdecilla, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain; Departamento de Medicina y Psiquiatría, Universidad de Cantabria, Santander, Spain
| | - Henry Völzke
- German Centre for Cardiovascular Research, Greifswald, Germany; Greifswald University Hospital, Greifswald, Germany
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, Los Angeles, California
| | - Kaja K Selmer
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital and the University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Kristiania University College, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ida E Sønderby
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
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16
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Suarez-Jimenez B, Lazarov A, Zhu X, Zilcha-Mano S, Kim Y, Marino CE, Rjabtsenkov P, Bavdekar SY, Pine DS, Bar-Haim Y, Larson CL, Huggins AA, Terri deRoon-Cassini, Tomas C, Fitzgerald J, Kennis M, Varkevisser T, Geuze E, Quidé Y, El Hage W, Wang X, O’Leary EN, Cotton AS, Xie H, Shih C, Disner SG, Davenport ND, Sponheim SR, Koch SB, Frijling JL, Nawijn L, van Zuiden M, Olff M, Veltman DJ, Gordon EM, May G, Nelson SM, Jia-Richards M, Neria Y, Morey RA. Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:299-307. [PMID: 38298781 PMCID: PMC10829610 DOI: 10.1016/j.bpsgos.2023.05.006] [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: 11/28/2022] [Revised: 04/12/2023] [Accepted: 05/22/2023] [Indexed: 02/02/2024] Open
Abstract
Background Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n= 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.
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Affiliation(s)
- Benjamin Suarez-Jimenez
- Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York
| | - Amit Lazarov
- Department of Clinical Psychology, School of Psychological Sciences, Tel-Aviv University, Tel-Aviv, Israel
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York
| | - Xi Zhu
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York
| | - Sigal Zilcha-Mano
- Department of Psychology, University of Haifa, Mount Carmel, Haifa, Israel
| | - Yoojean Kim
- Department of Psychiatry, New York State Psychiatric Institute, New York, New York
| | - Claire E. Marino
- Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York
| | - Pavel Rjabtsenkov
- Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York
| | - Shreya Y. Bavdekar
- Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York
| | - Daniel S. Pine
- Section on Developmental Affective Neuroscience, National Institute of Mental Health, Bethesda, Maryland
| | - Yair Bar-Haim
- Department of Clinical Psychology, School of Psychological Sciences, Tel-Aviv University, Tel-Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | | | | | | | | | | | - Mitzy Kennis
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, the Netherlands
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Tim Varkevisser
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, the Netherlands
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Elbert Geuze
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, the Netherlands
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Yann Quidé
- School of Psychology, University of New South Wales Sydney, Sydney, New South Wales, Australia
- Neuroscience Research Australia, Randwick, New South Wales, Australia
| | - Wissam El Hage
- Unité Mixte de Recherche 1253, Institut National de la Santé et de la Recherche Médicale, Université de Tours, Tours, France
- Centre d'investigation Clinique 1415, Institut National de la Santé et de la Recherche Médicale, Centre Hospitalier Régional Universitaire de Tours, Tours, France
| | - Xin Wang
- University of Toledo, Toledo, Ohio
| | | | | | - Hong Xie
- University of Toledo, Toledo, Ohio
| | | | - Seth G. Disner
- Minneapolis VA Health Care System, Minneapolis, Minnesota
| | | | | | - Saskia B.J. Koch
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands
| | - Jessie L. Frijling
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Mirjam van Zuiden
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
| | - Miranda Olff
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- ARQ National Psychotrauma Centre, Diemen, the Netherlands
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Evan M. Gordon
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri
| | - Geoffery May
- VISN 17 Center of Excellence for Research on Returning War Veterans, U.S. Department of Veterans Affairs, Waco, Texas
| | - Steven M. Nelson
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota
| | | | - Yuval Neria
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York
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Cao Z, McCabe M, Callas P, Cupertino RB, Ottino-González J, Murphy A, Pancholi D, Schwab N, Catherine O, Hutchison K, Cousijn J, Dagher A, Foxe JJ, Goudriaan AE, Hester R, Li CSR, Thompson WK, Morales AM, London ED, Lorenzetti V, Luijten M, Martin-Santos R, Momenan R, Paulus MP, Schmaal L, Sinha R, Solowij N, Stein DJ, Stein EA, Uhlmann A, van Holst RJ, Veltman DJ, Wiers RW, Yücel M, Zhang S, Conrod P, Mackey S, Garavan H. Recalibrating single-study effect sizes using hierarchical Bayesian models. FRONTIERS IN NEUROIMAGING 2023; 2:1138193. [PMID: 38179200 PMCID: PMC10764546 DOI: 10.3389/fnimg.2023.1138193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 11/27/2023] [Indexed: 01/06/2024]
Abstract
Introduction There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance. Methods We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method. Results The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. Discussion Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.
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Affiliation(s)
- Zhipeng Cao
- Shanghai Xuhui Mental Health Center, Shanghai, China
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Matthew McCabe
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Peter Callas
- Department of Mathematics and Statistics, University of Vermont College of Engineering and Mathematical Sciences, Burlington, VT, United States
| | - Renata B. Cupertino
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Jonatan Ottino-González
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Alistair Murphy
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Devarshi Pancholi
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Nathan Schwab
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Orr Catherine
- Department of Psychological Sciences, School of Health Sciences, Swinburne University, Melbourne, VIC, Australia
| | - Kent Hutchison
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, United States
| | - Janna Cousijn
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - Alain Dagher
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - John J. Foxe
- Department of Neuroscience, The Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Anna E. Goudriaan
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Robert Hester
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Chiang-Shan R. Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | | | - Angelica M. Morales
- Department of Psychiatry at Oregon Health and Science University, Portland, OR, United States
| | - Edythe D. London
- David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, United States
| | - Valentina Lorenzetti
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural & Health Sciences, Faculty of Health Sciences, Australian Catholic University, Australia
| | - Maartje Luijten
- Behavioural Science Institute, Radboud University, Nijmegen, Netherlands
| | - Rocio Martin-Santos
- Department of Psychiatry and Psychology, University of Barcelona, Barcelona, Spain
| | - Reza Momenan
- Clinical NeuroImaging Research Core, Division of Intramural Clinical and Biological Research, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, United States
| | - Martin P. Paulus
- Laureate Institute for Brain Research, Tulsa, OK, United States
- VA San Diego Healthcare System and Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Lianne Schmaal
- Orygen, Parkville, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Rajita Sinha
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Nadia Solowij
- School of Psychology and Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia
| | - Dan J. Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Elliot A. Stein
- Neuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD, United States
| | - Anne Uhlmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Ruth J. van Holst
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Reinout W. Wiers
- Addiction Development and Psychopathology (ADAPT)-Lab, Department of Psychology and Center for Urban Mental Health, University of Amsterdam, Amsterdam, Netherlands
| | - Murat Yücel
- BrainPark, Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging Facility, Monash University, Melbourne, VIC, Australia
| | - Sheng Zhang
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Patricia Conrod
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, QC, Canada
| | - Scott Mackey
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States
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18
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Zhu X, Kim Y, Ravid O, He X, Suarez-Jimenez B, Zilcha-Mano S, Lazarov A, Lee S, Abdallah CG, Angstadt M, Averill CL, Baird CL, Baugh LA, Blackford JU, Bomyea J, Bruce SE, Bryant RA, Cao Z, Choi K, Cisler J, Cotton AS, Daniels JK, Davenport ND, Davidson RJ, DeBellis MD, Dennis EL, Densmore M, deRoon-Cassini T, Disner SG, Hage WE, Etkin A, Fani N, Fercho KA, Fitzgerald J, Forster GL, Frijling JL, Geuze E, Gonenc A, Gordon EM, Gruber S, Grupe DW, Guenette JP, Haswell CC, Herringa RJ, Herzog J, Hofmann DB, Hosseini B, Hudson AR, Huggins AA, Ipser JC, Jahanshad N, Jia-Richards M, Jovanovic T, Kaufman ML, Kennis M, King A, Kinzel P, Koch SBJ, Koerte IK, Koopowitz SM, Korgaonkar MS, Krystal JH, Lanius R, Larson CL, Lebois LAM, Li G, Liberzon I, Lu GM, Luo Y, Magnotta VA, Manthey A, Maron-Katz A, May G, McLaughlin K, Mueller SC, Nawijn L, Nelson SM, Neufeld RWJ, Nitschke JB, O'Leary EM, Olatunji BO, Olff M, Peverill M, Phan KL, Qi R, Quidé Y, Rektor I, Ressler K, Riha P, Ross M, Rosso IM, Salminen LE, Sambrook K, Schmahl C, Shenton ME, Sheridan M, Shih C, Sicorello M, Sierk A, Simmons AN, Simons RM, Simons JS, Sponheim SR, Stein MB, Stein DJ, Stevens JS, Straube T, Sun D, Théberge J, Thompson PM, Thomopoulos SI, van der Wee NJA, van der Werff SJA, van Erp TGM, van Rooij SJH, van Zuiden M, Varkevisser T, Veltman DJ, Vermeiren RRJM, Walter H, Wang L, Wang X, Weis C, Winternitz S, Xie H, Zhu Y, Wall M, Neria Y, Morey RA. Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium. Neuroimage 2023; 283:120412. [PMID: 37858907 PMCID: PMC10842116 DOI: 10.1016/j.neuroimage.2023.120412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 09/10/2023] [Accepted: 10/16/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.
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Affiliation(s)
- Xi Zhu
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA
| | - Yoojean Kim
- New York State Psychiatric Institute, New York, NY, USA
| | - Orren Ravid
- New York State Psychiatric Institute, New York, NY, USA
| | - Xiaofu He
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
| | | | | | | | - Seonjoo Lee
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA
| | - Chadi G Abdallah
- Baylor College of Medicine, Houston, TX, USA; Yale University School of Medicine, New Haven, CT, USA
| | | | - Christopher L Averill
- Baylor College of Medicine, Houston, TX, USA; Yale University School of Medicine, New Haven, CT, USA
| | | | - Lee A Baugh
- Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA
| | | | | | - Steven E Bruce
- Center for Trauma Recovery, Department of Psychological Sciences, University of Missouri-St. Louis, St. Louis, MO, USA
| | - Richard A Bryant
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Zhihong Cao
- Department of Radiology, The Affiliated Yixing Hospital of Jiangsu University, Yixing, Jiangsu, China
| | - Kyle Choi
- University of California San Diego, La Jolla, CA, USA
| | - Josh Cisler
- Department of Psychiatry, University of Texas at Austin, Austin, TX, USA
| | | | | | | | | | | | - Emily L Dennis
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Maria Densmore
- Departments of Psychology and Psychiatry, Neuroscience Program, Western University, London, ON, Canada; Department of Psychology, University of British Columbia, Okanagan, Kelowna, British Columbia, Canada
| | | | - Seth G Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA
| | - Wissam El Hage
- UMR 1253, CIC 1415, University of Tours, CHRU de Tours, INSERM, France
| | | | - Negar Fani
- Emory University Department of Psychiatry and Behavioral Sciences, Atlanta, GA, USA
| | - Kelene A Fercho
- Civil Aerospace Medical Institute, US Federal Aviation Administration, Oklahoma City, OK, USA
| | | | - Gina L Forster
- Brain Health Research Centre, Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - Jessie L Frijling
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Elbert Geuze
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, The Netherlands
| | - Atilla Gonenc
- Cognitive and Clinical Neuroimaging Core, McLean Hospital, Belmont, MA, USA
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Staci Gruber
- Cognitive and Clinical Neuroimaging Core, McLean Hospital, Belmont, MA, USA
| | | | - Jeffrey P Guenette
- Division of Neuroradiology, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Ryan J Herringa
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | | | | | | | | | | | | | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | | | | | - Milissa L Kaufman
- Division of Women's Mental Health, McLean Hospital, Belmont, MA, USA
| | - Mitzy Kennis
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, The Netherlands
| | | | - Philipp Kinzel
- Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig Maximilian University of Munich, Munich, Germany; Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
| | - Saskia B J Koch
- Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Inga K Koerte
- Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig Maximilian University of Munich, Munich, Germany; Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
| | | | | | | | - Ruth Lanius
- Department of Neuroscience, Western University, London, ON, Canada
| | | | - Lauren A M Lebois
- McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Gen Li
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Israel Liberzon
- Psychiatry and Behavioral Science, Texas A&M University Health Science Center, College Station, TX, USA
| | - Guang Ming Lu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Yifeng Luo
- Department of Radiology, The Affiliated Yixing Hospital of Jiangsu University, Yixing, Jiangsu, China
| | | | - Antje Manthey
- Charité Universitätsmedizin Berlin Campus Charite Mitte: Charite Universitatsmedizin Berlin, Berlin, Germany
| | | | - Geoffery May
- VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA
| | | | | | - Laura Nawijn
- Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, VU University, Amsterdam, The Netherlands
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Richard W J Neufeld
- Departments of Psychology and Psychiatry, Neuroscience Program, Western University, London, ON, Canada; Department of Psychology, University of British Columbia, Okanagan, Kelowna, British Columbia, Canada
| | | | | | - Bunmi O Olatunji
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Miranda Olff
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | | | - K Luan Phan
- Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH, USA
| | - Rongfeng Qi
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Yann Quidé
- School of Psychology, University of New South Wales, Sydney, NSW, Australia; Neuroscience Research Australia, Randwick, NSW, Australia
| | | | - Kerry Ressler
- McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | - Marisa Ross
- Northwestern Neighborhood and Networks Initiative, Northwestern University Institute for Policy Research, Evanston, IL, USA
| | - Isabelle M Rosso
- McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | | | | | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
| | | | | | | | - Anika Sierk
- Charité Universitätsmedizin Berlin Campus Charite Mitte: Charite Universitatsmedizin Berlin, Berlin, Germany
| | - Alan N Simmons
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | | | | | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA; University of Minnesota, Minneapolis, MN, USA
| | | | - Dan J Stein
- University of Cape Town, Cape Town, South Africa
| | - Jennifer S Stevens
- Emory University Department of Psychiatry and Behavioral Sciences, Atlanta, GA, USA
| | | | | | - Jean Théberge
- Departments of Psychology and Psychiatry, Neuroscience Program, Western University, London, ON, Canada; Department of Psychology, University of British Columbia, Okanagan, Kelowna, British Columbia, Canada
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | | | | | | | - Sanne J H van Rooij
- Emory University Department of Psychiatry and Behavioral Sciences, Atlanta, GA, USA
| | - Mirjam van Zuiden
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Tim Varkevisser
- Brain Research and Innovation Centre, Ministry of Defence, Utrecht, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, VU University, Amsterdam, The Netherlands
| | | | - Henrik Walter
- Charité Universitätsmedizin Berlin Campus Charite Mitte: Charite Universitatsmedizin Berlin, Berlin, Germany
| | - Li Wang
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Xin Wang
- University of Toledo, Toledo, OH, USA
| | - Carissa Weis
- Medical College of Wisconsin, Milwaukee, WI, USA
| | - Sherry Winternitz
- Division of Women's Mental Health, McLean Hospital, Belmont, MA, USA
| | - Hong Xie
- University of Toledo, Toledo, OH, USA
| | - Ye Zhu
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Melanie Wall
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA
| | - Yuval Neria
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
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19
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Radua J, Koutsouleris N. Ten Simple Rules for Using Machine Learning in Mental Health Research. Biol Psychiatry 2023:S0006-3223(23)01724-9. [PMID: 37981177 DOI: 10.1016/j.biopsych.2023.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/16/2023] [Accepted: 11/16/2023] [Indexed: 11/21/2023]
Affiliation(s)
- Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Instituto de Salud Carlos III, University of Barcelona, Barcelona, Spain.
| | - Nikolaos Koutsouleris
- Section of Precision Psychiatry, Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Max Planck Institute of Psychiatry, Munich, Germany
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20
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Martinez-Heras E, Solana E, Vivó F, Lopez-Soley E, Calvi A, Alba-Arbalat S, Schoonheim MM, Strijbis EM, Vrenken H, Barkhof F, Rocca MA, Filippi M, Pagani E, Groppa S, Fleischer V, Dineen RA, Bellenberg B, Lukas C, Pareto D, Rovira A, Sastre-Garriga J, Collorone S, Prados F, Toosy A, Ciccarelli O, Saiz A, Blanco Y, Llufriu S. Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes. J Neurol Neurosurg Psychiatry 2023; 94:916-923. [PMID: 37321841 DOI: 10.1136/jnnp-2023-331531] [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: 03/27/2023] [Accepted: 05/30/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes. METHODS Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups. RESULTS Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes. CONCLUSIONS In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor.
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Affiliation(s)
- Eloy Martinez-Heras
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Elisabeth Solana
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Francesc Vivó
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Elisabet Lopez-Soley
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Alberto Calvi
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Salut Alba-Arbalat
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Eva M Strijbis
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Hugo Vrenken
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Sergiu Groppa
- Department of Neurology, Neurostimulation and Neuroimaging, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Neurostimulation and Neuroimaging, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Robert A Dineen
- Mental Health and Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK; and NIHR Nottingham Biomedical Research Centre, Nottingham, UK
| | - Barbara Bellenberg
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St. Josef Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital and Research Institute (VHIR), Barcelona, Spain
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital and Research Institute (VHIR), Barcelona, Spain
| | - Jaume Sastre-Garriga
- Neurology-Neuroimmunology Department, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Sara Collorone
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, London, UK
| | - Ferran Prados
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
- E-health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Ahmed Toosy
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, London, UK
| | - Olga Ciccarelli
- Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, London, UK
| | - Albert Saiz
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Yolanda Blanco
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Sara Llufriu
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
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21
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Harding IH, Ryan J, Heritier S, Spark S, Flanagan Z, McIntyre R, Anderson CS, Naismith SL, Chong TTJ, O'Sullivan M, Egan G, Law M, Zoungas S. STAREE-Mind Imaging Study: a randomised placebo-controlled trial of atorvastatin for prevention of cerebrovascular decline and neurodegeneration in older individuals. BMJ Neurol Open 2023; 5:e000541. [PMID: 37920607 PMCID: PMC10619122 DOI: 10.1136/bmjno-2023-000541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 10/08/2023] [Indexed: 11/04/2023] Open
Abstract
Introduction Cerebrovascular disease and neurodegeneration are causes of cognitive decline and dementia, for which primary prevention options are currently lacking. Statins are well-tolerated and widely available medications that potentially have neuroprotective effects. The STAREE-Mind Imaging Study is a randomised, double-blind, placebo-controlled clinical trial that will investigate the impact of atorvastatin on markers of neurovascular health and brain atrophy in a healthy, older population using MRI. This is a nested substudy of the 'Statins for Reducing Events in the Elderly' (STAREE) primary prevention trial. Methods Participants aged 70 years or older (n=340) will be randomised to atorvastatin or placebo. Comprehensive brain MRI assessment will be undertaken at baseline and up to 4 years follow-up, including structural, diffusion, perfusion and susceptibility imaging. The primary outcome measures will be change in brain free water fraction (a composite marker of vascular leakage, neuroinflammation and neurodegeneration) and white matter hyperintensity volume (small vessel disease). Secondary outcomes will include change in perivascular space volume (glymphatic drainage), cortical thickness, hippocampal volume, microbleeds and lacunae, prefrontal cerebral perfusion and white matter microstructure. Ethics and dissemination Academic publications from this work will address the current uncertainty regarding the impact of statins on brain structure and vascular integrity. This study will inform the utility of repurposing these well-tolerated, inexpensive and widely available drugs for primary prevention of neurological outcomes in older individuals. Ethics approval was given by Monash University Human Research Ethics Committee, Protocol 12206. Trial registration number ClinicalTrials.gov Identifier: NCT05586750.
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Affiliation(s)
- Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Stephane Heritier
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Simone Spark
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Zachary Flanagan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Richard McIntyre
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Craig S Anderson
- Global Brain Health Program, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Sharon L Naismith
- School of Psychology, University of Sydney, Sydney, New South Wales, Australia
| | - Trevor T-J Chong
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Michael O'Sullivan
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Gary Egan
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Sophia Zoungas
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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22
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Rodrigue AL, Hayes RA, Waite E, Corcoran M, Glahn DC, Jalbrzikowski M. Multimodal Neuroimaging Summary Scores as Neurobiological Markers of Psychosis. Schizophr Bull 2023:sbad149. [PMID: 37844289 DOI: 10.1093/schbul/sbad149] [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: 10/18/2023]
Abstract
BACKGROUND AND HYPOTHESIS Structural brain alterations are well-established features of schizophrenia but they do not effectively predict disease/disease risk. Similar to polygenic risk scores in genetics, we integrated multifactorial aspects of brain structure into a summary "Neuroscore" and examined its potential as a marker of disease. STUDY DESIGN We extracted measures from T1-weighted scans and diffusion tensor imaging (DTI) models from three studies with schizophrenia and healthy individuals. We calculated individual-level summary scores (Neuroscores) for T1-weighted and DTI measures and a combined score (Multimodal Neuroscore-MM). We assessed each score's ability to differentiate schizophrenia cases from controls and its relationship to clinical symptomatology, intelligence quotient (IQ), and medication dosage. We assessed Neuroscore specificity by performing all analyses in a more inclusive psychosis sample and by using scores generated from MDD effect sizes. STUDY RESULTS All Neuroscores significantly differentiated schizophrenia cases from controls (T1 d = 0.56, DTI d = 0.29, MM d = 0.64) to a greater degree than individual brain regions. Higher Neuroscores (ie, increased liability) were associated with lower IQ (T1 β = -0.26, DTI β = -0.15, MM β = -0.30). Higher T1-weighted Neuroscores were associated with higher positive and negative symptom severity (Positive β = 0.21, Negative β = 0.16); Higher Multimodal Neuroscores were associated with higher positive symptom severity (β = 0.30). SZ Neuroscores outperformed MDD Neuroscores in predicting IQ (T1: z = 3.5, q = 0.0007; MM: z = 1.8, q = 0.05). CONCLUSIONS Neuroscores are a step toward leveraging widespread structural brain alterations in psychosis to identify robust neurobiological markers of disease. Future studies will assess ways to improve neuroscore calculation, including developing the optimal methods to calculate neuroscores and considering disorder overlap.
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Affiliation(s)
- Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Rebecca A Hayes
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
| | - Emma Waite
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
| | - Mary Corcoran
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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23
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Kushol R, Parnianpour P, Wilman AH, Kalra S, Yang YH. Effects of MRI scanner manufacturers in classification tasks with deep learning models. Sci Rep 2023; 13:16791. [PMID: 37798392 PMCID: PMC10556074 DOI: 10.1038/s41598-023-43715-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 09/27/2023] [Indexed: 10/07/2023] Open
Abstract
Deep learning has become a leading subset of machine learning and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards multi-center neuroimaging studies to address complex questions in neuroscience, leveraging larger sample sizes and aiming to enhance the accuracy of deep learning models. However, variations in image pixel/voxel characteristics can arise between centers due to factors including differences in magnetic resonance imaging scanners. Such variations create challenges, particularly inconsistent performance in machine learning-based approaches, often referred to as domain shift, where the trained models fail to achieve satisfactory or improved results when confronted with dissimilar test data. This study analyzes the performance of multiple disease classification tasks using multi-center MRI data obtained from three widely used scanner manufacturers (GE, Philips, and Siemens) across several deep learning-based networks. Furthermore, we investigate the efficacy of mitigating scanner vendor effects using ComBat-based harmonization techniques when applied to multi-center datasets of 3D structural MR images. Our experimental results reveal a substantial decline in classification performance when models trained on one type of scanner manufacturer are tested with data from different manufacturers. Moreover, despite applying ComBat-based harmonization, the harmonized images do not demonstrate any noticeable performance enhancement for disease classification tasks.
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Affiliation(s)
- Rafsanjany Kushol
- Department of Computing Science, University of Alberta, Edmonton, Canada.
| | - Pedram Parnianpour
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Alan H Wilman
- Departments of Radiology and Diagnostic Imaging and Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Sanjay Kalra
- Department of Computing Science, University of Alberta, Edmonton, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
| | - Yee-Hong Yang
- Department of Computing Science, University of Alberta, Edmonton, Canada
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24
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Banaj N, Vecchio D, Piras F, De Rossi P, Bustillo J, Ciufolini S, Dazzan P, Di Forti M, Dickie EW, Ford JM, Fuentes-Claramonte P, Gruber O, Guerrero-Pedraza A, Hamilton HK, Howells FM, Kraemer B, Lawrie SM, Mathalon DH, Murray R, Pomarol-Clotet E, Potkin SG, Preda A, Radua J, Richter A, Salvador R, Sawa A, Scheffler F, Sim K, Spaniel F, Stein DJ, Temmingh HS, Thomopoulos SI, Tomecek D, Uhlmann A, Voineskos A, Yang K, Jahanshad N, Thompson PM, Van Erp TGM, Turner JA, Spalletta G, Piras F. Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses. Mol Psychiatry 2023; 28:4363-4373. [PMID: 37644174 PMCID: PMC10827665 DOI: 10.1038/s41380-023-02221-w] [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: 01/20/2023] [Revised: 08/02/2023] [Accepted: 08/07/2023] [Indexed: 08/31/2023]
Abstract
Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.
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Affiliation(s)
- Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy.
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Pietro De Rossi
- Child and Adolescence Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Juan Bustillo
- Psichiatry and Neuroscience, University of New Mexico, Albuquerque, NM, USA
| | - Simone Ciufolini
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Marta Di Forti
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Erin W Dickie
- Center for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Kimel Family Lab, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Judith M Ford
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Paola Fuentes-Claramonte
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | | | - Holly K Hamilton
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Fleur M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Bernd Kraemer
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburg, EH10 5HF, UK
| | - Daniel H Mathalon
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Robin Murray
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Edith Pomarol-Clotet
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Steven G Potkin
- Department of Psychiatry, University of California Irvine, Newfoundland, NJ, NJ 07435, USA
| | - Adrian Preda
- Psychiatry and Human Behavior, University of California Irvine, Orange, CA, 92868, USA
| | - Joaquim Radua
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Imaging of mood- and anxiety-related disorders (IMARD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, 08036, Spain
- Medicina, University of Barcelona, Barcelona, 08036, Spain
| | - Anja Richter
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | - Raymond Salvador
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
| | - Akira Sawa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine Baltimore, Baltimore, MD, USA
- Department of Pharmacology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Freda Scheffler
- Department of Psychiatry and Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Brain Behavior Unit, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Kang Sim
- West Region, Institute of Mental Health, National Healthcare Group, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Filip Spaniel
- CARE, National Institute of Mental Health, Klecany, Czech Republic
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Henk S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, Western Cape, South Africa
- Department of Psychiatry and Mental Health, Valkenberg Psychiatric Hospital, Cape Town, Western Cape, South Africa
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - David Tomecek
- CARE, National Institute of Mental Health, Klecany, Czech Republic
| | - Anne Uhlmann
- Department of child and adolescent psychiatry, TU Dresden, Dresden, Saxony, Germany
| | - Aristotle Voineskos
- Center for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Temerty Faculty of Medicine, Toronto, ON, Canada
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - 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
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, The Ohio State University, Columbus, OH, USA
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Federica Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
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Antonopoulos G, More S, Raimondo F, Eickhoff SB, Hoffstaedter F, Patil KR. A systematic comparison of VBM pipelines and their application to age prediction. Neuroimage 2023; 279:120292. [PMID: 37572766 PMCID: PMC10529438 DOI: 10.1016/j.neuroimage.2023.120292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 06/23/2023] [Accepted: 07/21/2023] [Indexed: 08/14/2023] Open
Abstract
Voxel-based morphometry (VBM) analysis is commonly used for localized quantification of gray matter volume (GMV). Several alternatives exist to implement a VBM pipeline. However, how these alternatives compare and their utility in applications, such as the estimation of aging effects, remain largely unclear. This leaves researchers wondering which VBM pipeline they should use for their project. In this study, we took a user-centric perspective and systematically compared five VBM pipelines, together with registration to either a general or a study-specific template, utilizing three large datasets (n>500 each). Considering the known effect of aging on GMV, we first compared the pipelines in their ability of individual-level age prediction and found markedly varied results. To examine whether these results arise from systematic differences between the pipelines, we classified them based on their GMVs, resulting in near-perfect accuracy. To gain deeper insights, we examined the impact of different VBM steps using the region-wise similarity between pipelines. The results revealed marked differences, largely driven by segmentation and registration steps. We observed large variability in subject-identification accuracies, highlighting the interpipeline differences in individual-level quantification of GMV. As a biologically meaningful criterion we correlated regional GMV with age. The results were in line with the age-prediction analysis, and two pipelines, CAT and the combination of fMRIPrep for tissue characterization with FSL for registration, reflected age information better.
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Affiliation(s)
- Georgios Antonopoulos
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Shammi More
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Federico Raimondo
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.
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26
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Palau P, Solanes A, Madre M, Saez-Francas N, Sarró S, Moro N, Verdolini N, Sanchez M, Alonso-Lana S, Amann BL, Romaguera A, Martin-Subero M, Fortea L, Fuentes-Claramonte P, García-León MA, Munuera J, Canales-Rodríguez EJ, Fernández-Corcuera P, Brambilla P, Vieta E, Pomarol-Clotet E, Radua J. Improved estimation of the risk of manic relapse by combining clinical and brain scan data. SPANISH JOURNAL OF PSYCHIATRY AND MENTAL HEALTH 2023; 16:235-243. [PMID: 37839962 DOI: 10.1016/j.rpsm.2023.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 12/22/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023]
Abstract
INTRODUCTION Estimating the risk of manic relapse could help the psychiatrist individually adjust the treatment to the risk. Some authors have attempted to estimate this risk from baseline clinical data. Still, no studies have assessed whether the estimation could improve by adding structural magnetic resonance imaging (MRI) data. We aimed to evaluate it. MATERIAL AND METHODS We followed a cohort of 78 patients with a manic episode without mixed symptoms (bipolar type I or schizoaffective disorder) at 2-4-6-9-12-15-18 months and up to 10 years. Within a cross-validation scheme, we created and evaluated a Cox lasso model to estimate the risk of manic relapse using both clinical and MRI data. RESULTS The model successfully estimated the risk of manic relapse (Cox regression of the time to relapse as a function of the estimated risk: hazard ratio (HR)=2.35, p=0.027; area under the curve (AUC)=0.65, expected calibration error (ECE)<0.2). The most relevant variables included in the model were the diagnosis of schizoaffective disorder, poor impulse control, unusual thought content, and cerebellum volume decrease. The estimations were poorer when we used clinical or MRI data separately. CONCLUSION Combining clinical and MRI data may improve the risk of manic relapse estimation after a manic episode. We provide a website that estimates the risk according to the model to facilitate replication by independent groups before translation to clinical settings.
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Affiliation(s)
- Pol Palau
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Benito Menni CASM - Hospital General de Granollers, Germanes Hospitalàries, Barcelona, Spain; Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Aleix Solanes
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Barcelona, Spain
| | - Merce Madre
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Naia Saez-Francas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital Sant Rafael, Germanes Hospitalàries. Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Noemí Moro
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Benito Menni CASM - Hospital General de Granollers, Germanes Hospitalàries, Barcelona, Spain
| | - Norma Verdolini
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Barcelona Bipolar Disorders and Depressive Unit, Institute of Neurosciences, Hospital Clinic, Barcelona, Spain
| | - Manel Sanchez
- Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Barcelona, Spain; Department of Geriatric Psychiatry, Sagrat Cor Hospital, Martorell, Barcelona, Spain; Sociedad Española de Psicogeriatría (SEPG), Barcelona, Spain
| | - Sílvia Alonso-Lana
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
| | - Benedikt L Amann
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction, Parc de Salut Mar, Barcelona, Spain; Mental Health Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstrasse 7, 80336 Munich, Germany
| | - Anna Romaguera
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital Mare de Déu de la Mercè, Germanes Hospitalàries, Barcelona, Spain
| | - Marta Martin-Subero
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction, Parc de Salut Mar, Barcelona, Spain; Mental Health Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Maria A García-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Josep Munuera
- Imatge Diagnòstica i Terapèutica, Institut de Recerca Sant Joan de Déu, Santa Rosa 39-57, 08950 Esplugues de Llobregat, Spain; Servei de Diagnòstic per la Imatge, Hospital Sant Joan de Déu, Passeig Sant Joan de Déu 2, 08950 Esplugues de Llobregat, Spain
| | - Erick Jorge Canales-Rodríguez
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015 Lausanne, Switzerland
| | - Paloma Fernández-Corcuera
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Psychiatry Department, Hospital de Mataró, Consorci Sanitari del Maresme, Mataró, Spain
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Eduard Vieta
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Barcelona Bipolar Disorders and Depressive Unit, Institute of Neurosciences, Hospital Clinic, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
| | - Joaquim Radua
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, United Kingdom; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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Torbati ME, Minhas DS, Laymon CM, Maillard P, Wilson JD, Chen CL, Crainiceanu CM, DeCarli CS, Hwang SJ, Tudorascu DL. MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data. Med Image Anal 2023; 89:102926. [PMID: 37595405 PMCID: PMC10529705 DOI: 10.1016/j.media.2023.102926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 06/06/2023] [Accepted: 08/03/2023] [Indexed: 08/20/2023]
Abstract
Large-scale data obtained from aggregation of already collected multi-site neuroimaging datasets has brought benefits such as higher statistical power, reliability, and robustness to the studies. Despite these promises from growth in sample size, substantial technical variability stemming from differences in scanner specifications exists in the aggregated data and could inadvertently bias any downstream analyses on it. Such a challenge calls for data normalization and/or harmonization frameworks, in addition to comprehensive criteria to estimate the scanner-related variability and evaluate the harmonization frameworks. In this study, we propose MISPEL (Multi-scanner Image harmonization via Structure Preserving Embedding Learning), a supervised multi-scanner harmonization method that is naturally extendable to more than two scanners. We also designed a set of criteria to investigate the scanner-related technical variability and evaluate the harmonization techniques. As an essential requirement of our criteria, we introduced a multi-scanner matched dataset of 3T T1 images across four scanners, which, to the best of our knowledge is one of the few datasets of this kind. We also investigated our evaluations using two popular segmentation frameworks: FSL and segmentation in statistical parametric mapping (SPM). Lastly, we compared MISPEL to popular methods of normalization and harmonization, namely White Stripe, RAVEL, and CALAMITI. MISPEL outperformed these methods and is promising for many other neuroimaging modalities.
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Affiliation(s)
| | - Davneet S Minhas
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Charles M Laymon
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Pauline Maillard
- Department of Neurology, University of California Davis, Davis, CA 95816, USA
| | - James D Wilson
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Chang-Le Chen
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Ciprian M Crainiceanu
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Charles S DeCarli
- Department of Neurology, University of California Davis, Davis, CA 95816, USA
| | - Seong Jae Hwang
- Department of Artificial Intelligence, Yonsei University, Seoul, South Korea
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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周 巧, 刘 健, 忻 凌, 方 妍, 齐 亚, 胡 月. [Identification of Characteristic lncRNA Molecular Markers in Osteoarthritis by Integrating GEO Database and Machine Learning Strategies and Experimental Validation]. SICHUAN DA XUE XUE BAO. YI XUE BAN = JOURNAL OF SICHUAN UNIVERSITY. MEDICAL SCIENCE EDITION 2023; 54:899-907. [PMID: 37866944 PMCID: PMC10579086 DOI: 10.12182/20230960101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Indexed: 10/24/2023]
Abstract
Objective To screen for long non-coding RNA (lncRNA) molecular markers characteristic of osteoarthritis (OA) by utilizing the Gene Expression Omnibus (GEO) database combined with machine learning. Methods The samples of 185 OA patients and 76 healthy individuals as normal controls were included in the study. GEO datasets were screened for differentially expressed lncRNAs. Three algorithms, the least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF), were used to screen for candidate lncRNA models and receiver operating characteristic (ROC) curves were plotted to evaluate the models. We collected the peripheral blood samples of 30 clinical OA patients and 15 health controls and measured the immunoinflammatory indicators. RT-PCR was performed for quantitative analysis of the expression of lncRNA molecular markers in peripheral blood mononuclear cells (PBMC). Pearson analysis was performed to examine the correlation between lncRNA and indicators for inflammation of the immune system. Results A total of 14 key markers were identified with LASSO, 6 genes were identified with SVM-RFE, and 24 genes were identified with RF. Venn diagram was used to screen for overlapping genes identified with the three algorithms, showing HOTAIR, H19, MIR155 HG, and NKILA to be the overlapping genes. The ROC curves showed that these four lncRNAs all had an area under the curve ( AUC) greater than 0.7. The RT-PCR findings revealed relatively elevated expression of HOTAIR, H19, and MIR155HG and decreased expression of NKILA in the PBMC of OA patients compared with those of the normal group ( P<0.01). The results were consistent with the bioinformatics predictions. Pearson analysis showed that the candidate lncRNAs were correlated with clinical indicators for inflammation. Conclusion HOTAIR, H19, MIR155 HG, and NKILA can be used as molecular markers for the clinical diagnosis of OA and are correlate with clinical indicators of inflammation of the immune system.
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Affiliation(s)
- 巧 周
- 安徽中医药大学第一附属医院 (合肥 230031)The First Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230031, China
- 安徽中医药大学第二附属医院 (合肥 230061)The Second Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230061, China
- 安徽省中医药科学院风湿病研究所 (合肥 230031)Institute of Rheumatism Prevention and Treatment of Traditional Chinese Medicine, Anhui Academy of Chinese Medicine Sciences, Hefei 230031, China
| | - 健 刘
- 安徽中医药大学第一附属医院 (合肥 230031)The First Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230031, China
- 安徽中医药大学第二附属医院 (合肥 230061)The Second Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230061, China
| | - 凌 忻
- 安徽中医药大学第一附属医院 (合肥 230031)The First Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230031, China
- 安徽中医药大学第二附属医院 (合肥 230061)The Second Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230061, China
| | - 妍妍 方
- 安徽中医药大学第一附属医院 (合肥 230031)The First Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230031, China
- 安徽中医药大学第二附属医院 (合肥 230061)The Second Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230061, China
| | - 亚军 齐
- 安徽中医药大学第一附属医院 (合肥 230031)The First Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230031, China
- 安徽中医药大学第二附属医院 (合肥 230061)The Second Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230061, China
| | - 月迪 胡
- 安徽中医药大学第一附属医院 (合肥 230031)The First Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230031, China
- 安徽中医药大学第二附属医院 (合肥 230061)The Second Affiliated Hospital, Anhui University of Chinese Medicine, Hefei 230061, China
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Shiohama T, Maikusa N, Kawaguchi M, Natsume J, Hirano Y, Saito K, Takanashi JI, Levman J, Takahashi E, Matsumoto K, Yokota H, Hattori S, Tsujimura K, Sawada D, Uchida T, Takatani T, Fujii K, Naganawa S, Sato N, Hamada H. A Brain Morphometry Study with Across-Site Harmonization Using a ComBat-Generalized Additive Model in Children and Adolescents. Diagnostics (Basel) 2023; 13:2774. [PMID: 37685313 PMCID: PMC10487204 DOI: 10.3390/diagnostics13172774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
Regional anatomical structures of the brain are intimately connected to functions corresponding to specific regions and the temporospatial pattern of genetic expression and their functions from the fetal period to old age. Therefore, quantitative brain morphometry has often been employed in neuroscience investigations, while controlling for the scanner effect of the scanner is a critical issue for ensuring accuracy in brain morphometric studies of rare orphan diseases due to the lack of normal reference values available for multicenter studies. This study aimed to provide across-site normal reference values of global and regional brain volumes for each sex and age group in children and adolescents. We collected magnetic resonance imaging (MRI) examinations of 846 neurotypical participants aged 6.0-17.9 years (339 male and 507 female participants) from 5 institutions comprising healthy volunteers or neurotypical patients without neurological disorders, neuropsychological disorders, or epilepsy. Regional-based analysis using the CIVET 2.1.0. pipeline provided regional brain volumes, and the measurements were across-site combined using ComBat-GAM harmonization. The normal reference values of global and regional brain volumes and lateral indices in our study could be helpful for evaluating the characteristics of the brain morphology of each individual in a clinical setting and investigating the brain morphology of ultra-rare diseases.
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Affiliation(s)
- Tadashi Shiohama
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
- Division of Newborn Medicine, Department of Medicine, Boston Children’s Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Norihide Maikusa
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo 108-8639, Japan
- Department of Radiology, National Center Hospital, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan
| | - Masahiro Kawaguchi
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Aichi, Japan; (M.K.)
| | - Jun Natsume
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Aichi, Japan; (M.K.)
- Department of Developmental Disability Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Aichi, Japan
| | - Yoshiyuki Hirano
- Research Center for Child Mental Development, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita 565-0871, Osaka, Japan
| | - Keito Saito
- Department of Pediatrics and Pediatric Neurology, Tokyo Women’s Medical University Yachiyo Medical Center, 477-96 Owadashinden, Yachiyo-shi 276-8524, Chiba, Japan
| | - Jun-ichi Takanashi
- Department of Pediatrics and Pediatric Neurology, Tokyo Women’s Medical University Yachiyo Medical Center, 477-96 Owadashinden, Yachiyo-shi 276-8524, Chiba, Japan
| | - Jacob Levman
- Division of Newborn Medicine, Department of Medicine, Boston Children’s Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
- Department of Mathematics, Statistics and Computer Science, St. Francis Xavier University, 5005 Chapel Square, Antigonish, NS B2G 2W5, Canada
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA
- Nova Scotia Health Authority—Research, Innovation and Discovery Center for Clinical Research, 5790 University Avenue, Halifax, NS B3H 1V7, Canada
| | - Emi Takahashi
- Division of Newborn Medicine, Department of Medicine, Boston Children’s Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, MA 02129, USA
| | - Koji Matsumoto
- Department of Radiology, Chiba University Hospital, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
| | - Hajime Yokota
- Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
| | - Shinya Hattori
- Department of Radiology, Chiba University Hospital, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
| | - Keita Tsujimura
- Group of Brain Function and Development, Neuroscience Institute of the Graduate School of Science, Nagoya University, Nagoya 466-8550, Aichi, Japan
- Research Unit for Developmental Disorders, Institute for Advanced Research, Nagoya University, Nagoya 466-8550, Aichi, Japan
| | - Daisuke Sawada
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
| | - Tomoko Uchida
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
| | - Tomozumi Takatani
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
| | - Katsunori Fujii
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
- Department of Pediatrics, International University of Welfare and Health School of Medicine, Narita 286-8520, Chiba, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Aichi, Japan
| | - Noriko Sato
- Department of Radiology, National Center Hospital, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan
| | - Hiromichi Hamada
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan
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30
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Rahayel S, Tremblay C, Vo A, Misic B, Lehéricy S, Arnulf I, Vidailhet M, Corvol JC, Gagnon JF, Postuma RB, Montplaisir J, Lewis S, Matar E, Ehgoetz Martens K, Borghammer P, Knudsen K, Hansen AK, Monchi O, Gan-Or Z, Dagher A. Mitochondrial function-associated genes underlie cortical atrophy in prodromal synucleinopathies. Brain 2023; 146:3301-3318. [PMID: 36826230 PMCID: PMC10393413 DOI: 10.1093/brain/awad044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 01/12/2023] [Accepted: 02/03/2023] [Indexed: 02/25/2023] Open
Abstract
Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49-87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41-88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks.
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Affiliation(s)
- Shady Rahayel
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
| | - Christina Tremblay
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Andrew Vo
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Bratislav Misic
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Stéphane Lehéricy
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Isabelle Arnulf
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Marie Vidailhet
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Jean-Christophe Corvol
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Jean-François Gagnon
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Psychology, University of Quebec in Montreal, Montreal H2X 3P2, Canada
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal H3W 1W5, Canada
| | - Ronald B Postuma
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Neurology, Montreal General Hospital, Montreal H3G 1A4, Canada
| | - Jacques Montplaisir
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Psychiatry, University of Montreal, Montreal H3T 1J4, Canada
| | - Simon Lewis
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
| | - Elie Matar
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
| | - Kaylena Ehgoetz Martens
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
- Department of Kinesiology, University of Waterloo, Waterloo N2L 3G1, Canada
| | - Per Borghammer
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Karoline Knudsen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Allan K Hansen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Oury Monchi
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal H3W 1W5, Canada
- Department of Radiology, Radio-Oncology, and Nuclear Medicine, University of Montreal, Montreal H3T 1A4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
- Department of Human Genetics, McGill University, Montreal H3A 0C7, Canada
| | - Alain Dagher
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
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31
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Elliott ML, Hanford LC, Hamadeh A, Hilbert T, Kober T, Dickerson BC, Mair RW, Eldaief MC, Buckner RL. Brain morphometry in older adults with and without dementia using extremely rapid structural scans. Neuroimage 2023; 276:120173. [PMID: 37201641 PMCID: PMC10330834 DOI: 10.1016/j.neuroimage.2023.120173] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/25/2023] [Accepted: 05/15/2023] [Indexed: 05/20/2023] Open
Abstract
T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry. Here we compared the measurement properties of a widely adopted 1.0 mm resolution scan from the Alzheimer's Disease Neuroimaging Initiative (ADNI = 5'12'') with two variants of highly accelerated 1.0 mm scans (compressed-sensing, CSx6 = 1'12''; and wave-controlled aliasing in parallel imaging, WAVEx9 = 1'09'') in a test-retest study of 37 older adults aged 54 to 86 (including 19 individuals diagnosed with a neurodegenerative dementia). Rapid scans produced highly reliable morphometric measures that largely matched the quality of morphometrics derived from the ADNI scan. Regions of lower reliability and relative divergence between ADNI and rapid scan alternatives tended to occur in midline regions and regions with susceptibility-induced artifacts. Critically, the rapid scans yielded morphometric measures similar to the ADNI scan in regions of high atrophy. The results converge to suggest that, for many current uses, extremely rapid scans can replace longer scans. As a final test, we explored the possibility of a 0'49'' 1.2 mm CSx6 structural scan, which also showed promise. Rapid structural scans may benefit MRI studies by shortening the scan session and reducing cost, minimizing opportunity for movement, creating room for additional scan sequences, and allowing for the repetition of structural scans to increase precision of the estimates.
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Affiliation(s)
- Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA.
| | - Lindsay C Hanford
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA
| | - Aya Hamadeh
- Baylor College of Medicine, Houston, TX 77030, USA
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Massachusetts General Hospital, USA; Alzheimer's Disease Research Center, Massachusetts General Hospital, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA; Department of Neurology, Massachusetts General Hospital & Harvard Medical School, USA; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Ross W Mair
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
| | - Mark C Eldaief
- Frontotemporal Disorders Unit, Massachusetts General Hospital, USA; Alzheimer's Disease Research Center, Massachusetts General Hospital, USA; Department of Neurology, Massachusetts General Hospital & Harvard Medical School, USA; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA; Alzheimer's Disease Research Center, Massachusetts General Hospital, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
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32
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Zhang ZC, Zhao X, Dong G, Zhao XM. Improving Alzheimer's Disease Diagnosis With Multi-Modal PET Embedding Features by a 3D Multi-Task MLP-Mixer Neural Network. IEEE J Biomed Health Inform 2023; 27:4040-4051. [PMID: 37247318 DOI: 10.1109/jbhi.2023.3280823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Positron emission tomography (PET) with fluorodeoxyglucose (FDG) or florbetapir (AV45) has been proved effective in the diagnosis of Alzheimer's disease. However, the expensive and radioactive nature of PET has limited its application. Here, employing multi-layer perceptron mixer architecture, we present a deep learning model, namely 3-dimensional multi-task multi-layer perceptron mixer, for simultaneously predicting the standardized uptake value ratios (SUVRs) for FDG-PET and AV45-PET from the cheap and widely used structural magnetic resonance imaging data, and the model can be further used for Alzheimer's disease diagnosis based on embedding features derived from SUVR prediction. Experiment results demonstrate the high prediction accuracy of the proposed method for FDG/AV45-PET SUVRs, where we achieved Pearson's correlation coefficients of 0.66 and 0.61 respectively between the estimated and actual SUVR and the estimated SUVRs also show high sensitivity and distinct longitudinal patterns for different disease status. By taking into account PET embedding features, the proposed method outperforms other competing methods on five independent datasets in the diagnosis of Alzheimer's disease and discriminating between stable and progressive mild cognitive impairments, achieving the area under receiver operating characteristic curves of 0.968 and 0.776 respectively on ADNI dataset, and generalizes better to other external datasets. Moreover, the top-weighted patches extracted from the trained model involve important brain regions related to Alzheimer's disease, suggesting good biological interpretability of our proposed method."
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33
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Wang C, Hayes R, Roeder K, Jalbrzikowski M. Neurobiological Clusters Are Associated With Trajectories of Overall Psychopathology in Youth. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:852-863. [PMID: 37121399 PMCID: PMC10792597 DOI: 10.1016/j.bpsc.2023.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/22/2023] [Accepted: 04/13/2023] [Indexed: 05/02/2023]
Abstract
BACKGROUND Integrating multiple neuroimaging modalities to identify clusters of individuals and then associating these clusters with psychopathology is a promising approach for understanding neurobiological mechanisms that underlie psychopathology and the extent to which these features are associated with clinical symptoms. METHODS We leveraged neuroimaging data from T1-weighted, diffusion-weighted, and resting-state functional magnetic resonance images from the Adolescent Brain Cognitive Development (ABCD) Study (N = 8035) and used similarity network fusion and spectral clustering to identify subgroups of participants. We examined neuroimaging measures as a function of clustering profiles using 1, 2, or 3 imaging modalities (i.e., data combinations), calculated the stability of the clustering assignment in each respective data combination, and compared the consistency of clusters across different data combinations. We then compared the extent to which clusters were associated with overall psychopathology at the baseline assessment and at 2 yearly follow-up visits. RESULTS Each data combination resulted in optimal clusters ranging from 2 to 4 subgroups for each data combination. Clusters were stable across subsampling of the ABCD Study cohort. Widespread structural measures (surface area, fractional anisotropy, and mean diffusivity) were important features contributing to clustering across different data combinations. Five of the seven data combinations were associated with overall psychopathology, both at baseline and over time (d = 0.08-0.41). Generally, lower global cortical volume and surface area, widespread reduced fractional anisotropy, and increased radial diffusivity were associated with increased overall psychopathology. CONCLUSIONS Profiles constructed from neuroimaging data combinations are associated with concurrent and future psychopathology trajectories.
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Affiliation(s)
- Catherine Wang
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Rebecca Hayes
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, Massachusetts
| | - Kathryn Roeder
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania; Department of Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts.
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Reynolds M, Chaudhary T, Eshaghzadeh Torbati M, Tudorascu DL, Batmanghelich K. ComBat Harmonization: Empirical Bayes versus fully Bayes approaches. Neuroimage Clin 2023; 39:103472. [PMID: 37506457 PMCID: PMC10412957 DOI: 10.1016/j.nicl.2023.103472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023]
Abstract
Studying small effects or subtle neuroanatomical variation requires large-scale sample size data. As a result, combining neuroimaging data from multiple datasets is necessary. Variation in acquisition protocols, magnetic field strength, scanner build, and many other non-biologically related factors can introduce undesirable bias into studies. Hence, harmonization is required to remove the bias-inducing factors from the data. ComBat is one of the most common methods applied to features from structural images. ComBat models the data using a hierarchical Bayesian model and uses the empirical Bayes approach to infer the distribution of the unknown factors. The empirical Bayes harmonization method is computationally efficient and provides valid point estimates. However, it tends to underestimate uncertainty. This paper investigates a new approach, fully Bayesian ComBat, where Monte Carlo sampling is used for statistical inference. When comparing fully Bayesian and empirical Bayesian ComBat, we found Empirical Bayesian ComBat more effectively removed scanner strength information and was much more computationally efficient. Conversely, fully Bayesian ComBat better preserved biological disease and age-related information while performing more accurate harmonization on traveling subjects. The fully Bayesian approach generates a rich posterior distribution, which is useful for generating simulated imaging features for improving classifier performance in a limited data setting. We show the generative capacity of our model for augmenting and improving the detection of patients with Alzheimer's disease. Posterior distributions for harmonized imaging measures can also be used for brain-wide uncertainty comparison and more principled downstream statistical analysis.Code for our new fully Bayesian ComBat extension is available at https://github.com/batmanlab/BayesComBat.
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Affiliation(s)
- Maxwell Reynolds
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, 5607 Baum Blvd. Suite 500, Pittsburgh, PA 15206, USA.
| | - Tigmanshu Chaudhary
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, 5607 Baum Blvd. Suite 500, Pittsburgh, PA 15206, USA.
| | - Mahbaneh Eshaghzadeh Torbati
- Intelligent System Program, University of Pittsburgh School of Computing and Information, 210 South Bouquet Street, Pittsburgh, PA 15260, USA.
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh School of Medicine, 3811 O'Hara Street, Pittsburgh, PA 15213, USA; Department of Biostatistics, University of Pittsburgh, 130 De Soto Street, Pittsburgh, PA 15213, USA.
| | - Kayhan Batmanghelich
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, 5607 Baum Blvd. Suite 500, Pittsburgh, PA 15206, USA.
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35
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Leming MJ, Bron EE, Bruffaerts R, Ou Y, Iglesias JE, Gollub RL, Im H. Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting. NPJ Digit Med 2023; 6:129. [PMID: 37443276 DOI: 10.1038/s41746-023-00868-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 06/26/2023] [Indexed: 07/15/2023] Open
Abstract
Advances in artificial intelligence have cultivated a strong interest in developing and validating the clinical utilities of computer-aided diagnostic models. Machine learning for diagnostic neuroimaging has often been applied to detect psychological and neurological disorders, typically on small-scale datasets or data collected in a research setting. With the collection and collation of an ever-growing number of public datasets that researchers can freely access, much work has been done in adapting machine learning models to classify these neuroimages by diseases such as Alzheimer's, ADHD, autism, bipolar disorder, and so on. These studies often come with the promise of being implemented clinically, but despite intense interest in this topic in the laboratory, limited progress has been made in clinical implementation. In this review, we analyze challenges specific to the clinical implementation of diagnostic AI models for neuroimaging data, looking at the differences between laboratory and clinical settings, the inherent limitations of diagnostic AI, and the different incentives and skill sets between research institutions, technology companies, and hospitals. These complexities need to be recognized in the translation of diagnostic AI for neuroimaging from the laboratory to the clinic.
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Affiliation(s)
- Matthew J Leming
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA.
- Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.
| | - Esther E Bron
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Rose Bruffaerts
- Computational Neurology, Experimental Neurobiology Unit (ENU), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Biomedical Research Institute, Hasselt University, Diepenbeek, Belgium
| | - Yangming Ou
- Boston Children's Hospital, 300 Longwood Ave, Boston, MA, USA
| | - Juan Eugenio Iglesias
- Center for Medical Image Computing, University College London, London, UK
- Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Randy L Gollub
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hyungsoon Im
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA.
- Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
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36
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Hu F, Chen AA, Horng H, Bashyam V, Davatzikos C, Alexander-Bloch A, Li M, Shou H, Satterthwaite TD, Yu M, Shinohara RT. Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization. Neuroimage 2023; 274:120125. [PMID: 37084926 PMCID: PMC10257347 DOI: 10.1016/j.neuroimage.2023.120125] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/12/2023] [Accepted: 04/19/2023] [Indexed: 04/23/2023] Open
Abstract
Magnetic resonance imaging and computed tomography from multiple batches (e.g. sites, scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to obtain new insights into the human brain. However, significant confounding due to batch-related technical variation, called batch effects, is present in this data; direct application of downstream analyses to the data may lead to biased results. Image harmonization methods seek to remove these batch effects and enable increased generalizability and reproducibility of downstream results. In this review, we describe and categorize current approaches in statistical and deep learning harmonization methods. We also describe current evaluation metrics used to assess harmonization methods and provide a standardized framework to evaluate newly-proposed methods for effective harmonization and preservation of biological information. Finally, we provide recommendations to end-users to advocate for more effective use of current methods and to methodologists to direct future efforts and accelerate development of the field.
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Affiliation(s)
- Fengling Hu
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States.
| | - Andrew A Chen
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
| | - Hannah Horng
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
| | - Vishnu Bashyam
- Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States; Penn-CHOP Lifespan Brain Institute, United States; Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, United States
| | - Mingyao Li
- Statistical Center for Single-Cell and Spatial Genomics, Perelman School of Medicine, University of Pennsylvania, United States
| | - Haochang Shou
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States; Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States; Penn-CHOP Lifespan Brain Institute, United States; The Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States
| | - Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, United States
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States; Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
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37
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Kennedy E, Dennis EL, Lindsey HM, deRoon-Cassini T, Du Plessis S, Fani N, Kaufman ML, Koen N, Larson CL, Laskowitz S, Lebois LAM, Morey RA, Newsome MR, Palermo C, Pastorek NJ, Powers A, Scheibel R, Seedat S, Seligowski A, Stein DJ, Stevens J, Sun D, Thompson P, Troyanskaya M, van Rooij SJH, Watts AA, Tomas CW, Williams W, Hillary FG, Pugh MJ, Wilde EA, Tate DF. Harmonizing PTSD severity scales across instruments and sites. Neuropsychology 2023; 37:398-408. [PMID: 35797175 PMCID: PMC9948684 DOI: 10.1037/neu0000823] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE The variety of instruments used to assess posttraumatic stress disorder (PTSD) allows for flexibility, but also creates challenges for data synthesis. The objective of this work was to use a multisite mega analysis to derive quantitative recommendations for equating scores across measures of PTSD severity. METHOD Empirical Bayes harmonization and linear models were used to describe and mitigate site and covariate effects. Quadratic models for converting scores across PTSD assessments were constructed using bootstrapping and tested on hold out data. RESULTS We aggregated 17 data sources and compiled an n = 5,634 sample of individuals who were assessed for PTSD symptoms. We confirmed our hypothesis that harmonization and covariate adjustments would significantly improve inference of scores across instruments. Harmonization significantly reduced cross-dataset variance (28%, p < .001), and models for converting scores across instruments were well fit (median R² = 0.985) with an average root mean squared error of 1.46 on sum scores. CONCLUSIONS These methods allow PTSD symptom severity to be placed on multiple scales and offers interesting empirical perspectives on the role of harmonization in the behavioral sciences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Eamonn Kennedy
- Department of Neurology, University of Utah School of Medicine
| | - Emily L Dennis
- Department of Neurology, University of Utah School of Medicine
| | | | - Terri deRoon-Cassini
- Department of Surgery, Division of Trauma and Acute Care Surgery, Medical College of Wisconsin
| | | | - Negar Fani
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine
| | | | - Nastassja Koen
- Department of Psychiatry and Mental Health, University of Cape Town
| | | | | | | | | | - Mary R Newsome
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine
| | - Cori Palermo
- Department of Psychiatry, Harvard Medical School
| | - Nicholas J Pastorek
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine
| | - Abigail Powers
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine
| | - Randall Scheibel
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine
| | - Soraya Seedat
- SU/UCT MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University
| | | | - Dan J Stein
- Department of Psychiatry and Mental Health, University of Cape Town
| | - Jennifer Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine
| | - Delin Sun
- Brain Imaging and Analysis Center, Duke University
| | - Paul Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC
| | - Maya Troyanskaya
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine
| | | | | | | | | | - Mary Jo Pugh
- Department of Neurology, University of Utah School of Medicine
| | | | - David F Tate
- Department of Neurology, University of Utah School of Medicine
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Mørch-Johnsen L, Jørgensen KN, Barth C, Nerland S, Bringslid IK, Wortinger LA, Andreou D, Melle I, Andreassen OA, Agartz I. Thalamic nuclei volumes in schizophrenia and bipolar spectrum disorders - Associations with diagnosis and clinical characteristics. Schizophr Res 2023; 256:26-35. [PMID: 37126979 DOI: 10.1016/j.schres.2023.04.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 03/16/2023] [Accepted: 04/19/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND The thalamus is central to brain functions ranging from primary sensory processing to higher-order cognition. Structural deficits in thalamic association nuclei such as the pulvinar and mediodorsal nuclei have previously been reported in schizophrenia. However, the specificity with regards to clinical presentation, and whether or not bipolar disorder (BD) is associated with similar alterations is unclear. METHODS We investigated thalamic nuclei volumes in 334 patients with schizophrenia spectrum disorders (SSD) (median age 29 years, 59 % male), 322 patients with BD (30 years, 40 % male), and 826 healthy controls (HC) (34 years, 54 % male). Volumes of 25 thalamic nuclei were extracted from T1-weighted magnetic resonance imaging using an automated Bayesian segmentation method and compared between groups. Furthermore, we explored associations with clinical characteristics across diagnostic groups, including psychotic and mood symptoms and medication use, as well as diagnostic subtype in BD. RESULTS Significantly smaller volumes were found in the mediodorsal, pulvinar, and lateral and medial geniculate thalamic nuclei in SSD. Similarly, smaller volumes were found in BD in the same four regions, but mediodorsal nucleus volume alterations were limited to its lateral part and pulvinar alterations to its anterior region. Smaller volumes in BD compared to HC were seen only in BD type I, not BD type II. Across diagnoses, having more negative symptoms was associated with smaller pulvinar volumes. CONCLUSIONS Structural alterations were found in both SSD and BD, mainly in the thalamic association nuclei. Structural deficits in the pulvinar may be of relevance for negative symptoms.
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Affiliation(s)
- Lynn Mørch-Johnsen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry & Department of Clinical Research, Østfold Hospital, Grålum, Norway.
| | - Kjetil Nordbø Jørgensen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry, Telemark Hospital, Skien, Norway
| | - Claudia Barth
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Stener Nerland
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Ida Kippersund Bringslid
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Laura A Wortinger
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Dimitrios Andreou
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden; K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
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39
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Brossard-Racine M, Rampakakis E, Tardif CL, Gilbert G, White A, Luu TM, Gallagher A, Pinchefsky E, Montreuil T, Simard MN, Wintermark P. Long-term consequences of neonatal encephalopathy in the hypothermia era: protocol for a follow-up cohort study at 9 years of age. BMJ Open 2023; 13:e073063. [PMID: 37055215 PMCID: PMC10106079 DOI: 10.1136/bmjopen-2023-073063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/15/2023] Open
Abstract
INTRODUCTION Therapeutic hypothermia (TH) became the standard of care treatment for neonates with moderate and severe neonatal encephalopathy (NE) in most industrialized countries about 10 years ago. Although TH is effective in reducing mortality and the incidence of severe developmental disabilities, the recent literature converges in reporting frequent cognitive and behavioural difficulties at school entry in children with NE-TH. Although these challenges are deemed minor compared with cerebral palsy and intellectual disability, their impacts on a child's self-determination and family's well-being are quite significant. Therefore, the nature and extent of these difficulties need to be comprehensively described so that appropriate care can be offered. METHODS AND ANALYSIS The current study will be the largest follow-up study of neonates with NE treated with TH to characterize their developmental outcomes and associated brain structural profiles at 9 years of age. Specifically, we will compare executive function, attention, social cognition, behaviour, anxiety, self-esteem, peer problems, brain volume, cortical features, white matter microstructure and myelination between children with NE-TH and matched peers without NE. Associations of perinatal risk factors and structural brain integrity with cognitive, behavioural and psycho-emotional deficits will be evaluated to inform about the potential aggravating and protective factors associated with function. ETHICS AND DISSEMINATION This study is supported by the Canadian Institute of Health Research (202203PJT-480065-CHI-CFAC-168509), and received approval from the Pediatric Ethical Review Board of the McGill University Health Center (MP-37-2023-9320). The study findings will be disseminated in scientific journals and conferences and presented to parental associations and healthcare providers to inform best practices. TRIAL REGISTRATION NUMBER NCT05756296.
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Affiliation(s)
- Marie Brossard-Racine
- Department of Pediatrics, McGill University Health Centre, Montreal, Quebec, Canada
- School of Physical and Occupational Therapy, McGill University, Montreal, Quebec, Canada
- Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | | | | | | | - Angela White
- Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Thuy Mai Luu
- Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada
- University of Montreal, Montreal, Quebec, Canada
| | - Anne Gallagher
- Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada
- University of Montreal, Montreal, Quebec, Canada
| | - Elana Pinchefsky
- Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada
- University of Montreal, Montreal, Quebec, Canada
| | - Tina Montreuil
- Department of Psychiatry, McGill University Montreal, Montreal, Quebec, Canada
- Department of Educational and Counselling Psychology, McGill University Montreal, Montreal, Quebec, Canada
| | - Marie-Noelle Simard
- Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada
- University of Montreal, Montreal, Quebec, Canada
| | - Pia Wintermark
- Department of Pediatrics, McGill University Health Centre, Montreal, Quebec, Canada
- Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
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40
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Kennedy E, Vadlamani S, Lindsey HM, Lei PW, Jo-Pugh M, Adamson M, Alda M, Alonso-Lana S, Ambrogi S, Anderson TJ, Arango C, Asarnow RF, Avram M, Ayesa-Arriola R, Babikian T, Banaj N, Bird LJ, Borgwardt S, Brodtmann A, Brosch K, Caeyenberghs K, Calhoun VD, Chiaravalloti ND, Cifu DX, Crespo-Facorro B, Dalrymple-Alford JC, Dams-O’Connor K, Dannlowski U, Darby D, Davenport N, DeLuca J, Diaz-Caneja CM, Disner SG, Dobryakova E, Ehrlich S, Esopenko C, Ferrarelli F, Frank LE, Franz C, Fuentes-Claramonte P, Genova H, Giza CC, Goltermann J, Grotegerd D, Gruber M, Gutierrez-Zotes A, Ha M, Haavik J, Hinkin C, Hoskinson KR, Hubl D, Irimia A, Jansen A, Kaess M, Kang X, Kenney K, Keřková B, Khlif MS, Kim M, Kindler J, Kircher T, Knížková K, Kolskår KK, Krch D, Kremen WS, Kuhn T, Kumari V, Kwon JS, Langella R, Laskowitz S, Lee J, Lengenfelder J, Liebel SW, Liou-Johnson V, Lippa SM, Løvstad M, Lundervold A, Marotta C, Marquardt CA, Mattos P, Mayeli A, McDonald CR, Meinert S, Melzer TR, Merchán-Naranjo J, Michel C, Morey RA, Mwangi B, Myall DJ, Nenadić I, Newsome MR, Nunes A, O’Brien T, Oertel V, Ollinger J, Olsen A, de la Foz VOG, Ozmen M, Pardoe H, Parent M, Piras F, Piras F, Pomarol-Clotet E, Repple J, Richard G, Rodriguez J, Rodriguez M, Rootes-Murdy K, Rowland J, Ryan NP, Salvador R, Sanders AM, Schmidt A, Soares JC, Spalleta G, Španiel F, Stasenko A, Stein F, Straube B, Thames A, Thomas-Odenthal F, Thomopoulos SI, Tone E, Torres I, Troyanskaya M, Turner JA, Ulrichsen KM, Umpierrez G, Vilella E, Vivash L, Walker WC, Werden E, Westlye LT, Wild K, Wroblewski A, Wu MJ, Wylie GR, Yatham LN, Zunta-Soares GB, Thompson PM, Tate DF, Hillary FG, Dennis EL, Wilde EA. Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.16.524331. [PMID: 36712107 PMCID: PMC9882238 DOI: 10.1101/2023.01.16.524331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual's latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.
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Affiliation(s)
- Eamonn Kennedy
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
- Division of Epidemiology, University of Utah, Salt Lake City, UT, 84132
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, 84132
| | - Shashank Vadlamani
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
| | - Hannah M Lindsey
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, 84132
| | - Pui-Wa Lei
- Department of Educational Psychology, Counseling, and Special Education, Pennsylvania State University, University Park, PA, 16801
| | - Mary Jo-Pugh
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
- Division of Epidemiology, University of Utah, Salt Lake City, UT, 84132
| | - Maheen Adamson
- WRIISC-WOMEN & Rehabilitation Department, VA Palo Alto, Palo Alto, CA, USA
- Neurosurgery, Stanford School of Medicine, Stanford, CA, USA
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Canada
| | - Silvia Alonso-Lana
- FIDMAG Research Foundation, Barcelona, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Tim J Anderson
- Department of Medicine, University of Otago, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Neurology, Te Whatu Ora – Health New Zealand Waitaha Canterbury, Christchurch, New Zealand
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Robert F Asarnow
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
- Brain Research Institute, UCLA, Los Angeles, CA, USA
- Department of Psychology, UCLA, Los Angeles, CA, USA
| | - Mihai Avram
- Translational Psychiatry, Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Rosa Ayesa-Arriola
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Talin Babikian
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
- UCLA Steve Tisch BrainSPORT Program, Los Angeles, CA, USA
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Laura J Bird
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Melbourne, VIC, Australia
| | - Stefan Borgwardt
- Translational Psychiatry, Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Center of Brain, Behaviour and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | - Amy Brodtmann
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - 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 University, Atlanta, GA, USA
| | - Nancy D Chiaravalloti
- Centers for Neuropsychology, Neuroscience & Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ, USA
| | - David X Cifu
- Rehabilitation Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
| | - Benedicto Crespo-Facorro
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Virgen del Rocio University Hospital, School of Medicine, University of Seville, IBIS, Seville, Spain
| | - John C Dalrymple-Alford
- Department of Medicine, University of Otago, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Kristen Dams-O’Connor
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Germany
| | - David Darby
- Department of Neuroscience, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Nicholas Davenport
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN
- Minneapolis VA Health Care System, Minneapolis, MN
| | - John DeLuca
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ, USA
- Kessler Foundation, East Hanover, NJ, USA
| | - Covadonga M Diaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Seth G Disner
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN
- Minneapolis VA Health Care System, Minneapolis, MN
| | - Ekaterina Dobryakova
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ, USA
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Germany
- Eating Disorders Research and Treatment Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany
| | - Carrie Esopenko
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lea E Frank
- Department of Psychology, University of Oregon, Eugene, OR, USA
| | - Carol Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Paola Fuentes-Claramonte
- FIDMAG Research Foundation, Barcelona, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Helen Genova
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ, USA
- Center for Autism Research, Kessler Foundation, East Hanover, NJ, USA
| | - Christopher C Giza
- UCLA Steve Tisch BrainSPORT Program, Los Angeles, CA, USA
- Department of Pediatrics, Division of Neurology, UCLA Mattel Children’s Hospital, Los Angeles, CA, USA
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Alfonso Gutierrez-Zotes
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
- Hospital Universitari Institut Pere Mata, Tarragona, Spain
- Institut d’Investiació Sanitària Pere Virgili-CERCA, Universitat Rovira i Virgili, Tarragona, Spain
| | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Charles Hinkin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
| | - Kristen R Hoskinson
- Center for Biobehavioral Health, The Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH
- Section of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio, USA
| | - Daniela Hubl
- Translational Research Centre, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative & Computational Biology, Dornsife College of Arts & Sciences, University of Southern California, Los Angeles CA, USA
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Clinic of Child and Adolescent Psychiatry, Centre of Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany
| | - Xiaojian Kang
- WRIISC-WOMEN & Rehabilitation Department, VA Palo Alto, Palo Alto, CA, USA
| | - Kimbra Kenney
- Department of Neurology, Uniformed Services University, Bethesda, MD
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD
| | | | - Mohamed Salah Khlif
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Karolina Knížková
- National Institute of Mental Health, Klecany, Czech Republic
- Department of Psychiatry, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Knut K Kolskår
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- Sunnaas Rehabilitation Hospital, Nesodden, Norway
| | - Denise Krch
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ, USA
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Taylor Kuhn
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
| | - Veena Kumari
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge, United Kingdom
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Roberto Langella
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Sarah Laskowitz
- Brain Imaging and Analysis Center, Duke University, Durham, NC
| | - Jungha Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Jean Lengenfelder
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ, USA
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ
| | - Spencer W Liebel
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, 84132
| | | | - Sara M Lippa
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD
- Department of Neuroscience, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Marianne Løvstad
- Department of Psychology, University of Oslo, Oslo, Norway
- Sunnaas Rehabilitation Hospital, Nesodden, Norway
| | - Astri Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Cassandra Marotta
- Department of Neuroscience, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - Craig A Marquardt
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN
- Minneapolis VA Health Care System, Minneapolis, MN
| | - Paulo Mattos
- Institute D’Or for Research and Education (IDOR), São Paulo, Brazil
| | - Ahmad Mayeli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carrie R McDonald
- Department of Radiation Medicine and Applied Sciences and Psychiatry, UC San Diego, La Jolla, CA, USA
- Center for Multimodal Imaging and Genetics, UC San Diego, San Diego, CA, USA
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Tracy R Melzer
- Department of Medicine, University of Otago, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Jessica Merchán-Naranjo
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Rajendra A Morey
- Brain Imaging and Analysis Center, Duke University, Durham, NC
- VISN 6 MIRECC, Durham VA, Durham, NC
| | - Benson Mwangi
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Daniel J Myall
- New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Mary R Newsome
- Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX
| | - Abraham Nunes
- Department of Psychiatry, Dalhousie University, Halifax, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
| | - Terence O’Brien
- Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
- Department of Neuroscience, The Central Clinical School, Alfred Health, Monash University, Melbourne, VIC, Australia
| | - Viola Oertel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapiey, Frankfurt University, Frankfurt, Germany
| | - John Ollinger
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- NorHEAD - Norwegian Centre for Headache Research, Trondheim, Norway
| | - Victor Ortiz García de la Foz
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Mustafa Ozmen
- Department of Electrical and Electronics Engineering, Antalya Bilim University, Antalya, Turkey
| | - Heath Pardoe
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Marise Parent
- Neuroscience Institute & Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Federica Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | | | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Geneviève Richard
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jonathan Rodriguez
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Mabel Rodriguez
- National Institute of Mental Health, Klecany, Czech Republic
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University University, Atlanta, GA, USA
| | - Jared Rowland
- W.G. (Bill) Hefner VA Medical Center, Salisbury, NC
- Department of Neurobiology & Anatomy, Wake Forest School of Medicine, Winston-Salem, NC
- VA Mid-Atlantic Mental Illness Research Education and Clinical Center (MA-MIRECC), Durham, NC
| | - Nicholas P Ryan
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia
| | - Raymond Salvador
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Anne-Marthe Sanders
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- Sunnaas Rehabilitation Hospital, Nesodden, Norway
| | - Andre Schmidt
- University of Basel, Department of Psychiatry (UPK), Basel, Switzerland
| | - Jair C Soares
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Filip Španiel
- National Institute of Mental Health, Klecany, Czech Republic
- 3rd Faculty of Medicine Charles University, Prague, Czech Republic
| | - Alena Stasenko
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Center for Multimodal Imaging and Genetics, UC San Diego, San Diego, CA, USA
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - April Thames
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
| | | | - Sophia I Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, 90007
| | - Erin Tone
- Department of Psychology, Georgia State University, Atlanta, GA
| | - Ivan Torres
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- British Columbia Mental Health and Substance Use Services Research Institute, Vancouver, BC, Canada
| | - Maya Troyanskaya
- Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX
| | - Jessica A Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Kristine M Ulrichsen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- Sunnaas Rehabilitation Hospital, Nesodden, Norway
| | - Guillermo Umpierrez
- Division of Endocrinology, Emory University School of Medicine, Atlanta, GA, USA
| | - Elisabet Vilella
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
- Hospital Universitari Institut Pere Mata, Tarragona, Spain
- Institut d’Investiació Sanitària Pere Virgili-CERCA, Universitat Rovira i Virgili, Tarragona, Spain
| | - Lucy Vivash
- Department of Neuroscience, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - William C Walker
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA
- Richmond Veterans Affairs (VA) Medical Center, Central Virginia VA Health Care System , Richmond, VA
| | - Emilio Werden
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Krista Wild
- Department of Psychology, Phoenix VA Health Care System, Phoenix, AZ, USA
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Mon-Ju Wu
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Glenn R Wylie
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ, USA
- Rocco Ortenzio Neuroimaging Center, Kessler Foundation, East Hanover, NJ, USA
| | - Lakshmi N Yatham
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Giovana B Zunta-Soares
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, 90007
- Departments of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and Ophthalmology, USC, Los Angeles, CA, 90007
| | - David F Tate
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, 84132
| | - Frank G Hillary
- Department of Psychology, Penn State University, State College, PA, 16801
- Department of Neurology, Hershey Medical Center, State College, PA, 16801
- Social Life and Engineering Science Imaging Center, Penn State University, State College, PA, 16801
| | - Emily L Dennis
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, 84132
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, 84132
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, 84132
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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: 0] [Impact Index Per Article: 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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Wang R, Bashyam V, Yang Z, Yu F, Tassopoulou V, Chintapalli SS, Skampardoni I, Sreepada LP, Sahoo D, Nikita K, Abdulkadir A, Wen J, Davatzikos C. Applications of generative adversarial networks in neuroimaging and clinical neuroscience. Neuroimage 2023; 269:119898. [PMID: 36702211 PMCID: PMC9992336 DOI: 10.1016/j.neuroimage.2023.119898] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 12/16/2022] [Accepted: 01/21/2023] [Indexed: 01/25/2023] Open
Abstract
Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields. They belong to the broader family of generative methods, which learn to generate realistic data with a probabilistic model by learning distributions from real samples. In the clinical context, GANs have shown enhanced capabilities in capturing spatially complex, nonlinear, and potentially subtle disease effects compared to traditional generative methods. This review critically appraises the existing literature on the applications of GANs in imaging studies of various neurological conditions, including Alzheimer's disease, brain tumors, brain aging, and multiple sclerosis. We provide an intuitive explanation of various GAN methods for each application and further discuss the main challenges, open questions, and promising future directions of leveraging GANs in neuroimaging. We aim to bridge the gap between advanced deep learning methods and neurology research by highlighting how GANs can be leveraged to support clinical decision making and contribute to a better understanding of the structural and functional patterns of brain diseases.
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Affiliation(s)
- Rongguang Wang
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA.
| | - Vishnu Bashyam
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Zhijian Yang
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Fanyang Yu
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Vasiliki Tassopoulou
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Sai Spandana Chintapalli
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Ioanna Skampardoni
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA; School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece
| | - Lasya P Sreepada
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Dushyant Sahoo
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Konstantina Nikita
- School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece
| | - Ahmed Abdulkadir
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA; Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Junhao Wen
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA
| | - Christos Davatzikos
- Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
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Yang Y, Schilling K, Shashikumar N, Jasodanand V, Moore EE, Pechman KR, Bilgel M, Beason‐Held LL, An Y, Shafer A, Risacher SL, Landman BA, Jefferson AL, Saykin AJ, Resnick SM, Hohman TJ, Archer DB. White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12425. [PMID: 37213219 PMCID: PMC10192723 DOI: 10.1002/dad2.12425] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 03/06/2023] [Accepted: 03/12/2023] [Indexed: 05/23/2023]
Abstract
Introduction White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum. Methods Diffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free-water (FW) corrected and conventional, and FW-corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status. Results Conventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished. Discussion White matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD. Highlights Longitudinal ComBat successfully harmonized large-scale diffusion magnetic resonance imaging (dMRI) metrics.Conventional dMRI metrics were globally sensitive to diagnostic status.Free-water (FW) correction mitigated intracellular associations with diagnostic status.The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW-corrected models may provide complementary information.
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Affiliation(s)
- Yisu Yang
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Kurt Schilling
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Varuna Jasodanand
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Elizabeth E. Moore
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Murat Bilgel
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Lori L. Beason‐Held
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Yang An
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Andrea Shafer
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Shannon L. Risacher
- Indiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndianapolisIndianaUSA
| | - Bennett A. Landman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTennesseeUSA
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Andrew J. Saykin
- Indiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndianapolisIndianaUSA
| | - Susan M. Resnick
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Derek B. Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
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Oliver D, Davies C, Zelaya F, Selvaggi P, De Micheli A, Catalan A, Baldwin H, Arribas M, Modinos G, Crossley NA, Allen P, Egerton A, Jauhar S, Howes OD, McGuire P, Fusar-Poli P. Parsing neurobiological heterogeneity of the clinical high-risk state for psychosis: A pseudo-continuous arterial spin labelling study. Front Psychiatry 2023; 14:1092213. [PMID: 36970257 PMCID: PMC10031088 DOI: 10.3389/fpsyt.2023.1092213] [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] [Received: 11/07/2022] [Accepted: 02/15/2023] [Indexed: 03/10/2023] Open
Abstract
Introduction The impact of the clinical high-risk for psychosis (CHR-P) construct is dependent on accurately predicting outcomes. Individuals with brief limited intermittent psychotic symptoms (BLIPS) have higher risk of developing a first episode of psychosis (FEP) compared to individuals with attenuated psychotic symptoms (APS). Supplementing subgroup stratification with information from candidate biomarkers based on neurobiological parameters, such as resting-state, regional cerebral blood flow (rCBF), may help refine risk estimates. Based on previous evidence, we hypothesized that individuals with BLIPS would exhibit increased rCBF compared to APS in key regions linked to dopaminergic pathways. Methods Data from four studies were combined using ComBat (to account for between-study differences) to analyse rCBF in 150 age- and sex-matched subjects (n = 30 healthy controls [HCs], n = 80 APS, n = 20 BLIPS and n = 20 FEP). Global gray matter (GM) rCBF was examined in addition to region-of-interest (ROI) analyses in bilateral/left/right frontal cortex, hippocampus and striatum. Group differences were assessed using general linear models: (i) alone; (ii) with global GM rCBF as a covariate; (iii) with global GM rCBF and smoking status as covariates. Significance was set at p < 0.05. Results Whole-brain voxel-wise analyses and Bayesian ROI analyses were also conducted. No significant group differences were found in global [F(3,143) = 1,41, p = 0.24], bilateral frontal cortex [F(3,143) = 1.01, p = 0.39], hippocampus [F(3,143) = 0.63, p = 0.60] or striatum [F(3,143) = 0.52, p = 0.57] rCBF. Similar null findings were observed in lateralized ROIs (p > 0.05). All results were robust to addition of covariates (p > 0.05). No significant clusters were identified in whole-brain voxel-wise analyses (p > 0.05FWE). Weak-to-moderate evidence was found for an absence of rCBF differences between APS and BLIPS in Bayesian ROI analyses. Conclusion On this evidence, APS and BLIPS are unlikely to be neurobiologically distinct. Due to this and the weak-to-moderate evidence for the null hypothesis, future research should investigate larger samples of APS and BLIPS through collaboration across large-scale international consortia.
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Affiliation(s)
- Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- NIHR Oxford Health Biomedical Research Centre, Oxford, United Kingdom
| | - Cathy Davies
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Fernando Zelaya
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Pierluigi Selvaggi
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Department of Translational Biomedicine and Neuroscience (DiBraiN), University of Bari Aldo Moro, Bari, Italy
| | - Andrea De Micheli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Ana Catalan
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Mental Health Department, Basurto University Hospital, Facultad de Medicina y Odontología, Campus de Leioa, Biocruces Bizkaia Health Research Institute, UPV/EHU, University of the Basque Country, Barakaldo, Spain
| | - Helen Baldwin
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- NIHR Mental Health Policy Research Unit, Division of Psychiatry, University College London, London, United Kingdom
| | - Maite Arribas
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Gemma Modinos
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Nicolas A. Crossley
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Paul Allen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychology, University of Roehampton, London, United Kingdom
| | - Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Sameer Jauhar
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Oliver D. Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Philip McGuire
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- NIHR Oxford Health Biomedical Research Centre, Oxford, United Kingdom
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, National Institute for Health Research, London, United Kingdom
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, National Institute for Health Research, London, United Kingdom
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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Lopez-Soley E, Martinez-Heras E, Solana E, Solanes A, Radua J, Vivo F, Prados F, Sepulveda M, Cabrera-Maqueda JM, Fonseca E, Blanco Y, Alba-Arbalat S, Martinez-Lapiscina EH, Villoslada P, Saiz A, Llufriu S. Diffusion tensor imaging metrics associated with future disability in multiple sclerosis. Sci Rep 2023; 13:3565. [PMID: 36864113 PMCID: PMC9981711 DOI: 10.1038/s41598-023-30502-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 02/24/2023] [Indexed: 03/04/2023] Open
Abstract
The relationship between brain diffusion microstructural changes and disability in multiple sclerosis (MS) remains poorly understood. We aimed to explore the predictive value of microstructural properties in white (WM) and grey matter (GM), and identify areas associated with mid-term disability in MS patients. We studied 185 patients (71% female; 86% RRMS) with the Expanded Disability Status Scale (EDSS), timed 25-foot walk (T25FW), nine-hole peg test (9HPT), and Symbol Digit Modalities Test (SDMT) at two time-points. We used Lasso regression to analyse the predictive value of baseline WM fractional anisotropy and GM mean diffusivity, and to identify areas related to each outcome at 4.1 years follow-up. Motor performance was associated with WM (T25FW: RMSE = 0.524, R2 = 0.304; 9HPT dominant hand: RMSE = 0.662, R2 = 0.062; 9HPT non-dominant hand: RMSE = 0.649, R2 = 0.139), and SDMT with GM diffusion metrics (RMSE = 0.772, R2 = 0.186). Cingulum, longitudinal fasciculus, optic radiation, forceps minor and frontal aslant were the WM tracts most closely linked to motor dysfunction, and temporal and frontal cortex were relevant for cognition. Regional specificity related to clinical outcomes provide valuable information that can be used to develop more accurate predictive models that could improve therapeutic strategies.
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Affiliation(s)
- E Lopez-Soley
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - E Martinez-Heras
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain.
| | - E Solana
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain.
| | - A Solanes
- Imaging of Mood- and Anxiety-Related Disorders Group, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, and CIBERSAM, Barcelona, Spain
| | - J Radua
- Imaging of Mood- and Anxiety-Related Disorders Group, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, and CIBERSAM, Barcelona, Spain
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Early Psychosis Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - F Vivo
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - F Prados
- E-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - M Sepulveda
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - J M Cabrera-Maqueda
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - E Fonseca
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
- Department of Neurology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
| | - Y Blanco
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - S Alba-Arbalat
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - E H Martinez-Lapiscina
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - P Villoslada
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - A Saiz
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
| | - S Llufriu
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Calle Villarroel 170, 08036, Barcelona, Spain
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Barth C, Kelly S, Nerland S, Jahanshad N, Alloza C, Ambrogi S, Andreassen OA, Andreou D, Arango C, Baeza I, Banaj N, Bearden CE, Berk M, Bohman H, Castro-Fornieles J, Chye Y, Crespo-Facorro B, de la Serna E, Díaz-Caneja CM, Gurholt TP, Hegarty CE, James A, Janssen J, Johannessen C, Jönsson EG, Karlsgodt KH, Kochunov P, Lois NG, Lundberg M, Myhre AM, Pascual-Diaz S, Piras F, Smelror RE, Spalletta G, Stokkan TS, Sugranyes G, Suo C, Thomopoulos SI, Tordesillas-Gutiérrez D, Vecchio D, Wedervang-Resell K, Wortinger LA, Thompson PM, Agartz I. In vivo white matter microstructure in adolescents with early-onset psychosis: a multi-site mega-analysis. Mol Psychiatry 2023; 28:1159-1169. [PMID: 36510004 PMCID: PMC10005938 DOI: 10.1038/s41380-022-01901-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 11/16/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022]
Abstract
Emerging evidence suggests brain white matter alterations in adolescents with early-onset psychosis (EOP; age of onset <18 years). However, as neuroimaging methods vary and sample sizes are modest, results remain inconclusive. Using harmonized data processing protocols and a mega-analytic approach, we compared white matter microstructure in EOP and healthy controls using diffusion tensor imaging (DTI). Our sample included 321 adolescents with EOP (median age = 16.6 years, interquartile range (IQR) = 2.14, 46.4% females) and 265 adolescent healthy controls (median age = 16.2 years, IQR = 2.43, 57.7% females) pooled from nine sites. All sites extracted mean fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) for 25 white matter regions of interest per participant. ComBat harmonization was performed for all DTI measures to adjust for scanner differences. Multiple linear regression models were fitted to investigate case-control differences and associations with clinical variables in regional DTI measures. We found widespread lower FA in EOP compared to healthy controls, with the largest effect sizes in the superior longitudinal fasciculus (Cohen's d = 0.37), posterior corona radiata (d = 0.32), and superior fronto-occipital fasciculus (d = 0.31). We also found widespread higher RD and more localized higher MD and AD. We detected significant effects of diagnostic subgroup, sex, and duration of illness, but not medication status. Using the largest EOP DTI sample to date, our findings suggest a profile of widespread white matter microstructure alterations in adolescents with EOP, most prominently in male individuals with early-onset schizophrenia and individuals with a shorter duration of illness.
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Affiliation(s)
- Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Sinead Kelly
- Department of Psychosis Studies, King's College London, London, UK
| | - Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, Madrid, Spain
| | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dimitrios Andreou
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Inmaculada Baeza
- Department Child and Adolescent Psychiatry and Psychology, 2017SGR881 Institute of Neuroscience, Hospital Clinic Barcelona. CIBERSAM. August Pi i Sunyer Biomedical Research Institute (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
- Department of Psychology, UCLA, Los Angeles, CA, USA
| | - Michael Berk
- Deakin University, Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Australia
| | - Hannes Bohman
- Department of Neuroscience, Child and Adolescent Psychiatry, Uppsala University, Uppsala, Sweden
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Josefina Castro-Fornieles
- Department Child and Adolescent Psychiatry and Psychology, 2017SGR881 Institute of Neuroscience, Hospital Clinic Barcelona. CIBERSAM. August Pi i Sunyer Biomedical Research Institute (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Yann Chye
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Benedicto Crespo-Facorro
- Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Department of Psychiatry, CIBERSAM, IBiS-CSIC, Sevilla, Spain
| | - Elena de la Serna
- Department Child and Adolescent Psychiatry and Psychology, 2017SGR881 Institute of Neuroscience, Hospital Clinic Barcelona. CIBERSAM. August Pi i Sunyer Biomedical Research Institute (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | | | - Anthony James
- Highfield Unit, Warneford Hospital, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, Madrid, Spain
| | - Cecilie Johannessen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Erik G Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Katherine H Karlsgodt
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
- Department of Psychology, UCLA, Los Angeles, CA, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MA, USA
| | - Noemi G Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - Mathias Lundberg
- Department of Neuroscience, Child and Adolescent Psychiatry, Uppsala University, Uppsala, Sweden
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Anne M Myhre
- Section of Child and Adolescent Mental Health Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Saül Pascual-Diaz
- Magnetic Resonance Imaging Core Facility, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Runar E Smelror
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Therese S Stokkan
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gisela Sugranyes
- Department Child and Adolescent Psychiatry and Psychology, 2017SGR881 Institute of Neuroscience, Hospital Clinic Barcelona. CIBERSAM. August Pi i Sunyer Biomedical Research Institute (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Chao Suo
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Diana Tordesillas-Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander (Cantabria), Spain
- Advanced Computing and e-Science, Instituto de Física de Cantabria (UC-CSIC), Santander (Cantabria), Spain
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Kirsten Wedervang-Resell
- Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Laura A Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
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Pouwels PJW, Vriend C, Liu F, de Joode NT, Otaduy MCG, Pastorello B, Robertson FC, Venkatasubramanian G, Ipser J, Lee S, Batistuzzo MC, Hoexter MQ, Lochner C, Miguel EC, Narayanaswamy JC, Rao R, Janardhan Reddy YC, Shavitt RG, Sheshachala K, Stein DJ, van Balkom AJLM, Wall M, Simpson HB, van den Heuvel OA. Global multi-center and multi-modal magnetic resonance imaging study of obsessive-compulsive disorder: Harmonization and monitoring of protocols in healthy volunteers and phantoms. Int J Methods Psychiatr Res 2023; 32:e1931. [PMID: 35971639 PMCID: PMC9976605 DOI: 10.1002/mpr.1931] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 06/13/2022] [Accepted: 06/22/2022] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVES We describe the harmonized MRI acquisition and quality assessment of an ongoing global OCD study, with the aim to translate representative, well-powered neuroimaging findings in neuropsychiatric research to worldwide populations. METHODS We report on T1-weighted structural MRI, resting-state functional MRI, and multi-shell diffusion-weighted imaging of 140 healthy participants (28 per site), two traveling controls, and regular phantom scans. RESULTS Human image quality measures (IQMs) and outcome measures showed smaller within-site variation than between-site variation. Outcome measures were less variable than IQMs, especially for the traveling controls. Phantom IQMs were stable regarding geometry, SNR, and mean diffusivity, while fMRI fluctuation was more variable between sites. CONCLUSIONS Variation in IQMs persists, even for an a priori harmonized data acquisition protocol, but after pre-processing they have less of an impact on the outcome measures. Continuous monitoring IQMs per site is valuable to detect potential artifacts and outliers. The inclusion of both cases and healthy participants at each site remains mandatory.
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Affiliation(s)
- Petra J. W. Pouwels
- Department of Radiology and Nuclear MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
| | - Chris Vriend
- Department of PsychiatryDepartment of Anatomy and NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
| | - Feng Liu
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Niels T. de Joode
- Department of PsychiatryDepartment of Anatomy and NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
| | - Maria C. G. Otaduy
- Department of RadiologyLIM44, InstituteHospital Das Clinicas‐HCFMUSPUniversity of Sao Paulo Medical SchoolSao PauloBrazil
| | - Bruno Pastorello
- Department of RadiologyLIM44, InstituteHospital Das Clinicas‐HCFMUSPUniversity of Sao Paulo Medical SchoolSao PauloBrazil
| | - Frances C. Robertson
- Cape Universities Body Imaging CentreUniversity of Cape TownCape TownSouth Africa
| | | | - Jonathan Ipser
- Department of PsychiatrySAMRC Unit on Risk & Resilience in Mental DisordersNeuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - Seonjoo Lee
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Marcelo C. Batistuzzo
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
- Department of Methods and Techniques in PsychologyPontifical Catholic UniversitySao PauloSPBrazil
| | - Marcelo Q. Hoexter
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
| | - Christine Lochner
- Department of PsychiatrySAMRC Unit on Risk & Resilience in Mental DisordersStellenbosch UniversityCape TownSouth Africa
| | - Euripedes C. Miguel
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
| | | | - Rashmi Rao
- National Institute of Mental Health & Neurosciences (NIMHANS)BangaloreIndia
| | | | - Roseli G. Shavitt
- Obsessive‐Compulsive Spectrum Disorders ProgramDepartmento de Psiquiatria da Faculdade de MedicinaLIM23Hospital Das Clinicas HCFMUSPUniversidade de São PauloSao PauloSPBrazil
| | | | - Dan J. Stein
- Department of PsychiatrySAMRC Unit on Risk & Resilience in Mental DisordersNeuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - Anton J. L. M. van Balkom
- Department of PsychiatryAmsterdam UMCVrije UniversiteitAmsterdam Public Health Research InstituteSpecialised Mental Health CareAmsterdamThe Netherlands
| | - Melanie Wall
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Helen Blair Simpson
- Columbia University Irving Medical CenterColumbia UniversityNew York State Psychiatric InstituteNew YorkNYUSA
| | - Odile A. van den Heuvel
- Department of PsychiatryDepartment of Anatomy and NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdam NeuroscienceAmsterdamThe Netherlands
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48
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Dennis EL, Keleher F, Tate DF, Wilde EA. The Role of Neuroimaging in Evolving TBI Research and Clinical Practice. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.24.23286258. [PMID: 36865222 PMCID: PMC9980266 DOI: 10.1101/2023.02.24.23286258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2023]
Abstract
Neuroimaging technologies such as computed tomography (CT) and magnetic resonance imaging (MRI) have been widely adopted in the clinical diagnosis and management of traumatic brain injury (TBI), particularly at the more acute and severe levels of injury. Additionally, a number of advanced applications of MRI have been employed in TBI-related clinical research with great promise, and researchers have used these techniques to better understand underlying mechanisms, progression of secondary injury and tissue perturbation over time, and relation of focal and diffuse injury to later outcome. However, the acquisition and analysis time, the cost of these and other imaging modalities, and the need for specialized expertise have represented historical barriers in extending these tools in clinical practice. While group studies are important in detecting patterns, heterogeneity among patient presentation and limited sample sizes from which to compare individual level data to well-developed normative data have also played a role in the limited translatability of imaging to wider clinical application. Fortunately, the field of TBI has benefitted from increased public and scientific awareness of the prevalence and impact of TBI, particularly in head injury related to recent military conflicts and sport-related concussion. This awareness parallels an increase in federal funding in the United States and other countries allocated to investigation in these areas. In this article we summarize funding and publication trends since the mainstream adoption of imaging in TBI to elucidate evolving trends and priorities in the application of different techniques and patient populations. We also review recent and ongoing efforts to advance the field through promoting reproducibility, data sharing, big data analytic methods, and team science. Finally, we discuss international collaborative efforts to combine and harmonize neuroimaging, cognitive, and clinical data, both prospectively and retrospectively. Each of these represent unique, but related, efforts that facilitate closing gaps between the use of advanced imaging solely as a research tool and the use of it in clinical diagnosis, prognosis, and treatment planning and monitoring.
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Affiliation(s)
- Emily L Dennis
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT
| | - Finian Keleher
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT
| | - David F Tate
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT
| | - Elisabeth A Wilde
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT
- Baylor College of Medicine, Houston, TX
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49
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History of suicide attempt associated with amygdala and hippocampus changes among individuals with schizophrenia. Eur Arch Psychiatry Clin Neurosci 2023:10.1007/s00406-023-01554-5. [PMID: 36788147 DOI: 10.1007/s00406-023-01554-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 01/09/2023] [Indexed: 02/16/2023]
Abstract
Abnormalities in subcortical brain structures may reflect higher suicide risk in mood disorders, but less is known about its associations for schizophrenia. This cross-sectional imaging study aimed to explore whether the history of suicide attempts was associated with subcortical changes among individuals with schizophrenia. We recruited 44 individuals with schizophrenia and a history of suicide attempts (SZ-SA) and 44 individuals with schizophrenia but without a history of suicide attempts (SZ-NSA) and 44 healthy controls. Linear regression showed that SZ-SA had smaller volumes of the hippocampus (Cohen's d = -0.72), the amygdala (Cohen's d = -0.69), and some nuclei of the amygdala (Cohen's d, -0.57 to -0.72) than SZ-NSA after adjusting for age, sex, illness phase, and intracranial volume. There was no difference in the volume of the subfields of the hippocampus. It suggests the history of suicide attempts is associated with subcortical volume alterations in schizophrenia.
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50
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Harris AD, Amiri H, Bento M, Cohen R, Ching CRK, Cudalbu C, Dennis EL, Doose A, Ehrlich S, Kirov II, Mekle R, Oeltzschner G, Porges E, Souza R, Tam FI, Taylor B, Thompson PM, Quidé Y, Wilde EA, Williamson J, Lin AP, Bartnik-Olson B. Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations. Front Neurol 2023; 13:1045678. [PMID: 36686533 PMCID: PMC9845632 DOI: 10.3389/fneur.2022.1045678] [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: 09/15/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impact, however, has been limited due to small sample sizes and methodological variability in addition to intrinsic limitations of the method itself such as its sensitivity to motion. The lack of standardization from a data acquisition and data processing perspective makes it difficult to pool multiple studies and/or conduct multisite studies that are necessary for supporting clinically relevant findings. Based on the experience of the ENIGMA MRS work group and a review of the literature, this manuscript provides an overview of the current state of MRS data harmonization. Key factors that need to be taken into consideration when conducting both retrospective and prospective studies are described. These include (1) MRS acquisition issues such as pulse sequence, RF and B0 calibrations, echo time, and SNR; (2) data processing issues such as pre-processing steps, modeling, and quantitation; and (3) biological factors such as voxel location, age, sex, and pathology. Various approaches to MRS data harmonization are then described including meta-analysis, mega-analysis, linear modeling, ComBat and artificial intelligence approaches. The goal is to provide both novice and experienced readers with the necessary knowledge for conducting MRS data harmonization studies.
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Affiliation(s)
- Ashley D. Harris
- Department of Radiology, University of Calgary, Calgary, AB, Canada,Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Houshang Amiri
- Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
| | - Mariana Bento
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada,Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Ronald Cohen
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, Los Angeles, CA, United States
| | - Christina Cudalbu
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland,Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Emily L. Dennis
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, United States
| | - Arne Doose
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Ivan I. Kirov
- Department of Radiology, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY, United States
| | - Ralf Mekle
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Eric Porges
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Roberto Souza
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada,Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Friederike I. Tam
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Brian Taylor
- Division of Diagnostic Imaging, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, Los Angeles, CA, United States
| | - Yann Quidé
- School of Psychology, University of New South Wales (UNSW), Sydney, NSW, Australia
| | - Elisabeth A. Wilde
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, United States
| | - John Williamson
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Alexander P. Lin
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Brenda Bartnik-Olson
- Department of Radiology, Loma Linda University Medical Center, Loma Linda, CA, United States,*Correspondence: Brenda Bartnik-Olson ✉
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