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Li X, Wei W, Wang Q, Deng W, Li M, Ma X, Zeng J, Zhao L, Guo W, Hall MH, Li T. Identify Potential Causal Relationships Between Cortical Thickness, Mismatch Negativity, Neurocognition, and Psychosocial Functioning in Drug-Naïve First-Episode Psychosis Patients. Schizophr Bull 2024; 50:827-838. [PMID: 38635296 PMCID: PMC11283193 DOI: 10.1093/schbul/sbae026] [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: 04/19/2024]
Abstract
BACKGROUND Cortical thickness (CT) alterations, mismatch negativity (MMN) reductions, and cognitive deficits are robust findings in first-episode psychosis (FEP). However, most studies focused on medicated patients, leaving gaps in our understanding of the interrelationships between CT, MMN, neurocognition, and psychosocial functioning in unmedicated FEP. This study aimed to employ multiple mediation analysis to investigate potential pathways among these variables in unmedicated drug-naïve FEP. METHODS We enrolled 28 drug-naïve FEP and 34 age and sex-matched healthy controls. Clinical symptoms, neurocognition, psychosocial functioning, auditory duration MMN, and T1 structural magnetic resonance imaging data were collected. We measured CT in the superior temporal gyrus (STG), a primary MMN-generating region. RESULTS We found a significant negative correlation between MMN amplitude and bilateral CT of STG (CT_STG) in FEP (left: r = -.709, P < .001; right: r = -.612, P = .008). Multiple mediation models revealed that a thinner left STG cortex affected functioning through both direct (24.66%) and indirect effects (75.34%). In contrast, the effects of the right CT_STG on functioning were mainly mediated through MMN and neurocognitive pathways. CONCLUSIONS Bilateral CT_STG showed significant association with MMN, and MMN plays a mediating role between CT and cognition. Both MMN alone and its interaction with cognition mediated the effects of structural alterations on psychosocial function. The decline in overall function in FEP may stem from decreased CT_STG, leading to subsequent MMN deficits and neurocognitive dysfunction. These findings underline the crucial role of MMN in elucidating how subtle structural alterations can impact neurocognition and psychosocial function in FEP.
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Affiliation(s)
- Xiaojing Li
- Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
- Nanhu Brain-Computer Interface Institute, Hangzhou 311100, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Wei Wei
- Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
- Nanhu Brain-Computer Interface Institute, Hangzhou 311100, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Wei Deng
- Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
- Nanhu Brain-Computer Interface Institute, Hangzhou 311100, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Mingli Li
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Jinkun Zeng
- Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Wanjun Guo
- Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
- Nanhu Brain-Computer Interface Institute, Hangzhou 311100, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Mei-Hua Hall
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Tao Li
- Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
- Nanhu Brain-Computer Interface Institute, Hangzhou 311100, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, 1369 West Wenyi Road, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
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2
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Uyar Demir A, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Van Rheenen TE, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos SI, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TGM, Cheng W, Feng J. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm. Nat Commun 2024; 15:5996. [PMID: 39013848 PMCID: PMC11252381 DOI: 10.1038/s41467-024-50267-3] [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: 10/17/2023] [Accepted: 07/03/2024] [Indexed: 07/18/2024] Open
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Magdeburg, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- 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
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Gianfranco Spalletta
- 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
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, SYD, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, SYD, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Min Tae M Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, TO, Canada
- Centre for Addiction and Mental Health, TO, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, MEL, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- School of Data Science, Fudan University, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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Petric PS, Ifteni P, Popa AV, Teodorescu A. Cerebral Computed Tomographic Findings in Schizophrenia: Relationship to Second-Generation Antipsychotics and Hyperprolactinemia. Healthcare (Basel) 2024; 12:1343. [PMID: 38998877 PMCID: PMC11241017 DOI: 10.3390/healthcare12131343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/02/2024] [Accepted: 07/04/2024] [Indexed: 07/14/2024] Open
Abstract
Antipsychotic medications are essential for managing severe mental illnesses like schizophrenia, which impacts about 1% of the global population. Despite efficacy, in some cases, they can induce hyperprolactinemia, affecting roughly half of the patients. The prevalence of this condition varies with the specific medication used. Although prolactinomas are rare among schizophrenia patients, treating them with dopamine agonists poses conflicts with antipsychotic medication, necessitating careful monitoring and adjustments. The aim of this study was to explore the presence of brain tumors, prolactinomas, and other structural brain changes in schizophrenia patients treated with second-generation antipsychotics using cerebral computed tomography (CT) scans. We conducted a cross-sectional study involving 152 hospitalized patients diagnosed between 1 January 2020 and 31 March 2024. Evaluations included cerebral CT scans, prolactin level assessments, and the monitoring of side effects. Patients, with an average age of 42.79 years and an illness duration of 17.89 years, predominantly received olanzapine (46.05%) and risperidone (36.84%). Side effects, reported by 61.78% of patients, included tremors, dizziness, and weight gain. Abnormal prolactin levels were observed in 53.95% of patients, more prevalent in females on risperidone and in both genders on olanzapine. No prolactinomas were detected on CT scans. Managing hyperprolactinemia in schizophrenia patients undergoing antipsychotic therapy is essential to prevent long-term complications and to ensure treatment compliance.
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Affiliation(s)
- Paula Simina Petric
- Facultatea de Medicină, Universitatea Transilvania din Brașov, Bulevardul Eroilor 29, 500036 Brașov, Romania; (P.S.P.); (A.V.P.); (A.T.)
- Spitalul Clinic de Psihiatrie și Neurologie Brașov, Str. Prundului No. 7-9, 500123 Brașov, Romania
| | - Petru Ifteni
- Facultatea de Medicină, Universitatea Transilvania din Brașov, Bulevardul Eroilor 29, 500036 Brașov, Romania; (P.S.P.); (A.V.P.); (A.T.)
- Spitalul Clinic de Psihiatrie și Neurologie Brașov, Str. Prundului No. 7-9, 500123 Brașov, Romania
| | - Andreea Violeta Popa
- Facultatea de Medicină, Universitatea Transilvania din Brașov, Bulevardul Eroilor 29, 500036 Brașov, Romania; (P.S.P.); (A.V.P.); (A.T.)
- Spitalul Clinic de Psihiatrie și Neurologie Brașov, Str. Prundului No. 7-9, 500123 Brașov, Romania
| | - Andreea Teodorescu
- Facultatea de Medicină, Universitatea Transilvania din Brașov, Bulevardul Eroilor 29, 500036 Brașov, Romania; (P.S.P.); (A.V.P.); (A.T.)
- Spitalul Clinic de Psihiatrie și Neurologie Brașov, Str. Prundului No. 7-9, 500123 Brașov, Romania
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Reinen JM, Polosecki P, Castro E, Corcoran CM, Cecchi GA, Colibazzi T. Multimodal fusion of brain signals for robust prediction of psychosis transition. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:54. [PMID: 38773120 PMCID: PMC11109212 DOI: 10.1038/s41537-024-00464-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 03/15/2024] [Indexed: 05/23/2024]
Abstract
The prospective study of youths at clinical high risk (CHR) for psychosis, including neuroimaging, can identify neural signatures predictive of psychosis outcomes using algorithms that integrate complex information. Here, to identify risk and psychosis conversion, we implemented multiple kernel learning (MKL), a multimodal machine learning approach allowing patterns from each modality to inform each other. Baseline multimodal scans (n = 74, 11 converters) included structural, resting-state functional imaging, and diffusion-weighted data. Multimodal MKL outperformed unimodal models (AUC = 0.73 vs. 0.66 in predicting conversion). Moreover, patterns learned by MKL were robust to training set variations, suggesting it can identify cross-modality redundancies and synergies to stabilize the predictive pattern. We identified many predictors consistent with the literature, including frontal cortices, cingulate, thalamus, and striatum. This highlights the advantage of methods that leverage the complex pathophysiology of psychosis.
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Affiliation(s)
- Jenna M Reinen
- IBM T.J. Watson Research Center, Yorktown Heights, NY, USA.
| | | | - Eduardo Castro
- IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Cheryl M Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Tiziano Colibazzi
- Department of Psychiatry, The New York State Psychiatric Institute, Columbia College of Physicians and Surgeons, New York, NY, USA
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5
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Svancer P, Capek V, Skoch A, Kopecek M, Vochoskova K, Fialova M, Furstova P, Jakob L, Bakstein E, Kolenic M, Hlinka J, Knytl P, Spaniel F. Longitudinal assessment of ventricular volume trajectories in early-stage schizophrenia: evidence of both enlargement and shrinkage. BMC Psychiatry 2024; 24:309. [PMID: 38658884 PMCID: PMC11040899 DOI: 10.1186/s12888-024-05749-5] [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: 10/19/2023] [Accepted: 04/08/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Lateral ventricular enlargement represents a canonical morphometric finding in chronic patients with schizophrenia; however, longitudinal studies elucidating complex dynamic trajectories of ventricular volume change during critical early disease stages are sparse. METHODS We measured lateral ventricular volumes in 113 first-episode schizophrenia patients (FES) at baseline visit (11.7 months after illness onset, SD = 12.3) and 128 age- and sex-matched healthy controls (HC) using 3T MRI. MRI was then repeated in both FES and HC one year later. RESULTS Compared to controls, ventricular enlargement was identified in 18.6% of patients with FES (14.1% annual ventricular volume (VV) increase; 95%CI: 5.4; 33.1). The ventricular expansion correlated with the severity of PANSS-negative symptoms at one-year follow-up (p = 0.0078). Nevertheless, 16.8% of FES showed an opposite pattern of statistically significant ventricular shrinkage during ≈ one-year follow-up (-9.5% annual VV decrease; 95%CI: -23.7; -2.4). There were no differences in sex, illness duration, age of onset, duration of untreated psychosis, body mass index, the incidence of Schneiderian symptoms, or cumulative antipsychotic dose among the patient groups exhibiting ventricular enlargement, shrinkage, or no change in VV. CONCLUSION Both enlargement and ventricular shrinkage are equally present in the early stages of schizophrenia. The newly discovered early reduction of VV in a subgroup of patients emphasizes the need for further research to understand its mechanisms.
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Affiliation(s)
- Patrik Svancer
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Vaclav Capek
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Miloslav Kopecek
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Kristyna Vochoskova
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Marketa Fialova
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Petra Furstova
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Lea Jakob
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Eduard Bakstein
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Marian Kolenic
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jaroslav Hlinka
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Pavel Knytl
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic.
- Third Faculty of Medicine, Charles University, Prague, Czech Republic.
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6
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Tandon R, Nasrallah H, Akbarian S, Carpenter WT, DeLisi LE, Gaebel W, Green MF, Gur RE, Heckers S, Kane JM, Malaspina D, Meyer-Lindenberg A, Murray R, Owen M, Smoller JW, Yassin W, Keshavan M. The schizophrenia syndrome, circa 2024: What we know and how that informs its nature. Schizophr Res 2024; 264:1-28. [PMID: 38086109 DOI: 10.1016/j.schres.2023.11.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 03/01/2024]
Abstract
With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.
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Affiliation(s)
- Rajiv Tandon
- Department of Psychiatry, WMU Homer Stryker School of Medicine, Kalamazoo, MI 49008, United States of America.
| | - Henry Nasrallah
- Department of Psychiatry, University of Cincinnati College of Medicine Cincinnati, OH 45267, United States of America
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21201, United States of America
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance and Harvard Medical School, Cambridge, MA 02139, United States of America
| | - Wolfgang Gaebel
- Department of Psychiatry and Psychotherapy, LVR-Klinikum Dusseldorf, Heinrich-Heine University, Dusseldorf, Germany
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute of Neuroscience and Human Behavior, UCLA, Los Angeles, CA 90024, United States of America; Greater Los Angeles Veterans' Administration Healthcare System, United States of America
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States of America
| | - Stephan Heckers
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37232, United States of America
| | - John M Kane
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Glen Oaks, NY 11004, United States of America
| | - Dolores Malaspina
- Department of Psychiatry, Neuroscience, Genetics, and Genomics, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannhein/Heidelberg University, Mannheim, Germany
| | - Robin Murray
- Institute of Psychiatry, Psychology, and Neuroscience, Kings College, London, UK
| | - Michael Owen
- Centre for Neuropsychiatric Genetics and Genomics, and Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Jordan W Smoller
- Center for Precision Psychiatry, Department of Psychiatry, Psychiatric and Neurodevelopmental Unit, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States of America
| | - Walid Yassin
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
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O'Neill A, Dooley N, Roddy D, Healy C, Carey E, Frodl T, O'Hanlon E, Cannon M. Longitudinal hippocampal subfield development associated with psychotic experiences in young people. Transl Psychiatry 2024; 14:44. [PMID: 38245522 PMCID: PMC10799917 DOI: 10.1038/s41398-024-02746-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: 05/17/2023] [Revised: 12/21/2023] [Accepted: 01/08/2024] [Indexed: 01/22/2024] Open
Abstract
Hippocampal volumetric reductions are observed across the psychosis spectrum, with interest in the localisation of these reductions within the hippocampal subfields increasing. Deficits of the CA1 subfield in particular have been implicated in the neuropathophysiology of psychotic disorders. Investigating the trajectory of these abnormalities in healthy adolescents reporting sub-threshold psychotic experiences (PE) can provide insight into the neural mechanisms underlying psychotic symptoms without the potentially confounding effects of a formal disorder, or antipsychotic medication. In this novel investigation, a sample of 211 young people aged 11-13 participated initially in the Adolescent Brain Development study. PE classification was determined by expert consensus at each timepoint. Participants underwent neuroimaging at 3 timepoints, over 6 years. 78 participants with at least one scan were included in the final sample; 33 who met criteria for a definite PE at least once across all the timepoints (PE group), and 45 controls. Data from bilateral subfields of interest (CA1, CA2/3, CA4/DG, presubiculum and subiculum) were extracted for Linear Mixed Effects analyses. Before correction, subfield volumes were found to increase in the control group and decrease in the PE group for the right CA2 and CA2/3 subfields, with moderate to large effect sizes (d = -0.61, and d = -0.79, respectively). Before correction, right subiculum and left presubiculum volumes were reduced in the PE group compared to controls, regardless of time, with moderate effect sizes (d = -0.52, and d = -0.59, respectively). However, none of these effects survived correction. Severity of symptoms were not associated with any of the noted subfields. These findings provide novel insight to the discussion of the role of hippocampal subfield abnormalities in the pathophysiology underlying psychotic experiences.
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Affiliation(s)
- Aisling O'Neill
- Department of Psychology, St Patrick's Mental Health Services, Dublin, Ireland.
- Department of Psychiatry, RCSI University of Medicine and Health Sciences, St Stephens Green, Dublin, Ireland.
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
| | - Niamh Dooley
- Department of Psychiatry, RCSI University of Medicine and Health Sciences, St Stephens Green, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Darren Roddy
- Department of Psychiatry, RCSI University of Medicine and Health Sciences, St Stephens Green, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Colm Healy
- Department of Psychiatry, RCSI University of Medicine and Health Sciences, St Stephens Green, Dublin, Ireland
- Department of Medicine, University College Dublin, Dublin, Ireland
| | - Eleanor Carey
- Department of Psychiatry, RCSI University of Medicine and Health Sciences, St Stephens Green, Dublin, Ireland
| | - Thomas Frodl
- Department of Medicine, University College Dublin, Dublin, Ireland
- Klinik für Psychiatrie, Psychotherapie und Psychosomatik, Uniklinik RWTH Aachen, Aachen, Germany
| | - Erik O'Hanlon
- Department of Psychiatry, RCSI University of Medicine and Health Sciences, St Stephens Green, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Mary Cannon
- Department of Psychiatry, RCSI University of Medicine and Health Sciences, St Stephens Green, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
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8
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Bayar Kapici O, Kapici Y, Tekın A, Şırık M. A novel diagnosis method for schizophrenia based on globus pallidus data. Psychiatry Res Neuroimaging 2023; 336:111732. [PMID: 37922672 DOI: 10.1016/j.pscychresns.2023.111732] [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: 05/09/2023] [Revised: 08/25/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023]
Abstract
This research aims to diagnose schizophrenia with machine learning-based algorithms. Bayesian neural network, logistic regression, decision tree, k-nearest neighbor, and gaussian kernel classification techniques are investigated to diagnose schizophrenia with data from 125 persons. This study showed that left lateral ventricles and left globus pallidus volumes and their percentages in the brain were significantly lower than HCs in FEP patients. Using brain volumes, we were able to diagnose FEP with an accuracy of 73.6 % via logistic regression and with an accuracy of 86.4 % using the SVM kernel classifier method. Therefore, brain volumes can be used to diagnose FEP with the SVM kernel classifier method.
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Affiliation(s)
- Olga Bayar Kapici
- Department of Radiology, Adıyaman Training and Research Hospital, Adıyaman, Turkey
| | - Yaşar Kapici
- Department of Psychiatry, Kahta State Hospital, Adıyaman, Turkey.
| | - Atilla Tekın
- Department of Psychiatry, Adıyaman University Faculty of Medicine, Adıyaman, Turkey
| | - Mehmet Şırık
- Department of Radiology, Adıyaman University Faculty of Medicine, Adıyaman, Turkey
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9
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Chopra S, Segal A, Oldham S, Holmes A, Sabaroedin K, Orchard ER, Francey SM, O’Donoghue B, Cropley V, Nelson B, Graham J, Baldwin L, Tiego J, Yuen HP, Allott K, Alvarez-Jimenez M, Harrigan S, Fulcher BD, Aquino K, Pantelis C, Wood SJ, Bellgrove M, McGorry PD, Fornito A. Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis. JAMA Psychiatry 2023; 80:1246-1257. [PMID: 37728918 PMCID: PMC10512169 DOI: 10.1001/jamapsychiatry.2023.3293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 06/21/2023] [Indexed: 09/22/2023]
Abstract
Importance Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. Objective To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. Design, Settings, and Participants This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. Main Outcomes and Measures Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance. Results Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression. Conclusion and Relevance These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.
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Affiliation(s)
- Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Ashlea Segal
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Stuart Oldham
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Alexander Holmes
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Kristina Sabaroedin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Radiology, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Paediatrics, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Edwina R. Orchard
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Child Study Centre, Yale University, New Haven, Connecticut
| | - Shona M. Francey
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Brian O’Donoghue
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
| | - Barnaby Nelson
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jessica Graham
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lara Baldwin
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jeggan Tiego
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Hok Pan Yuen
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Kelly Allott
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Mario Alvarez-Jimenez
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Susy Harrigan
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Mental Health, Melbourne School of Global and Population Health, The University of Melbourne, Parkville, Victoria, Australian
| | - Ben D. Fulcher
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Kevin Aquino
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Centre for Complex Systems, University of Sydney, Sydney, New South Wales, Australia
| | - Christos Pantelis
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
- NorthWestern Mental Health, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Western Health Sunshine Hospital, St Albans, Victoria, Australia
| | - Stephen J. Wood
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- School of Psychology, University of Birmingham, Edgbaston, United Kingdom
| | - Mark Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
| | - Patrick D. McGorry
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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10
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Lodge DJ, Elam HB, Boley AM, Donegan JJ. Discrete hippocampal projections are differentially regulated by parvalbumin and somatostatin interneurons. Nat Commun 2023; 14:6653. [PMID: 37863893 PMCID: PMC10589277 DOI: 10.1038/s41467-023-42484-z] [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] [Received: 08/02/2022] [Accepted: 10/12/2023] [Indexed: 10/22/2023] Open
Abstract
People with schizophrenia show hyperactivity in the ventral hippocampus (vHipp) and we have previously demonstrated distinct behavioral roles for vHipp cell populations. Here, we test the hypothesis that parvalbumin (PV) and somatostatin (SST) interneurons differentially innervate and regulate hippocampal pyramidal neurons based on their projection target. First, we use eGRASP to show that PV-positive interneurons form a similar number of synaptic connections with pyramidal cells regardless of their projection target while SST-positive interneurons preferentially target nucleus accumbens (NAc) projections. To determine if these anatomical differences result in functional changes, we used in vivo opto-electrophysiology to show that SST cells also preferentially regulate the activity of NAc-projecting cells. These results suggest vHipp interneurons differentially regulate that vHipp neurons that project to the medial prefrontal cortex (mPFC) and NAc. Characterization of these cell populations may provide potential molecular targets for the treatment schizophrenia and other psychiatric disorders associated with vHipp dysfunction.
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Affiliation(s)
- Daniel J Lodge
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, Audie L. Murphy Division, San Antonio, TX, USA
| | - Hannah B Elam
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, Audie L. Murphy Division, San Antonio, TX, USA
| | - Angela M Boley
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, Audie L. Murphy Division, San Antonio, TX, USA
| | - Jennifer J Donegan
- Department of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX, 78229, USA.
- Department of Psychiatry and Behavioral Sciences and Center for Early Life Adversity, Department of Neuroscience, Dell Medical School at the University of Texas at Austin, Austin, TX, 78712, USA.
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Demir AU, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Rheenen TEV, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos S, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TG, Cheng W, Feng J. Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.11.23296862. [PMID: 37873296 PMCID: PMC10593004 DOI: 10.1101/2023.10.11.23296862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, 305-8575, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Frederike Stein
- 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
| | - Lea Teutenberg
- 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
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L. Rodrigue
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Gianfranco Spalletta
- 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
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R. Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S. Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Min Tae M. Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Centre for Addiction and Mental Health, Toronto, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, California, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Sophia Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi’an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, 92697-3950, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | | | | | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- School of Data Science, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
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Hua JPY, Loewy RL, Stuart B, Fryer SL, Niendam TA, Carter CS, Vinogradov S, Mathalon DH. Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia. Psychiatry Res Neuroimaging 2023; 332:111653. [PMID: 37121090 PMCID: PMC10362971 DOI: 10.1016/j.pscychresns.2023.111653] [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: 01/23/2023] [Revised: 03/27/2023] [Accepted: 04/18/2023] [Indexed: 05/02/2023]
Abstract
Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.
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Affiliation(s)
- Jessica P Y Hua
- Sierra Pacific Mental Illness Research Education and Clinical Centers, San Francisco VA Medical Center, and the University of California, San Francisco, CA, United States; Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States; Department of Psychological Sciences, University of Missouri, Columbia, 65211, MO, United States
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States
| | - Barbara Stuart
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States
| | - Susanna L Fryer
- Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States
| | - Tara A Niendam
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, 95616, CA, United States
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, 95616, CA, United States
| | - Sophia Vinogradov
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, 55455, MN, United States
| | - Daniel H Mathalon
- Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States.
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13
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Abbas MS, Nassar ST, Tasha T, Desai A, Bajgain A, Ali A, Dutta C, Pasha K, Paul S, Venugopal S. Exercise as an Adjuvant Treatment of Schizophrenia: A Review. Cureus 2023; 15:e42084. [PMID: 37602139 PMCID: PMC10434720 DOI: 10.7759/cureus.42084] [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: 08/25/2022] [Accepted: 07/17/2023] [Indexed: 08/22/2023] Open
Abstract
Schizophrenia is a chronic debilitating condition associated with impaired social functioning, memory, and executive functioning. To date, we are still unsure about the exact etiology of schizophrenia, but there are many factors, such as genetics, diminished hippocampal volume, and imbalance of neurotransmitters, that lead to the pathogenies of the disease. Antipsychotics are the most effective treatment option for schizophrenia so far, yet they are associated with a wide array of side effects, ranging from extrapyramidal side effects to conditions, such as metabolic syndrome. Exercise has been shown to increase neural connections in the brain, which can improve cognition and memory. This literature review focuses on the signs and symptoms of schizophrenia, its treatment options, and how exercise can help with some of the symptoms of schizophrenia, especially the negative symptoms that are least effectively treated by antipsychotics.
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Affiliation(s)
- Muhammad S Abbas
- Psychiatry, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Sondos T Nassar
- Medicine and Surgery, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Tasniem Tasha
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Anjali Desai
- Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Anjana Bajgain
- Division of Research & Academic Affairs, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Asna Ali
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Chandrani Dutta
- Family Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Khadija Pasha
- Pediatrics, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Salomi Paul
- Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Sathish Venugopal
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
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14
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Chen VCH, Chuang W, Chen CW, Tsai YH, McIntyre RS, Weng JC. Detecting microstructural alterations of cerebral white matter associated with breast cancer and chemotherapy revealed by generalized q-sampling MRI. Front Psychiatry 2023; 14:1161246. [PMID: 37363171 PMCID: PMC10289548 DOI: 10.3389/fpsyt.2023.1161246] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 05/22/2023] [Indexed: 06/28/2023] Open
Abstract
Objective Previous studies have discussed the impact of chemotherapy on the brain microstructure. There is no evidence of the impact regarding cancer-related psychiatric comorbidity on cancer survivors. We aimed to evaluate the impact of both chemotherapy and mental health problem on brain microstructural alterations and consequent cognitive dysfunction in breast cancer survivors. Methods In this cross-sectional study conducted in a tertiary center, data from 125 female breast cancer survivors who had not received chemotherapy (BB = 65; 49.86 ± 8.23 years) and had received chemotherapy (BA = 60; 49.82 ± 7.89 years) as well as from 71 age-matched healthy controls (47.18 ± 8.08 years) was collected. Chemotherapeutic agents used were docetaxel and epirubicin. We used neuropsychological testing and questionnaire to evaluate psychiatric comorbidity, cognitive dysfunction as well as generalized sampling imaging (GQI) and graph theoretical analysis (GTA) to detect microstructural alterations in the brain. Findings Cross-comparison between groups revealed that neurotoxicity caused by chemotherapy and cancer-related psychiatric comorbidity may affect the corpus callosum and middle frontal gyrus. In addition, GQI indices were correlated with the testing scores of cognitive function, quality of life, anxiety, and depression. Furthermore, weaker connections between brain regions and lower segregated ability were found in the post-treatment group. Conclusion This study suggests that chemotherapy and cancer-related mental health problem both play an important role in the development of white matter alterations and cognitive dysfunction.
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Affiliation(s)
- Vincent Chin-Hung Chen
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Wei Chuang
- Department of Medical Imaging and Radiological Sciences, Department of Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan
| | - Chien-Wei Chen
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Yuan-Hsiung Tsai
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Roger S. McIntyre
- Mood Disorder Psychopharmacology Unit, Department of Psychiatry, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Departments of Psychiatry and Pharmacology, University of Toronto, Toronto, ON, Canada
| | - Jun-Cheng Weng
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan
- Department of Medical Imaging and Radiological Sciences, Department of Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan
- Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan
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15
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Adamu MJ, Qiang L, Nyatega CO, Younis A, Kawuwa HB, Jabire AH, Saminu S. Unraveling the pathophysiology of schizophrenia: insights from structural magnetic resonance imaging studies. Front Psychiatry 2023; 14:1188603. [PMID: 37275974 PMCID: PMC10236951 DOI: 10.3389/fpsyt.2023.1188603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 04/20/2023] [Indexed: 06/07/2023] Open
Abstract
Background Schizophrenia affects about 1% of the global population. In addition to the complex etiology, linking this illness to genetic, environmental, and neurobiological factors, the dynamic experiences associated with this disease, such as experiences of delusions, hallucinations, disorganized thinking, and abnormal behaviors, limit neurological consensuses regarding mechanisms underlying this disease. Methods In this study, we recruited 72 patients with schizophrenia and 74 healthy individuals matched by age and sex to investigate the structural brain changes that may serve as prognostic biomarkers, indicating evidence of neural dysfunction underlying schizophrenia and subsequent cognitive and behavioral deficits. We used voxel-based morphometry (VBM) to determine these changes in the three tissue structures: the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). For both image processing and statistical analysis, we used statistical parametric mapping (SPM). Results Our results show that patients with schizophrenia exhibited a significant volume reduction in both GM and WM. In particular, GM volume reductions were more evident in the frontal, temporal, limbic, and parietal lobe, similarly the WM volume reductions were predominantly in the frontal, temporal, and limbic lobe. In addition, patients with schizophrenia demonstrated a significant increase in the CSF volume in the left third and lateral ventricle regions. Conclusion This VBM study supports existing research showing that schizophrenia is associated with alterations in brain structure, including gray and white matter, and cerebrospinal fluid volume. These findings provide insights into the neurobiology of schizophrenia and may inform the development of more effective diagnostic and therapeutic approaches.
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Affiliation(s)
- Mohammed Jajere Adamu
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
- Department of Computer Science, Yobe State University, Damaturu, Nigeria
| | - Li Qiang
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
| | - Charles Okanda Nyatega
- Department of Information and Communication Engineering, School of Electrical and Information Engineering, Tianjin University, Tianjin, China
- Department of Electronics and Telecommunication Engineering, Mbeya University of Science and Technology, Mbeya, Tanzania
| | - Ayesha Younis
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
| | - Halima Bello Kawuwa
- Department of Biomedical Engineering and Scientific Instruments, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Adamu Halilu Jabire
- Department of Electrical and Electronics Engineering, Taraba State University, Jalingo, Nigeria
| | - Sani Saminu
- Department of Biomedical Engineering, University of Ilorin, Ilorin, Nigeria
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16
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Badarnee M, Wen Z, Nassar N, Milad MR. Gray matter associations with extinction-induced neural activation in patients with anxiety disorders. J Psychiatr Res 2023; 162:180-186. [PMID: 37167838 DOI: 10.1016/j.jpsychires.2023.05.015] [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] [Received: 01/17/2023] [Revised: 04/17/2023] [Accepted: 05/01/2023] [Indexed: 05/13/2023]
Abstract
The relationship between structural characteristics and extinction-induced brain activations in anxiety disorders (ANX) remains a space for greater exploration. In this study, we assessed gray matter volume (GMV) and its associated functional activations during fear extinction memory recall in an ANX cohort. We performed voxel-based morphometry analysis to examine GMVs from ANX (n = 92) and controls (n = 73). We further examined the correlation between GMVs and extinction-induced neural activations during recall across groups. In the patients' group, we observed decreased GMV in the anterior hippocampus and increased GMV in the dorsolateral prefrontal cortex (dlPFC). Hippocampal volume was positively correlated with ventromedial prefrontal cortex activation in healthy controls, while it was negatively correlated with dorsal anterior cingulate cortex (dACC) activation in ANX. The dlPFC volume was positively correlated with activations of dACC, pre- and post-central gyrus, and supramarginal gyrus only in healthy controls. Therefore, the link between structural and functional imbalance within the hippocampus and dlPFC might contribute to the pathophysiology of ANX. In the controls, the relationship between structural variance in the hippocampus and dlPFC and extinction-induced neural activations is consistent with a greater ability to regulate fear responding; associations that were absent in the ANX cohort. Furthermore, our findings of structure-function abnormalities within key nodes of emotional homeostasis in ANX point to dlPFC as a potential neural node to target using neuromodulation tools.
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Affiliation(s)
- Muhammad Badarnee
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Zhenfu Wen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Noor Nassar
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Mohammed R Milad
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA; Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA; Nathan Kline Institute for Psychiatric Research, Rockland, NY, USA.
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17
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Alexandros Lalousis P, Wood S, Reniers R, Schmaal L, Azam H, Mazziota A, Saeed H, Wragg C, Upthegrove R. Transdiagnostic structural neuroimaging features in depression and psychosis: A systematic review. Neuroimage Clin 2023; 38:103388. [PMID: 37031636 PMCID: PMC10120394 DOI: 10.1016/j.nicl.2023.103388] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 03/22/2023] [Accepted: 03/24/2023] [Indexed: 03/31/2023]
Abstract
BACKGROUND Previous research suggests that there may be similarities in structural brain changes seen in patients with depression and psychosis compared to healthy controls. However, there is yet no systematic review collating studies comparing structural brain changes in depression and psychosis. Establishing shared and specific neuroanatomical features could aid the investigation of underlying biological processes. AIMS To identify structural neuroimaging similarities and differences between patients with depression and psychosis. METHOD We searched PubMed, PsychInfo, Embase, NICE Evidence, Medline and the Cochrane Library were searched from inception to 30/06/2021 using relevant subject headings (controlled vocabularies) and search syntax. Papers were assessed for quality using the Newcastle-Ottawa Scale. RESULTS Five-hundred and twenty papers were retrieved, seven met inclusion criteria. In narrative collation of results, grey matter volume (GMV) reductions were found in the medial frontal gyrus (MFG), hippocampus and left-sided posterior subgenual prefrontal cortex in both psychosis and depression. GMV reductions affected more brain regions in psychosis, including in the insula and thalamus. White matter volume (WMV) decline was found in both depression and psychosis. Reduced fractional anisotropy (FA) was more commonly seen in depression. CONCLUSIONS Our results suggest potential transdiagnostic patterns of GMV and WMV reductions in areas including the MFG, hippocampus, and left-sided posterior subgenual prefrontal cortex. These could be investigated as a future biomarker of transdiagnostic signature across mental illnesses. However, due to the limited number and poor quality of studies future research in large samples and harmonised imaging data is first needed.
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Affiliation(s)
- Paris Alexandros Lalousis
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, United Kingdom.
| | - Stephen Wood
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, United Kingdom; Orygen, the National Centre of Excellence in Youth Mental Health, Melbourne, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, Australia
| | - Renate Reniers
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, United Kingdom
| | - Lianne Schmaal
- Orygen, the National Centre of Excellence in Youth Mental Health, Melbourne, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, Australia
| | - Hannah Azam
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom
| | - Antonella Mazziota
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom
| | - Hasson Saeed
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom
| | - Charlotte Wragg
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham B15 2SA, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, United Kingdom
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18
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Xu X, Li Q, Qian Y, Cai H, Zhang C, Zhao W, Zhu J, Yu Y. Genetic mechanisms underlying gray matter volume changes in patients with drug-naive first-episode schizophrenia. Cereb Cortex 2023; 33:2328-2341. [PMID: 35640648 DOI: 10.1093/cercor/bhac211] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Brain structural damage is a typical feature of schizophrenia. Investigating such disease phenotype in patients with drug-naive first-episode schizophrenia (DFSZ) may exclude the confounds of antipsychotics and illness chronicity. However, small sample sizes and marked clinical heterogeneity have precluded definitive identification of gray matter volume (GMV) changes in DFSZ as well as their underlying genetic mechanisms. Here, GMV changes in DFSZ were assessed using a neuroimaging meta-analysis of 19 original studies, including 605 patients and 637 controls. Gene expression data were derived from the Allen Human Brain Atlas and processed with a newly proposed standardized pipeline. Then, we used transcriptome-neuroimaging spatial correlations to identify genes associated with GMV changes in DFSZ, followed by a set of gene functional feature analyses. Meta-analysis revealed consistent GMV reduction in the right superior temporal gyrus, right insula and left inferior temporal gyrus in DFSZ. Moreover, we found that these GMV changes were spatially correlated with expression levels of 1,201 genes, which exhibited a wide range of functional features. Our findings may provide important insights into the genetic mechanisms underlying brain morphological abnormality in schizophrenia.
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Affiliation(s)
- Xiaotao Xu
- Department of Radiology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei 230012, China.,Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Qian Li
- Department of Radiology, Chaohu Hospital of Anhui Medical University, Hefei 238000, China.,Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Cun Zhang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Wenming Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China.,Department of Radiology, Chaohu Hospital of Anhui Medical University, Hefei 238000, China.,Department of Radiology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei 230012, China
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19
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Glutamatergic dysfunction leads to a hyper-dopaminergic phenotype through deficits in short-term habituation: a mechanism for aberrant salience. Mol Psychiatry 2023; 28:579-587. [PMID: 36460723 PMCID: PMC9908551 DOI: 10.1038/s41380-022-01861-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 10/19/2022] [Accepted: 10/28/2022] [Indexed: 12/05/2022]
Abstract
Psychosis in disorders like schizophrenia is commonly associated with aberrant salience and elevated striatal dopamine. However, the underlying cause(s) of this hyper-dopaminergic state remain elusive. Various lines of evidence point to glutamatergic dysfunction and impairments in synaptic plasticity in the etiology of schizophrenia, including deficits associated with the GluA1 AMPAR subunit. GluA1 knockout (Gria1-/-) mice provide a model of impaired synaptic plasticity in schizophrenia and exhibit a selective deficit in a form of short-term memory which underlies short-term habituation. As such, these mice are unable to reduce attention to recently presented stimuli. In this study we used fast-scan cyclic voltammetry to measure phasic dopamine responses in the nucleus accumbens of Gria1-/- mice to determine whether this behavioral phenotype might be a key driver of a hyper-dopaminergic state. There was no effect of GluA1 deletion on electrically-evoked dopamine responses in anaesthetized mice, demonstrating normal endogenous release properties of dopamine neurons in Gria1-/- mice. Furthermore, dopamine signals were initially similar in Gria1-/- mice compared to controls in response to both sucrose rewards and neutral light stimuli. They were also equally sensitive to changes in the magnitude of delivered rewards. In contrast, however, these stimulus-evoked dopamine signals failed to habituate with repeated presentations in Gria1-/- mice, resulting in a task-relevant, hyper-dopaminergic phenotype. Thus, here we show that GluA1 dysfunction, resulting in impaired short-term habituation, is a key driver of enhanced striatal dopamine responses, which may be an important contributor to aberrant salience and psychosis in psychiatric disorders like schizophrenia.
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20
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Xiong Y, Ye C, Sun R, Chen Y, Zhong X, Zhang J, Zhong Z, Chen H, Huang M. Disrupted Balance of Gray Matter Volume and Directed Functional Connectivity in Mild Cognitive Impairment and Alzheimer's Disease. Curr Alzheimer Res 2023; 20:161-174. [PMID: 37278043 PMCID: PMC10514512 DOI: 10.2174/1567205020666230602144659] [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] [Received: 11/17/2022] [Revised: 03/11/2023] [Accepted: 04/04/2023] [Indexed: 06/07/2023]
Abstract
BACKGROUND Alterations in functional connectivity have been demonstrated in Alzheimer's disease (AD), an age-progressive neurodegenerative disorder that affects cognitive function; however, directional information flow has never been analyzed. OBJECTIVE This study aimed to determine changes in resting-state directional functional connectivity measured using a novel approach, granger causality density (GCD), in patients with AD, and mild cognitive impairment (MCI) and explore novel neuroimaging biomarkers for cognitive decline detection. METHODS In this study, structural MRI, resting-state functional magnetic resonance imaging, and neuropsychological data of 48 Alzheimer's Disease Neuroimaging Initiative participants were analyzed, comprising 16 patients with AD, 16 with MCI, and 16 normal controls. Volume-based morphometry (VBM) and GCD were used to calculate the voxel-based gray matter (GM) volumes and directed functional connectivity of the brain. We made full use of voxel-based between-group comparisons of VBM and GCD values to identify specific regions with significant alterations. In addition, Pearson's correlation analysis was conducted between directed functional connectivity and several clinical variables. Furthermore, receiver operating characteristic (ROC) analysis related to classification was performed in combination with VBM and GCD. RESULTS In patients with cognitive decline, abnormal VBM and GCD (involving inflow and outflow of GCD) were noted in default mode network (DMN)-related areas and the cerebellum. GCD in the DMN midline core system, hippocampus, and cerebellum was closely correlated with the Mini- Mental State Examination and Functional Activities Questionnaire scores. In the ROC analysis combining VBM with GCD, the neuroimaging biomarker in the cerebellum was optimal for the early detection of MCI, whereas the precuneus was the best in predicting cognitive decline progression and AD diagnosis. CONCLUSION Changes in GM volume and directed functional connectivity may reflect the mechanism of cognitive decline. This discovery could improve our understanding of the pathology of AD and MCI and provide available neuroimaging markers for the early detection, progression, and diagnosis of AD and MCI.
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Affiliation(s)
- Yu Xiong
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Chenghui Ye
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Ruxin Sun
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Ying Chen
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Xiaochun Zhong
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Jiaqi Zhang
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Zhanhua Zhong
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Hongda Chen
- Department of Traditional Chinese Medicine, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Min Huang
- Department of Neurology, the Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518107, China
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21
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Uenishi S, Tamaki A, Yamada S, Yasuda K, Ikeda N, Mizutani-Tiebel Y, Keeser D, Padberg F, Tsuji T, Kimoto S, Takahashi S. Computational modeling of electric fields for prefrontal tDCS across patients with schizophrenia and mood disorders. Psychiatry Res Neuroimaging 2022; 326:111547. [PMID: 36240572 DOI: 10.1016/j.pscychresns.2022.111547] [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: 10/25/2021] [Revised: 07/30/2022] [Accepted: 10/01/2022] [Indexed: 02/25/2023]
Abstract
This cross-diagnostic study aims to computationally model electric field (efield) for prefrontal transcranial direct current stimulation in mood disorders and schizophrenia. Enrolled were patients with major depressive disorder (n = 23), bipolar disorder (n = 24), schizophrenia (n = 23), and healthy controls (n = 23). The efield was simulated using SimNIBS software (ver.2.1.1). Electrodes were placed at the left and right prefrontal areas and the current intensity was set to 2 mA intensity. Schizophrenia and major depressive disorder groups showed significantly lower 99.5th percentile efield strength than healthy controls. In voxel-wise analysis, patients with schizophrenia showed a significant reduction of simulated efield strength in the bilateral frontal lobe, cerebellum and brain stem compared with healthy controls. Among the patients with schizophrenia, reduction of simulated efield strength was not significantly correlated with psychiatric symptoms or global functioning. The patients with bipolar disorder showed no significant difference in simulated efield strength compared with healthy controls, and there was no significant difference between the clinical groups. Our results suggest attenuated electrophysiological response to transcranial direct current stimulation to the prefrontal cortex in patients with schizophrenia, and to some extent in patients with major depressive disorder.
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Affiliation(s)
- Shinya Uenishi
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan; Department of Psychiatry, Hidaka Hospital, Gobo, Japan.
| | - Atsushi Tamaki
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan; Department of Psychiatry, Hidaka Hospital, Gobo, Japan
| | - Shinichi Yamada
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Kasumi Yasuda
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Natsuko Ikeda
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan; Department of Psychiatry, Wakayama Prefectural Mental Health Care Center, Aridagawa, Japan
| | - Yuki Mizutani-Tiebel
- Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Munich, Germany; Department of Radiology, University Hospital LMU Munich, Munich, Germany
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Munich, Germany
| | - Tomikimi Tsuji
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Sohei Kimoto
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Shun Takahashi
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan; Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan; Graduate School of Rehabilitation Science, Osaka Metropolitan University, Habikino, Japan; Clinical Research and Education Center, Asakayama General Hospital, Sakai, Japan
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22
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Relevance of interactions between dopamine and glutamate neurotransmission in schizophrenia. Mol Psychiatry 2022; 27:3583-3591. [PMID: 35681081 PMCID: PMC9712151 DOI: 10.1038/s41380-022-01649-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/16/2022] [Accepted: 05/25/2022] [Indexed: 02/08/2023]
Abstract
Dopamine (DA) and glutamate neurotransmission are strongly implicated in schizophrenia pathophysiology. While most studies focus on contributions of neurons that release only DA or glutamate, neither DA nor glutamate models alone recapitulate the full spectrum of schizophrenia pathophysiology. Similarly, therapeutic strategies limited to either system cannot effectively treat all three major symptom domains of schizophrenia: positive, negative, and cognitive symptoms. Increasing evidence suggests extensive interactions between the DA and glutamate systems and more effective treatments may therefore require the targeting of both DA and glutamate signaling. This offers the possibility that disrupting DA-glutamate circuitry between these two systems, particularly in the striatum and forebrain, culminate in schizophrenia pathophysiology. Yet, the mechanisms behind these interactions and their contributions to schizophrenia remain unclear. In addition to circuit- or system-level interactions between neurons that solely release either DA or glutamate, here we posit that functional alterations involving a subpopulation of neurons that co-release both DA and glutamate provide a novel point of integration between DA and glutamate systems, offering a key missing link in our understanding of schizophrenia pathophysiology. Better understanding of mechanisms underlying DA/glutamate co-release from these neurons may therefore shed new light on schizophrenia pathophysiology and lead to more effective therapeutics.
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23
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Vanes LD, Murray RM, Nosarti C. Adult outcome of preterm birth: Implications for neurodevelopmental theories of psychosis. Schizophr Res 2022; 247:41-54. [PMID: 34006427 DOI: 10.1016/j.schres.2021.04.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/19/2021] [Accepted: 04/21/2021] [Indexed: 12/22/2022]
Abstract
Preterm birth is associated with an elevated risk of developmental and adult psychiatric disorders, including psychosis. In this review, we evaluate the implications of neurodevelopmental, cognitive, motor, and social sequelae of preterm birth for developing psychosis, with an emphasis on outcomes observed in adulthood. Abnormal brain development precipitated by early exposure to the extra-uterine environment, and exacerbated by neuroinflammation, neonatal brain injury, and genetic vulnerability, can result in alterations of brain structure and function persisting into adulthood. These alterations, including abnormal regional brain volumes and white matter macro- and micro-structure, can critically impair functional (e.g. frontoparietal and thalamocortical) network connectivity in a manner characteristic of psychotic illness. The resulting executive, social, and motor dysfunctions may constitute the basis for behavioural vulnerability ultimately giving rise to psychotic symptomatology. There are many pathways to psychosis, but elucidating more precisely the mechanisms whereby preterm birth increases risk may shed light on that route consequent upon early neurodevelopmental insult.
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Affiliation(s)
- Lucy D Vanes
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
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Maurus I, Röll L, Keeser D, Karali T, Papazov B, Hasan A, Schmitt A, Papazova I, Lembeck M, Hirjak D, Thieme CE, Sykorova E, Münz S, Seitz V, Greska D, Campana M, Wagner E, Löhrs L, Pömsl J, Roeh A, Malchow B, Keller-Varady K, Ertl-Wagner B, Stöcklein S, Meyer-Lindenberg A, Falkai P. Associations between aerobic fitness, negative symptoms, cognitive deficits and brain structure in schizophrenia-a cross-sectional study. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:63. [PMID: 35918344 PMCID: PMC9345912 DOI: 10.1038/s41537-022-00269-1] [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] [Received: 03/03/2022] [Accepted: 07/12/2022] [Indexed: 11/21/2022]
Abstract
Negative symptoms and cognitive deficits are common in individuals with schizophrenia, greatly affect their outcome, and have been associated with alterations in cerebral gray and white matter volume (GMV, WMV). In the last decade, aerobic endurance training has emerged as a promising intervention to alleviate these symptoms and improved aerobic fitness has been suggested as a key moderator variable. In the present study, we investigated, whether aerobic fitness is associated with fewer cognitive deficits and negative symptoms and with GMVs and WMVs in individuals with schizophrenia in a cross-sectional design. In the largest study to date on the implications of fitness in individuals with schizophrenia, 111 participants at two centers underwent assessments of negative symptoms, cognitive functioning, and aerobic fitness and 69 underwent additional structural magnetic resonance imaging. Multilevel Bayesian partial correlations were computed to quantify relationships between the variables of interest. The main finding was a positive association of aerobic fitness with right hippocampal GMV and WMVs in parahippocampal and several cerebellar regions. We found limited evidence for an association of aerobic fitness with cognitive functioning and negative symptoms. In summary, our results strengthen the notion that aerobic fitness and hippocampal plasticity are interrelated which holds implications for the design of exercise interventions in individuals with schizophrenia.
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Affiliation(s)
- Isabel Maurus
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany.
| | - Lukas Röll
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- NeuroImaging Core Unit Munich (NICUM), University Hospital LMU, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- NeuroImaging Core Unit Munich (NICUM), University Hospital LMU, Munich, Germany
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Temmuz Karali
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Boris Papazov
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Alkomiet Hasan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Bezirkskrankenhaus Augsburg, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Andrea Schmitt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Laboratory of Neuroscience (LIM27), Institute of Psychiatry, University of Sao Paulo, São Paulo, Brazil
| | - Irina Papazova
- Department of Psychiatry, Psychotherapy and Psychosomatics, Bezirkskrankenhaus Augsburg, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Moritz Lembeck
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Dusan Hirjak
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Cristina E Thieme
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Eliska Sykorova
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Susanne Münz
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Valentina Seitz
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - David Greska
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Mattia Campana
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Elias Wagner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Lisa Löhrs
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Johannes Pömsl
- Department of Psychiatry and Psychotherapy, Medical Faculty, Technical University of Munich, University Hospital Klinikum rechts der Isar, Munich, Germany
| | - Astrid Roeh
- Department of Psychiatry, Psychotherapy and Psychosomatics, Bezirkskrankenhaus Augsburg, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Berend Malchow
- Department of Psychiatry and Psychotherapy, University Hospital Göttingen, Göttingen, Germany
| | | | - Birgit Ertl-Wagner
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
- Department of Medical Imaging, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Sophia Stöcklein
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Andreas Meyer-Lindenberg
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
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A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer's disease. COMMUNICATIONS MEDICINE 2022; 2:70. [PMID: 35759330 PMCID: PMC9209493 DOI: 10.1038/s43856-022-00133-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 05/24/2022] [Indexed: 01/12/2023] Open
Abstract
Background Alzheimer's disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care. Methods We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). Results The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer's related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype. Conclusions This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.
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Schaub N, Ammann N, Conring F, Müller T, Federspiel A, Wiest R, Hoepner R, Stegmayer K, Walther S. Effect of Season of Birth on Hippocampus Volume in a Transdiagnostic Sample of Patients With Depression and Schizophrenia. Front Hum Neurosci 2022; 16:877461. [PMID: 35769255 PMCID: PMC9234120 DOI: 10.3389/fnhum.2022.877461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/17/2022] [Indexed: 11/13/2022] Open
Abstract
Psychiatric disorders share an excess of seasonal birth in winter and spring, suggesting an increase of neurodevelopmental risks. Evidence suggests season of birth can serve as a proxy of harmful environmental factors. Given that prenatal exposure of these factors may trigger pathologic processes in the neurodevelopment, they may consequently lead to brain volume alterations. Here we tested the effects of season of birth on gray matter volume in a transdiagnostic sample of patients with schizophrenia and depression compared to healthy controls (n = 192). We found a significant effect of season of birth on gray matter volume with reduced right hippocampal volume in summer-born compared to winter-born patients with depression. In addition, the volume of the right hippocampus was reduced independent from season of birth in schizophrenia. Our results support the potential impact of season of birth on hippocampal volume in depression.
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Affiliation(s)
- Nora Schaub
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Nina Ammann
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Frauke Conring
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Thomas Müller
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Andrea Federspiel
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Roland Wiest
- Support Center of Advanced Neuroimaging (SCAN), Inselspital, University Institute of Diagnostic and Interventional Neuroradiology, Bern, Switzerland
| | - Robert Hoepner
- Department of Neurology, Inselspital, University Hospital and University of Bern, Bern, Switzerland
| | - Katharina Stegmayer
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
- *Correspondence: Katharina Stegmayer,
| | - Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
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Bernardo M, Anmella G, Verdolini N, Saiz-Masvidal C, Casals S, Contreras F, Garrido I, Pérez F, Safont G, Mas S, Rodriguez N, Meseguer A, Pons-Cabrera MT, Vieta E, Amoretti S. Assessing cognitive reserve outcomes and biomarkers in first episode of psychosis: rationale, objectives, protocol and preliminary results of the CRASH Project. REVISTA DE PSIQUIATRIA Y SALUD MENTAL 2022. [DOI: 10.1016/j.rpsm.2022.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Demro C, Shen C, Hendrickson TJ, Arend JL, Disner SG, Sponheim SR. Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins. Front Aging Neurosci 2022; 14:872867. [PMID: 35527740 PMCID: PMC9074783 DOI: 10.3389/fnagi.2022.872867] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 03/11/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.
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Affiliation(s)
- Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Chen Shen
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | | | - Jessica L. Arend
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Seth G. Disner
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, United States
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, United States
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Ren X, Zhao X, Li J, Liu Y, Ren Y, Pruessner JC, Yang J. The Hippocampal-Ventral Medial Prefrontal Cortex Neurocircuitry Involvement in the Association of Daily Life Stress With Acute Perceived Stress and Cortisol Responses. Psychosom Med 2022; 84:276-287. [PMID: 35149637 DOI: 10.1097/psy.0000000000001058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Daily life stressors include everyday irritants, hassles, and inconveniences, such as problems in traffic and unexpected work deadlines. A growing body of research has suggested higher daily stress is associated with blunted cortisol response to acute psychosocial stressors. However, so far, the neural mechanism underlying this association has not been elucidated. The current study aimed to examine the role of stress neurocircuitry between the hippocampus and the ventral medial prefrontal cortex in this relationship. METHODS To this end, as an index of daily stress in 44 young healthy individuals (23 females; mean [standard deviation] age = 19.07 [1.11] years), the total stressful rating score of daily life stress events that occurred in a 24-hour period was quantified. Individuals were then administered a modified version of the Montreal Imaging Stress Task while undergoing functional magnetic resonance imaging scans, and their saliva samples were collected for assessment of the stress hormone cortisol. RESULTS Results revealed that a higher level of daily stress was associated with lower salivary cortisol secretion (r = -0.39, p = .008) and lower activation of the left hippocampus (tpeak = -5.51) in response to the Montreal Imaging Stress Task. Furthermore, a higher level of daily stress was associated with stronger functional connectivity between the left hippocampus and the ventral medial prefrontal cortex/subgenual anterior cingulate cortex (tpeak = 4.91, R2= 0.365). CONCLUSIONS Taken together, the current study suggested a possible neurocircuitry of the hippocampus and ventral medial prefrontal cortex in the relationship between daily life stress and acute psychosocial stress.
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Affiliation(s)
- Xi Ren
- From the Faculty of Psychology (X. Ren, Zhao, Li, liu, Y. Ren, Yang), Southwest University, Chongqing, China; and Department of Psychology (Pruessner), University of Constance, Constance, Germany
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Li W, Lv L, Luo XJ. In vivo study sheds new light on the dendritic spine pathology hypothesis of schizophrenia. Mol Psychiatry 2022; 27:1866-1868. [PMID: 35079121 DOI: 10.1038/s41380-022-01449-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 01/05/2022] [Accepted: 01/13/2022] [Indexed: 11/10/2022]
Affiliation(s)
- Wenqiang Li
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, 453002, China.,Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, 453002, China
| | - Luxian Lv
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, 453002, China.,Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, 453002, China
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650204, China. .,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, 650204, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, 650204, China. .,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650204, China.
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Prasad K, Rubin J, Mitra A, Lewis M, Theis N, Muldoon B, Iyengar S, Cape J. Structural covariance networks in schizophrenia: A systematic review Part I. Schizophr Res 2022; 240:1-21. [PMID: 34906884 PMCID: PMC8917984 DOI: 10.1016/j.schres.2021.11.035] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 08/02/2021] [Accepted: 11/23/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND Schizophrenia is proposed as a disorder of dysconnectivity. However, examination of complexities of dysconnectivity has been challenging. Structural covariance networks (SCN) provide important insights into the nature of dysconnectivity. This systematic review examines the SCN studies that employed statistical approaches to elucidate covariation of regional morphometric variations. METHODS A systematic search of literature was conducted for peer-reviewed publications using different keywords and keyword combinations for schizophrenia. Fifty-two studies met the criteria. RESULTS Early SCN studies began using correlational structure of selected regions. Over the last 3 decades, methodological approaches have grown increasingly sophisticated from examining selected brain regions using correlation tests on small sample sizes to recent approaches that use advanced statistical methods to examine covariance structure of whole-brain parcellations on larger samples. Although the results are not fully consistent across all studies, a pattern of fronto-temporal, fronto-parietal and fronto-thalamic covariation is reported. Attempts to associate SCN alterations with functional connectivity, to differentiate between disease-related and neurodevelopment-related morphometric changes, and to develop "causality-based" models are being reported. Clinical correlation with outcome, psychotic symptoms, neurocognitive and social cognitive performance are also reported. CONCLUSIONS Application of advanced statistical methods are beginning to provide insights into interesting patterns of regional covariance including correlations with clinical and cognitive data. Although these findings appear similar to morphometric studies, SCNs have the advantage of highlighting topology of these regions and their relationship to the disease and associated variables. Further studies are needed to investigate neurobiological underpinnings of shared covariance, and causal links to clinical domains.
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Affiliation(s)
- Konasale Prasad
- University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O'Hara St, Pittsburgh, PA 15213, United States of America; University of Pittsburgh Swanson School of Engineering, 3700 O'Hara St, Pittsburgh, PA 15213, United States of America; VA Pittsburgh Healthcare System, University Dr C, Pittsburgh, PA 15240, United States of America.
| | - Jonathan Rubin
- Department of Mathematics, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh PA 15260
| | - Anirban Mitra
- Department of Statistics, University of Pittsburgh, 1826 Wesley W. Posvar Hall, Pittsburgh PA 15260
| | - Madison Lewis
- University of Pittsburgh Swanson School of Engineering, 3700 O’Hara St, Pittsburgh PA 15213
| | - Nicholas Theis
- University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O’Hara St, Pittsburgh PA 15213
| | - Brendan Muldoon
- University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O’Hara St, Pittsburgh PA 15213
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, 1826 Wesley W. Posvar Hall, Pittsburgh PA 15260
| | - Joshua Cape
- Department of Statistics, University of Pittsburgh, 1826 Wesley W. Posvar Hall, Pittsburgh PA 15260
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Abstract
Schizophrenia, characterised by psychotic symptoms and in many cases social and occupational decline, remains an aetiological and therapeutic challenge. Contrary to popular belief, the disorder is modestly more common in men than in women. Nor is the outcome uniformly poor. A division of symptoms into positive, negative, and disorganisation syndromes is supported by factor analysis. Catatonic symptoms are not specific to schizophrenia and so-called first rank symptoms are no longer considered diagnostically important. Cognitive impairment is now recognised as a further clinical feature of the disorder. Lateral ventricular enlargement and brain volume reductions of around 2% are established findings. Brain functional changes occur in different subregions of the frontal cortex and might ultimately be understandable in terms of disturbed interaction among large-scale brain networks. Neurochemical disturbance, involving dopamine function and glutamatergic N-methyl-D-aspartate receptor function, is supported by indirect and direct evidence. The genetic contribution to schizophrenia is now recognised to be largely polygenic. Birth and early life factors also have an important aetiological role. The mainstay of treatment remains dopamine receptor-blocking drugs; a psychological intervention, cognitive behavioural therapy, has relatively small effects on symptoms. The idea that schizophrenia is better regarded as the extreme end of a continuum of psychotic symptoms is currently influential. Other areas of debate include cannabis and childhood adversity as causative factors, whether there is progressive brain change after onset, and the long-term success of early intervention initiatives.
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Affiliation(s)
- Sameer Jauhar
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College, London, UK
| | - Mandy Johnstone
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College, London, UK; National Psychosis Service, South London and Maudsley NHS Foundation Trust, London, UK
| | - Peter J McKenna
- FIDMAG Hermanas Hospitalarias Research Foundation, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain.
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Kanahara N, Yamanaka H, Shiko Y, Kawasaki Y, Iyo M. The effects of cumulative antipsychotic dose on brain structures in patients with schizophrenia: Observational study of multiple CT scans over a long-term clinical course. Psychiatry Res Neuroimaging 2022; 319:111422. [PMID: 34856453 DOI: 10.1016/j.pscychresns.2021.111422] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 10/23/2021] [Accepted: 10/28/2021] [Indexed: 10/19/2022]
Abstract
Multiple lines of evidence indicate that antipsychotic agents could affect brain structures of schizophrenia patients. However, the effect of antipsychotic dosage or type on brain structure is uncertain. The present study retrospectively analyzed brain computed tomography (CT) images from a psychiatric hospital to examine the relationship between cumulative dose of antipsychotics and brain volume reduction in schizophrenia patients. A total of 43 patients with repeated relapse episode of psychosis were included and CT scans that were performed an average of 3.2 times per patient during nearly 13 years of follow-up were analyzed. The results revealed significant positive relationships of expansion of cerebrospinal fluid space with cumulative dosage of all antipsychotics and that of typical antipsychotics. Patients treated with antipsychotics including typical antipsychotics exhibited a greater volume reduction compared to patients treated with only atypical antipsychotics. The present study was one of the longest longitudinal studies examining the effects of antipsychotics on brain volume in schizophrenia patients. These results suggest a relation between cumulative lifetime antipsychotic dosage and progressive brain volume reduction in patients with schizophrenia. However, the effects of specific agent on brain structure are still uncertain, and more detailed analysis is needed.
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Affiliation(s)
- Nobuhisa Kanahara
- Division of Medical Treatment and Rehabilitation, Center for Forensic Mental Health, Chiba University, Chiba, Japan; Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan.
| | - Hiroshi Yamanaka
- Department of Psychiatry, Chiba Psychiatric Medical Center, Chiba, Japan
| | - Yuki Shiko
- Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
| | - Yohei Kawasaki
- Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
| | - Masaomi Iyo
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
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Schröder R, Faiola E, Fernanda Urquijo M, Bey K, Meyhöfer I, Steffens M, Kasparbauer AM, Ruef A, Högenauer H, Hurlemann R, Kambeitz J, Philipsen A, Wagner M, Koutsouleris N, Ettinger U. Neural Correlates of Smooth Pursuit Eye Movements in Schizotypy and Recent Onset Psychosis: A Multivariate Pattern Classification Approach. SCHIZOPHRENIA BULLETIN OPEN 2022; 3:sgac034. [PMID: 39144773 PMCID: PMC11206064 DOI: 10.1093/schizbullopen/sgac034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Schizotypy refers to a set of personality traits that bear resemblance, at subclinical level, to psychosis. Despite evidence of similarity at multiple levels of analysis, direct comparisons of schizotypy and clinical psychotic disorders are rare. Therefore, we used functional magnetic resonance imaging (fMRI) to examine the neural correlates and task-based functional connectivity (psychophysiological interactions; PPI) of smooth pursuit eye movements (SPEM) in patients with recent onset psychosis (ROP; n = 34), participants with high levels of negative (HNS; n = 46) or positive (HPS; n = 41) schizotypal traits, and low-schizotypy control participants (LS; n = 61) using machine-learning. Despite strong previous evidence that SPEM is a highly reliable marker of psychosis, patients and controls could not be significantly distinguished based on SPEM performance or blood oxygen level dependent (BOLD) signal during SPEM. Classification was, however, significant for the right frontal eye field (FEF) seed region in the PPI analyses but not for seed regions in other key areas of the SPEM network. Applying the right FEF classifier to the schizotypal samples yielded decision scores between the LS and ROP groups, suggesting similarities and dissimilarities of the HNS and HPS samples with the LS and ROP groups. The very small difference between groups is inconsistent with previous studies that showed significant differences between patients with ROP and controls in both SPEM performance and underlying neural mechanisms with large effect sizes. As the current study had sufficient power to detect such differences, other reasons are discussed.
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Affiliation(s)
- Rebekka Schröder
- Department of Psychology, University of Bonn, Kaiser-Karl-Ring 9, 53111, Bonn, Germany
| | - Eliana Faiola
- Department of Psychology, University of Bonn, Kaiser-Karl-Ring 9, 53111, Bonn, Germany
| | - Maria Fernanda Urquijo
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University of Munich, Nußbaumstr. 7, 80336, Munich, Germany
| | - Katharina Bey
- Department of Psychiatry and Psychotherapy, University of Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - Inga Meyhöfer
- Department of Psychology, University of Bonn, Kaiser-Karl-Ring 9, 53111, Bonn, Germany
| | - Maria Steffens
- Department of Psychology, University of Bonn, Kaiser-Karl-Ring 9, 53111, Bonn, Germany
| | | | - Anne Ruef
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University of Munich, Nußbaumstr. 7, 80336, Munich, Germany
| | - Hanna Högenauer
- Department of Psychiatry and Psychotherapy, University of Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - René Hurlemann
- Department of Psychiatry, University of Oldenburg Medical Campus, Hermann-Ehlers-Str. 7, 26160, Bad Zwischenahn, Germany
- Department of Psychiatry and Division of Medical Psychology, University HospitalBonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50931, Cologne, Germany
| | - Alexandra Philipsen
- Department of Psychiatry and Psychotherapy, University of Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - Michael Wagner
- Department of Psychiatry and Psychotherapy, University of Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University of Munich, Nußbaumstr. 7, 80336, Munich, Germany
| | - Ulrich Ettinger
- Department of Psychology, University of Bonn, Kaiser-Karl-Ring 9, 53111, Bonn, Germany
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Koga M, Nakagawa S, Sato A, Oka M, Makikhara K, Sakai Y, Toyomaki A, Sato M, Matsui M, Toda H, Kusumi I. Plasma fatty acid-binding protein 7 concentration correlates with depression/anxiety, cognition, and positive symptom in patients with schizophrenia. J Psychiatr Res 2021; 144:304-311. [PMID: 34715597 DOI: 10.1016/j.jpsychires.2021.10.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/08/2021] [Accepted: 10/19/2021] [Indexed: 10/20/2022]
Abstract
Because of the involvement of the brain in the pathophysiology of psychiatric disorders, obtaining information on the biochemical features that directly contribute to symptoms is challenging. The present study aimed to assess fatty acid-binding protein 7 (FABP7) expressed specifically in the brain and detectable in the peripheral blood and to investigate the correlation between blood FABP7 concentration and symptoms. We recruited 30, 29, and 35 patients with schizophrenia, bipolar disorder, and depression and evaluated using the Positive and Negative Syndrome Scale (PANSS), Young Mania Rating Scale (YMRS), and Hamilton Depression Rating Scale (HAMD-21), respectively. Plasma FABP7 concentrations correlated with PANSS scores (R2 = 0.3305, p < 0.001) but not with other scales. In the analysis of the relationship between five dimensions of schizophrenia symptoms derived from the PANSS 5-factor model and measured plasma FABP7 concentrations, severities of depression/anxiety, cognition, and positive symptom were significantly correlated with plasma FABP7 concentrations. Further molecular investigation of the functional and kinetic analyses of FABP7 is necessary to understand the relationship of this protein with schizophrenia pathology. Nevertheless, the present study suggests that FABP7 can be a biological indicator reflecting the pathogenesis of schizophrenia and has potential applications as a biomarker for diagnosis and symptom assessment.
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Affiliation(s)
- Minori Koga
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan; Department of Psychiatry, National Defense Medical College, Tokorozawa, Saitama, Japan.
| | - Shin Nakagawa
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan; Yamaguchi University Graduate School of Medicine Division of Neuropsychiatry, Department of Neuroscience, Japan
| | - Asumi Sato
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Matsuhiko Oka
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Keisuke Makikhara
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Yuri Sakai
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Atsuhito Toyomaki
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Mayumi Sato
- Department of Psychiatry, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Marie Matsui
- Department of Psychiatry, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Hiroyuki Toda
- Department of Psychiatry, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Ichiro Kusumi
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
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Chandrasekaran A, Jensen P, Mohamed FA, Lancaster M, Benros ME, Larsen MR, Freude KK. A protein-centric view of in vitro biological model systems for schizophrenia. Stem Cells 2021; 39:1569-1578. [PMID: 34431581 DOI: 10.1002/stem.3447] [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: 05/01/2021] [Accepted: 08/10/2021] [Indexed: 01/10/2023]
Abstract
Schizophrenia (SCZ) is a severe brain disorder, characterized by psychotic, negative, and cognitive symptoms, affecting 1% of the population worldwide. The precise etiology of SCZ is still unknown; however, SCZ has a high heritability and is associated with genetic, environmental, and social risk factors. Even though the genetic contribution is indisputable, the discrepancies between transcriptomics and proteomics in brain tissues are consistently challenging the field to decipher the disease pathology. Here we provide an overview of the state of the art of neuronal two-dimensional and three-dimensional model systems that can be combined with proteomics analyses to decipher specific brain pathology and detection of alternative entry points for drug development.
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Affiliation(s)
- Abinaya Chandrasekaran
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Pia Jensen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Fadumo A Mohamed
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Madeline Lancaster
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, UK
| | - Michael E Benros
- Biological and Precision Psychiatry, Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Hellerup, Denmark
- Department of Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Martin R Larsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Kristine K Freude
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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38
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Benchoua A, Lasbareilles M, Tournois J. Contribution of Human Pluripotent Stem Cell-Based Models to Drug Discovery for Neurological Disorders. Cells 2021; 10:cells10123290. [PMID: 34943799 PMCID: PMC8699352 DOI: 10.3390/cells10123290] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 11/19/2021] [Accepted: 11/23/2021] [Indexed: 02/07/2023] Open
Abstract
One of the major obstacles to the identification of therapeutic interventions for central nervous system disorders has been the difficulty in studying the step-by-step progression of diseases in neuronal networks that are amenable to drug screening. Recent advances in the field of human pluripotent stem cell (PSC) biology offers the capability to create patient-specific human neurons with defined clinical profiles using reprogramming technology, which provides unprecedented opportunities for both the investigation of pathogenic mechanisms of brain disorders and the discovery of novel therapeutic strategies via drug screening. Many examples not only of the creation of human pluripotent stem cells as models of monogenic neurological disorders, but also of more challenging cases of complex multifactorial disorders now exist. Here, we review the state-of-the art brain cell types obtainable from PSCs and amenable to compound-screening formats. We then provide examples illustrating how these models contribute to the definition of new molecular or functional targets for drug discovery and to the design of novel pharmacological approaches for rare genetic disorders, as well as frequent neurodegenerative diseases and psychiatric disorders.
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Affiliation(s)
- Alexandra Benchoua
- Neuroplasticity and Therapeutics, CECS, I-STEM, AFM, 91100 Corbeil-Essonnes, France;
- High Throughput Screening Platform, CECS, I-STEM, AFM, 91100 Corbeil-Essonnes, France;
- Correspondence:
| | - Marie Lasbareilles
- Neuroplasticity and Therapeutics, CECS, I-STEM, AFM, 91100 Corbeil-Essonnes, France;
- UEVE UMR 861, I-STEM, AFM, 91100 Corbeil-Essonnes, France
| | - Johana Tournois
- High Throughput Screening Platform, CECS, I-STEM, AFM, 91100 Corbeil-Essonnes, France;
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39
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The central executive network and executive function in healthy and persons with schizophrenia groups: a meta-analysis of structural and functional MRI. Brain Imaging Behav 2021; 16:1451-1464. [PMID: 34775552 DOI: 10.1007/s11682-021-00589-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2021] [Indexed: 10/19/2022]
Abstract
This meta-analysis evaluated the extent to which executive function can be understood with structural and functional magnetic resonance imaging. Studies included structural in schizophrenia (k = 8; n = 241) and healthy controls (k = 12; n = 1660), and functional in schizophrenia (k = 4; n = 104) and healthy controls (k = 12; n = 712). Results revealed a positive association in the brain behavior relationship when pooled across schizophrenia and control samples for structural (pr = 0.27) and functional (pr = 0.29) modalities. Subgroup analyses revealed no significant difference for functional neuroimaging (pr = .43, 95%CI = -.08-.77, p = .088) but with structural neuroimaging (pr = .37, 95%CI = -.08-.69, p = .015) the association to executive functions is lower in the control group. Subgroup analyses also revealed no significant differences in the strength of the brain-behavior relationship in the schizophrenia group (pr = .59, 95%CI = .58-.61, p = .881) or the control group (pr = 0.19, 95%CI = 0.18-0.19, p = 0.920), suggesting concordance.
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40
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Cui J, Xu H, Lehtinen MK. Macrophages on the margin: choroid plexus immune responses. Trends Neurosci 2021; 44:864-875. [PMID: 34312005 PMCID: PMC8551004 DOI: 10.1016/j.tins.2021.07.002] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/29/2021] [Accepted: 07/01/2021] [Indexed: 12/11/2022]
Abstract
The choroid plexus (ChP), an epithelial bilayer containing a network of mesenchymal, immune, and neuronal cells, forms the blood-cerebrospinal fluid (CSF) barrier (BCSFB). While best recognized for secreting CSF, the ChP is also a hotbed of immune cell activity and can provide circulating peripheral immune cells with passage into the central nervous system (CNS). Here, we review recent studies on ChP immune cells, with a focus on the ontogeny, development, and behaviors of ChP macrophages, the principal resident immune cells of the ChP. We highlight the implications of immune cells for ChP barrier function, CSF cytokines and volume regulation, and their contribution to neurodevelopmental disorders, with possible age-specific features to be elucidated in the future.
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Affiliation(s)
- Jin Cui
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Huixin Xu
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Maria K Lehtinen
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA.
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41
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Thomas KT, Zakharenko SS. MicroRNAs in the Onset of Schizophrenia. Cells 2021; 10:2679. [PMID: 34685659 PMCID: PMC8534348 DOI: 10.3390/cells10102679] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 09/30/2021] [Accepted: 10/02/2021] [Indexed: 12/14/2022] Open
Abstract
Mounting evidence implicates microRNAs (miRNAs) in the pathology of schizophrenia. These small noncoding RNAs bind to mRNAs containing complementary sequences and promote their degradation and/or inhibit protein synthesis. A single miRNA may have hundreds of targets, and miRNA targets are overrepresented among schizophrenia-risk genes. Although schizophrenia is a neurodevelopmental disorder, symptoms usually do not appear until adolescence, and most patients do not receive a schizophrenia diagnosis until late adolescence or early adulthood. However, few studies have examined miRNAs during this critical period. First, we examine evidence that the miRNA pathway is dynamic throughout adolescence and adulthood and that miRNAs regulate processes critical to late neurodevelopment that are aberrant in patients with schizophrenia. Next, we examine evidence implicating miRNAs in the conversion to psychosis, including a schizophrenia-associated single nucleotide polymorphism in MIR137HG that is among the strongest known predictors of age of onset in patients with schizophrenia. Finally, we examine how hemizygosity for DGCR8, which encodes an obligate component of the complex that synthesizes miRNA precursors, may contribute to the onset of psychosis in patients with 22q11.2 microdeletions and how animal models of this disorder can help us understand the many roles of miRNAs in the onset of schizophrenia.
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Affiliation(s)
- Kristen T. Thomas
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Stanislav S. Zakharenko
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
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42
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N-methyl-D-aspartate receptor antibody and the choroid plexus in schizophrenia patients with tardive dyskinesia. J Psychiatr Res 2021; 142:290-298. [PMID: 34411812 DOI: 10.1016/j.jpsychires.2021.08.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/02/2021] [Accepted: 08/09/2021] [Indexed: 11/21/2022]
Abstract
BACKGROUND Immune disturbance has been postulated to be one of the mechanisms underlying the pathogenesis of tardive dyskinesia (TD). Recently, the role of autoimmune abnormality in TD has been increasingly recognized. Autoantibodies against neuronal N-methyl-D-aspartate receptor (NMDAR) may be cross-reactive in the brain in neuropsychiatric disorders, and the choroid plexus (CP) is a crucial immune barrier in the central nervous system (CNS). We supposed that NMDAR antibodies might underlie the pathophysiological process of TD through the mediation of CP. METHODS Serum NMDAR antibody levels were assessed by enzyme-linked immunosorbent assay, CP and ventricle volumes were assessed by magnetic resonance imaging in schizophrenia patients with TD (n = 61), without TD (NTD, n = 61), and in healthy controls (n = 74). Psychopathology and TD severity were assessed by the Positive and Negative Syndrome Scale and Abnormal Involuntary Movement Scale (AIMS). RESULTS NMDAR antibody levels were significantly higher, CP volumes were larger in the TD group than in the NTD group (p = 0.022; p = 0.019, respectively). In the TD group, higher NMDAR antibody level was correlated with larger CP volume (β = 0.406, p = 0.002). An elevated NMDAR antibody level and enlarged CP volume were correlated with orofacial AIMS score (β = 0.331, p = 0.011; β = 0.459, p = 3.34 × 10-4, respectively). In a mediation model, the effect of NMDAR antibody level on the orofacial AIMS score was mediated by the CP volume (indirect effect: β = 0.08, 95% confidence interval = 0.002-0.225; direct effect: β = 0.14, p = 0.154). CONCLUSIONS Our findings highlight a potential NMDAR antibody-associated mechanism in orofacial TD, which may be mediated by increased CP volume.
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43
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Zhang S, Li M, Guo Z. Effect of cannabidiol on schizophrenia based on randomized controlled trials: A meta-analysis. ANNALES MEDICO-PSYCHOLOGIQUES 2021. [DOI: 10.1016/j.amp.2021.09.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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44
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Khanal P, Hotulainen P. Dendritic Spine Initiation in Brain Development, Learning and Diseases and Impact of BAR-Domain Proteins. Cells 2021; 10:cells10092392. [PMID: 34572042 PMCID: PMC8468246 DOI: 10.3390/cells10092392] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/08/2021] [Accepted: 09/09/2021] [Indexed: 02/08/2023] Open
Abstract
Dendritic spines are small, bulbous protrusions along neuronal dendrites where most of the excitatory synapses are located. Dendritic spine density in normal human brain increases rapidly before and after birth achieving the highest density around 2-8 years. Density decreases during adolescence, reaching a stable level in adulthood. The changes in dendritic spines are considered structural correlates for synaptic plasticity as well as the basis of experience-dependent remodeling of neuronal circuits. Alterations in spine density correspond to aberrant brain function observed in various neurodevelopmental and neuropsychiatric disorders. Dendritic spine initiation affects spine density. In this review, we discuss the importance of spine initiation in brain development, learning, and potential complications resulting from altered spine initiation in neurological diseases. Current literature shows that two Bin Amphiphysin Rvs (BAR) domain-containing proteins, MIM/Mtss1 and SrGAP3, are involved in spine initiation. We review existing literature and open databases to discuss whether other BAR-domain proteins could also take part in spine initiation. Finally, we discuss the potential molecular mechanisms on how BAR-domain proteins could regulate spine initiation.
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Affiliation(s)
- Pushpa Khanal
- Minerva Foundation Institute for Medical Research, Tukholmankatu 8, 00290 Helsinki, Finland;
- HiLIFE-Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland
| | - Pirta Hotulainen
- Minerva Foundation Institute for Medical Research, Tukholmankatu 8, 00290 Helsinki, Finland;
- Correspondence:
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45
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Rodrigues RS, Paulo SL, Moreira JB, Tanqueiro SR, Sebastião AM, Diógenes MJ, Xapelli S. Adult Neural Stem Cells as Promising Targets in Psychiatric Disorders. Stem Cells Dev 2021; 29:1099-1117. [PMID: 32723008 DOI: 10.1089/scd.2020.0100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The development of new therapies for psychiatric disorders is of utmost importance, given the enormous toll these disorders pose to society nowadays. This should be based on the identification of neural substrates and mechanisms that underlie disease etiopathophysiology. Adult neural stem cells (NSCs) have been emerging as a promising platform to counteract brain damage. In this perspective article, we put forth a detailed view of how NSCs operate in the adult brain and influence brain homeostasis, having profound implications at both behavioral and functional levels. We appraise evidence suggesting that adult NSCs play important roles in regulating several forms of brain plasticity, particularly emotional and cognitive flexibility, and that NSC dynamics are altered upon brain pathology. Furthermore, we discuss the potential therapeutic value of utilizing adult endogenous NSCs as vessels for regeneration, highlighting their importance as targets for the treatment of multiple mental illnesses, such as affective disorders, schizophrenia, and addiction. Finally, we speculate on strategies to surpass current challenges in neuropsychiatric disease modeling and brain repair.
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Affiliation(s)
- Rui S Rodrigues
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Sara L Paulo
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - João B Moreira
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Sara R Tanqueiro
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Ana M Sebastião
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Maria J Diógenes
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
| | - Sara Xapelli
- Instituto de Farmacologia e Neurociências, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
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46
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Dawidowski B, Górniak A, Podwalski P, Lebiecka Z, Misiak B, Samochowiec J. The Role of Cytokines in the Pathogenesis of Schizophrenia. J Clin Med 2021; 10:jcm10173849. [PMID: 34501305 PMCID: PMC8432006 DOI: 10.3390/jcm10173849] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 08/21/2021] [Accepted: 08/24/2021] [Indexed: 02/07/2023] Open
Abstract
Schizophrenia is a chronic mental illness of unknown etiology. A growing and compelling body of evidence implicates immunologic dysfunction as the key element in its pathomechanism. Cytokines, whose altered levels have been increasingly reported in various patient populations, are the major mediators involved in the coordination of the immune system. The available literature reports both elevated levels of proinflammatory as well as reduced levels of anti-inflammatory cytokines, and their effects on clinical status and neuroimaging changes. There is evidence of at least a partial genetic basis for the association between cytokine alterations and schizophrenia. Two other factors implicated in its development include early childhood trauma and disturbances in the gut microbiome. Moreover, its various subtypes, characterized by individual symptom severity and course, such as deficit schizophrenia, seem to differ in terms of changes in peripheral cytokine levels. While the use of a systematic review methodology could be difficult due to the breadth and diversity of the issues covered in this review, the applied narrative approach allows for a more holistic presentation. The aim of this narrative review was to present up-to-date evidence on cytokine dysregulation in schizophrenia, its effect on the psychopathological presentation, and links with antipsychotic medication. We also attempted to summarize its postulated underpinnings, including early childhood trauma and gut microbiome disturbances, and propose trait and state markers of schizophrenia.
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Affiliation(s)
- Bartosz Dawidowski
- Department of Psychiatry, Pomeranian Medical University, 71-460 Szczecin, Poland; (B.D.); (A.G.); (J.S.)
| | - Adrianna Górniak
- Department of Psychiatry, Pomeranian Medical University, 71-460 Szczecin, Poland; (B.D.); (A.G.); (J.S.)
| | - Piotr Podwalski
- Department of Psychiatry, Pomeranian Medical University, 71-460 Szczecin, Poland; (B.D.); (A.G.); (J.S.)
- Correspondence: ; Tel.: +48-510-091-466
| | - Zofia Lebiecka
- Department of Health Psychology, Pomeranian Medical University, 71-210 Szczecin, Poland;
| | - Błażej Misiak
- Department of Psychiatry, Division of Consultation Psychiatry and Neuroscience, Medical University, 50-367 Wroclaw, Poland;
| | - Jerzy Samochowiec
- Department of Psychiatry, Pomeranian Medical University, 71-460 Szczecin, Poland; (B.D.); (A.G.); (J.S.)
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47
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Wrigglesworth J, Ward P, Harding IH, Nilaweera D, Wu Z, Woods RL, Ryan J. Factors associated with brain ageing - a systematic review. BMC Neurol 2021; 21:312. [PMID: 34384369 PMCID: PMC8359541 DOI: 10.1186/s12883-021-02331-4] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/24/2021] [Indexed: 11/10/2022] Open
Abstract
Background Brain age is a biomarker that predicts chronological age using neuroimaging features. Deviations of this predicted age from chronological age is considered a sign of age-related brain changes, or commonly referred to as brain ageing. The aim of this systematic review is to identify and synthesize the evidence for an association between lifestyle, health factors and diseases in adult populations, with brain ageing. Methods This systematic review was undertaken in accordance with the PRISMA guidelines. A systematic search of Embase and Medline was conducted to identify relevant articles using search terms relating to the prediction of age from neuroimaging data or brain ageing. The tables of two recent review papers on brain ageing were also examined to identify additional articles. Studies were limited to adult humans (aged 18 years and above), from clinical or general populations. Exposures and study design of all types were also considered eligible. Results A systematic search identified 52 studies, which examined brain ageing in clinical and community dwelling adults (mean age between 21 to 78 years, ~ 37% were female). Most research came from studies of individuals diagnosed with schizophrenia or Alzheimer’s disease, or healthy populations that were assessed cognitively. From these studies, psychiatric and neurologic diseases were most commonly associated with accelerated brain ageing, though not all studies drew the same conclusions. Evidence for all other exposures is nascent, and relatively inconsistent. Heterogenous methodologies, or methods of outcome ascertainment, were partly accountable. Conclusion This systematic review summarised the current evidence for an association between genetic, lifestyle, health, or diseases and brain ageing. Overall there is good evidence to suggest schizophrenia and Alzheimer’s disease are associated with accelerated brain ageing. Evidence for all other exposures was mixed or limited. This was mostly due to a lack of independent replication, and inconsistency across studies that were primarily cross sectional in nature. Future research efforts should focus on replicating current findings, using prospective datasets. Trial registration A copy of the review protocol can be accessed through PROSPERO, registration number CRD42020142817. Supplementary Information The online version contains supplementary material available at 10.1186/s12883-021-02331-4.
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Affiliation(s)
- Jo Wrigglesworth
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Phillip Ward
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, 3168, Australia.,Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, 3800, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Clayton, Victoria , 3800, , Australia
| | - Ian H Harding
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, 3168, Australia.,Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, 3004, Australia
| | - Dinuli Nilaweera
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Zimu Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Robyn L Woods
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia.
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48
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Sefiani A, Geoffroy CG. The Potential Role of Inflammation in Modulating Endogenous Hippocampal Neurogenesis After Spinal Cord Injury. Front Neurosci 2021; 15:682259. [PMID: 34220440 PMCID: PMC8249862 DOI: 10.3389/fnins.2021.682259] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 05/17/2021] [Indexed: 12/24/2022] Open
Abstract
Currently there are approximately 291,000 people suffering from a spinal cord injury (SCI) in the United States. SCI is associated with traumatic changes in mobility and neuralgia, as well as many other long-term chronic health complications, including metabolic disorders, diabetes mellitus, non-alcoholic steatohepatitis, osteoporosis, and elevated inflammatory markers. Due to medical advances, patients with SCI survive much longer than previously. This increase in life expectancy exposes them to novel neurological complications such as memory loss, cognitive decline, depression, and Alzheimer's disease. In fact, these usually age-associated disorders are more prevalent in people living with SCI. A common factor of these disorders is the reduction in hippocampal neurogenesis. Inflammation, which is elevated after SCI, plays a major role in modulating hippocampal neurogenesis. While there is no clear consensus on the mechanism of the decline in hippocampal neurogenesis and cognition after SCI, we will examine in this review how SCI-induced inflammation could modulate hippocampal neurogenesis and provoke age-associated neurological disorders. Thereafter, we will discuss possible therapeutic options which may mitigate the influence of SCI associated complications on hippocampal neurogenesis.
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49
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Svancer P, Spaniel F. Brain ventricular volume changes in schizophrenia. A narrative review. Neurosci Lett 2021; 759:136065. [PMID: 34146640 DOI: 10.1016/j.neulet.2021.136065] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 05/15/2021] [Accepted: 06/14/2021] [Indexed: 11/18/2022]
Abstract
Brain ventricles are among the most studied structures in psychotic illness. In our mini-review we present available evidence on brain ventricle changes during the course of schizophrenia, from high-risk subjects and the first episode of schizophrenia to patients with chronic schizophrenia. We present current findings on the relationship between ventricle changes and level of psychopathology. The potential pathophysiological background of ventricle changes is also discussed. Understanding the dynamics of brain ventricle changes could resolve long-standing questions on the proportion of neurodegenerative and neurodevelopmental processes in the pathophysiology of schizophrenia.
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Affiliation(s)
- Patrik Svancer
- National Institute of Mental Health, Klecany, Czech Republic; Third Faculty of Medicine, Charles University, Prague, Czech Republic.
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic; Third Faculty of Medicine, Charles University, Prague, Czech Republic
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Wu CL, Lin TJ, Chiou GL, Lee CY, Luan H, Tsai MJ, Potvin P, Tsai CC. A Systematic Review of MRI Neuroimaging for Education Research. Front Psychol 2021; 12:617599. [PMID: 34093308 PMCID: PMC8174785 DOI: 10.3389/fpsyg.2021.617599] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 04/21/2021] [Indexed: 11/13/2022] Open
Abstract
This study aims to disclose how the magnetic resonance imaging (MRI) neuroimaging approach has been applied in education studies, and what kind of learning themes has been investigated in the reviewed MRI neuroimaging research. Based on the keywords “brain or neuroimaging or neuroscience” and “MRI or diffusion tensor imaging (DTI) or white matter or gray matter or resting-state,” a total of 25 papers were selected from the subject areas “Educational Psychology” and “Education and Educational Research” from the Web of Science and Scopus from 2000 to 2019. Content analysis showed that MRI neuroimaging and learning were studied under the following three major topics and nine subtopics: cognitive function (language, creativity, music, physical activity), science education (mathematical learning, biology learning, physics learning), and brain development (parenting, personality development). As for the type of MRI neuroimaging research, the most frequently used approaches were functional MRI, followed by structural MRI and DTI, although the choice of approach was often motivated by the specific research question. Research development trends show that the neural plasticity theme has become more prominent recently. This study concludes that in educational research, the MRI neuroimaging approach provides objective and empirical evidence to connect learning processes, outcomes, and brain mechanisms.
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Affiliation(s)
- Ching-Lin Wu
- Program of Learning Sciences, School of Learning Informatics, National Taiwan Normal University, Taipei, Taiwan.,Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Tzung-Jin Lin
- Program of Learning Sciences, School of Learning Informatics, National Taiwan Normal University, Taipei, Taiwan.,Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Guo-Li Chiou
- Program of Learning Sciences, School of Learning Informatics, National Taiwan Normal University, Taipei, Taiwan.,Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Chia-Ying Lee
- Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan.,Institute of Linguistics, Academia Sinica, Taipei, Taiwan.,Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan.,Research Center for Mind, Brain, and Learning, National Chengchi University, Taipei, Taiwan
| | - Hui Luan
- Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Meng-Jung Tsai
- Program of Learning Sciences, School of Learning Informatics, National Taiwan Normal University, Taipei, Taiwan.,Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Patrice Potvin
- Département de Didactique, Université du Québec à Montréal, Montréal, QC, Canada
| | - Chin-Chung Tsai
- Program of Learning Sciences, School of Learning Informatics, National Taiwan Normal University, Taipei, Taiwan.,Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei, Taiwan
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