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Kim JS, Hong SB, Park KW, Lee ATC. Psychotic Symptoms in Patients With Major Neurological Diseases. J Clin Neurol 2024; 20:153-165. [PMID: 38433485 PMCID: PMC10921039 DOI: 10.3988/jcn.2023.0501] [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: 12/11/2023] [Revised: 12/28/2023] [Accepted: 12/30/2023] [Indexed: 03/05/2024] Open
Abstract
Neurological diseases often manifest with neuropsychiatric symptoms such as depression, emotional incontinence, anger, apathy and fatigue. In addition, affected patients may also experience psychotic symptoms such as hallucinations and delusions. Various factors contribute to the development of psychotic symptoms, and the mechanisms of psychosis are similar, but still differ among various neurological diseases. Although psychotic symptoms are uncommon, and have been less well investigated, they may annoy patients and their families as well as impair the patients' quality of life and increase the caregiver burden. Therefore, we need to appropriately identify and treat these psychotic symptoms in patients with neurological diseases.
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Affiliation(s)
- Jong S Kim
- Department of Neurology, Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Korea.
| | - Seung-Bong Hong
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Keun-Woo Park
- Department of Neurology, Korea University Anam Hospital, Seoul, Korea
| | - Allen T C Lee
- Department of Psychiatry, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China
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Lamsma J, Raine A, Kia SM, Cahn W, Arold D, Banaj N, Barone A, Brosch K, Brouwer R, Brunetti A, Calhoun VD, Chew QH, Choi S, Chung YC, Ciccarelli M, Cobia D, Cocozza S, Dannlowski U, Dazzan P, de Bartolomeis A, Di Forti M, Dumais A, Edmond JT, Ehrlich S, Evermann U, Flinkenflügel K, Georgiadis F, Glahn DC, Goltermann J, Green MJ, Grotegerd D, Guerrero-Pedraza A, Ha M, Hong EL, Hulshoff Pol H, Iasevoli F, Kaiser S, Kaleda V, Karuk A, Kim M, Kircher T, Kirschner M, Kochunov P, Kwon JS, Lebedeva I, Lencer R, Marques TR, Meinert S, Murray R, Nenadić I, Nguyen D, Pearlson G, Piras F, Pomarol-Clotet E, Pontillo G, Potvin S, Preda A, Quidé Y, Rodrigue A, Rootes-Murdy K, Salvador R, Skoch A, Sim K, Spalletta G, Spaniel F, Stein F, Thomas-Odenthal F, Tikàsz A, Tomecek D, Tomyshev A, Tranfa M, Tsogt U, Turner JA, van Erp TGM, van Haren NEM, van Os J, Vecchio D, Wang L, Wroblewski A, Nickl-Jockschat T. Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.04.24302268. [PMID: 38370846 PMCID: PMC10871467 DOI: 10.1101/2024.02.04.24302268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Background Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome. Methods This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale. Results Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control. Conclusions This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.
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Affiliation(s)
- Jelle Lamsma
- Department of Criminology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Adrian Raine
- Department of Criminology, University of Pennsylvania, Philadelphia, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
| | - Seyed M. Kia
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Dominic Arold
- Division of Psychological and Social Medicine and Developmental Neurosciences, TU Dresden, Germany
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Annarita Barone
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, USA
| | - Rachel Brouwer
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, USA
| | - Qian H. Chew
- Department of Research, Institute of Mental Health, Singapore
| | - Sunah Choi
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University, Jeonju, South Korea
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, South Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea
| | - Mariateresa Ciccarelli
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Derin Cobia
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, USA
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Paola Dazzan
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Andrea de Bartolomeis
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Marta Di Forti
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Alexandre Dumais
- Department of Psychiatry and Addictology, University of Montreal, Montreal, Canada
- Institut Philippe-Pinel, Montreal, Canada
| | - Jesse T. Edmond
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, USA
- Department of Psychology, Georgia State University, Atlanta, USA
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, TU Dresden, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, TU Dresden, Germany
| | - Ulrika Evermann
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Kira Flinkenflügel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Switzerland
| | - David C. Glahn
- Department of Psychiatry, Harvard Medical School, Harvard, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, USA
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Melissa J. Green
- Neuroscience Research Australia, Randwick, Australia
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | | | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Elliot L. Hong
- Department of Psychiatry and Behavioral Science, UTHealth Houston, Houston, USA
| | - Hilleke Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Psychology, Utrecht University, Utrecht, the Netherlands
| | - Felice Iasevoli
- Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, Naples, Italy
| | - Stefan Kaiser
- Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Vasily Kaleda
- Department of Youth Psychiatry, Mental Health Research Center, Moscow, Russia
| | - Andriana Karuk
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Switzerland
- Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
- Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
| | - Peter Kochunov
- Department of Psychiatry and Behavioral Science, UTHealth Houston, Houston, USA
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russia
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapy, University of Lübeck, Germany
| | - Tiago R. Marques
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
- Institute of Clinical Sciences, Imperial College London, London, UK
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Robin Murray
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Dana Nguyen
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, USA
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Barcelona, Spain
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
| | - Stéphane Potvin
- Department of Psychiatry and Addictology, University of Montreal, Montreal, Canada
- Centre de Recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, USA
| | - Yann Quidé
- Neuroscience Research Australia, Randwick, Australia
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Amanda Rodrigue
- Department of Psychiatry, Harvard Medical School, Harvard, USA
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, USA
- Department of Psychology, Georgia State University, Atlanta, USA
| | - Raymond Salvador
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Barcelona, Spain
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
| | - Kang Sim
- Department of Research, Institute of Mental Health, Singapore
| | | | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | | | - Andràs Tikàsz
- Department of Psychiatry and Addictology, University of Montreal, Montreal, Canada
- Centre de Recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada
| | - 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
| | - Alexander Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russia
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Uyanga Tsogt
- Department of Psychiatry, Jeonbuk National University, Jeonju, South Korea
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, USA
| | - Theo G. M. van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, USA
| | - Neeltje E. M. van Haren
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC Sophia, Rotterdam, the Netherlands
| | - Jim van Os
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Lei Wang
- Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, USA
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, USA
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, University of Iowa, Iowa City, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, USA
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Relationships between cognitive performance, clinical insight and regional brain volumes in schizophrenia. SCHIZOPHRENIA 2022; 8:33. [PMID: 35853892 PMCID: PMC9261092 DOI: 10.1038/s41537-022-00243-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 02/23/2022] [Indexed: 11/22/2022]
Abstract
Impairments in cognitive performance are common in schizophrenia, and these contribute to poor awareness of symptoms and treatment (‘clinical insight’), which is an important predictor of functional outcome. Although relationships between cognitive impairment and reductions in regional brain volumes in patients are relatively well characterised, less is known about the brain structural correlates of clinical insight. To address this gap, we aimed to explore brain structural correlates of cognitive performance and clinical insight in the same sample. 108 patients with schizophrenia (SZH) and 94 age and gender-matched controls (CON) (from the Northwestern University Schizophrenia Data and Software Tool (NUSDAST) database) were included. SZH had smaller grey matter volume across most fronto-temporal regions and significantly poorer performance on all cognitive domains. Multiple regression showed that higher positive symptoms and poorer attention were significant predictors of insight in SZH; however, no significant correlations were seen between clinical insight and regional brain volumes. In contrast, symptomology did not contribute to cognitive performance, but robust positive relationships were found between regional grey matter volumes in fronto-temporal regions and cognitive performance (particularly executive function). Many of these appeared to be unique to SZH as they were not observed in CON. Findings suggest that while there exists a tight link between cognitive functioning and neuropathological processes affecting gross brain anatomy in SZH, this is not the case for clinical insight. Instead, clinical insight levels seem to be influenced by symptomology, attentional performance and other subject-specific variables.
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Brenner AM, Claudino FCDA, Burin LM, Scheibe VM, Padilha BL, de Souza GR, Duarte JA, da Rocha NS. Structural magnetic resonance imaging findings in severe mental disorders adult inpatients: A systematic review. Psychiatry Res Neuroimaging 2022; 326:111529. [PMID: 36058133 DOI: 10.1016/j.pscychresns.2022.111529] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 07/13/2022] [Accepted: 08/04/2022] [Indexed: 11/21/2022]
Abstract
In severe presentations, major depressive disorder (MDD), schizophrenia (SZ), and bipolar disorder (BD) can be categorized as severe mental disorders (SMD). Our aim is to evaluate structural magnetic resonance imaging and computed tomography findings in adult inpatients diagnosed with SMD and hospitalized at psychiatric wards. PubMed, Embase, PsycInfo, Cochrane Library, and Web of Science were searched up to May 27th, 2021. Articles were screened and extracted by two independent groups, with third-party raters for discrepancies. Quality of evidence was evaluated with the Newcastle-Ottawa Scale. Synthesis was made by qualitative analysis. This study was registered on PROSPERO (CRD42020171718) and followed the PRISMA protocol. 35 studies were included, of which none was considered to likely introduce bias in our analyses. Overlapping areas in MDD, SZ, and Affective Psychosis (AP) patients, that include BD and MDD with psychotic features, are presented in the inferior temporal and cingulate gyri. MDD and SZ had commonly affected areas in the inferior and middle frontal gyri, transverse temporal gyrus, insula, and hippocampus. SZ and AP had commonly affected areas in the temporal pole. Overlapping affected areas among SMD patients are reported, but the heterogeneity of studies' designs and findings are still a limitation for clinically relevant guidelines.
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Affiliation(s)
- Augusto Mädke Brenner
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
| | - Felipe Cesar de Almeida Claudino
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Luísa Monteiro Burin
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Victória Machado Scheibe
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Luterana do Brasil, Canoas, Rio Grande do Sul, Brazil
| | - Barbara Larissa Padilha
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Gianfranco Rizzotto de Souza
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Juliana Avila Duarte
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Neusa Sica da Rocha
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Department of Psychiatry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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Shailaja B, Javadekar A, Chaudhury S, Saldanha D. Clinical correlates of regional gray matter volumes in schizophrenia: A structural magnetic resonance imaging study. Ind Psychiatry J 2022; 31:282-292. [PMID: 36419700 PMCID: PMC9678149 DOI: 10.4103/ipj.ipj_104_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 06/21/2021] [Accepted: 10/12/2021] [Indexed: 03/14/2023] Open
Abstract
OBJECTIVES The objective of this study is to investigate the correlation between the regional gray matter volumes and length of Para Cingulate Sulcus (PCS) with the clinical profile of patients with schizophrenia. MATERIALS AND METHODS In this hospital-based, cross-sectional study, thirty consecutive in-patients diagnosed with schizophrenia and equal number of healthy volunteers matched for age- and sex- were recruited as controls. Detailed clinical assessment and magnetic resonance imaging (MRI) of the brain were carried out within 2 days for controls and within 2 weeks of hospitalization for patients. The Positive and Negative Syndrome Scale and Montreal Cognitive Assessment were applied to schizophrenia patients to assess symptoms and cognitive function, respectively. RESULTS Schizophrenia patients had significant volume deficit in bilateral amygdalae, bilateral superior temporal gyri, anterior cingulate cortex and bilateral hippocampi, along with a highly significant reduction in the length of right PCS. Schizophrenia patients with the duration of untreated psychosis (DUP) of 6-12 months showed a significantly greater volume of the right superior temporal gyrus (STG). First-episode schizophrenia patients had a significant reduction in the length of the left PCS. The volume of bilateral superior temporal gyri in schizophrenia patients showed a significant direct correlation with positive symptoms and an inverse correlation with negative symptoms. CONCLUSION Schizophrenia patients have significant volume deficit in some brain regions. DUP of 6-12 months is associated with significantly greater volume of the right STG. First-episode schizophrenia patients have a significant reduction in the length of the left PCS. In schizophrenia patients, the volume of bilateral superior temporal gyri showed a significant direct correlation with the positive symptoms and an inverse correlation with the negative symptoms.
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Affiliation(s)
- B Shailaja
- Department of Psychiatry, M. S. Ramaiah Medical College, Bengaluru, Karnataka, India
| | - Archana Javadekar
- Department of Psychiatry, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
| | - Suprakash Chaudhury
- Department of Psychiatry, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
| | - Daniel Saldanha
- Department of Psychiatry, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
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Toll A, Blanco-Hinojo L, Bergé D, Duran X, Canosa I, Legido T, Marmol F, Pérez-Solà V, Fernández-Egea E, Mané A. Multidimensional predictors of negative symptoms in antipsychotic-naive first-episode psychosis. J Psychiatry Neurosci 2022; 47:E21-E31. [PMID: 35046133 PMCID: PMC8789336 DOI: 10.1503/jpn.210138] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 10/15/2021] [Accepted: 11/01/2021] [Indexed: 11/01/2022] Open
Abstract
BACKGROUND Despite a large body of schizophrenia research, we still have no reliable predictors to guide treatment from illness onset. The present study aimed to identify baseline clinical or neurobiological factors - including peripheral brain-derived neurotrophic factor (BDNF) levels and amygdala or hippocampal relative volumes - that could predict negative symptomatology and persistent negative symptoms in first-episode psychosis after 1 year of follow-up. METHODS We recruited 50 drug-naive patients with first-episode psychosis and 50 age- and sex-matched healthy controls to study brain volumes. We performed univariate and multiple and logistic regression analyses to determine the association between baseline clinical and neurobiological variables, score on the PANSS negative subscale and persistent negative symptoms after 1 year of follow-up. RESULTS Low baseline serum BDNF levels (p = 0.011), decreased left amygdala relative volume (p = 0.001) and more severe negative symptomatology (p = 0.021) predicted the severity of negative symptoms at 1 year, as measured by the PANSS negative subscale. Low baseline serum BDNF levels (p = 0.012) and decreased left amygdala relative volume (p = 0.010) predicted persistent negative symptoms at 1 year. LIMITATIONS We were unable to assess negative symptoms and their dimensions with next-generation scales, which were not available when the study was initiated. CONCLUSION This study shows that a set of variables at baseline, including low BDNF levels, smaller left amygdala relative volume and score on the PANSS negative subscale are significant predictors of outcomes in first-episode psychosis. These findings might offer an initial step for tailoring treatments in first-episode psychosis.
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Affiliation(s)
| | - Laura Blanco-Hinojo
- From the Institut de Neuropsiquiatria i Adiccions (INAD), Parc de Salut Mar, Barcelona, Spain (Toll, Bergé, Canosa, Legido, Pérez-Solà, Mané); the Fundació Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain (Toll, Bergé, Duran, Canosa, Legido, Pérez-Solà, Mané); the Centro de Investigación Biomédica en Red, Área de Salud Mental (CIBERSAM), Spain (Toll, Blanco-Hinojo, Bergé, Canosa, Pérez-Solà, Mané); the Department of Psychiatry and Forensic Medicine, Universitat Autónoma de Barcelona (UAB), Barcelona, Spain (Toll); the MRI Research Unit, Department of Radiology, Parc de Salut Mar, Barcelona, Spain (Blanco-Hinojo); the Pharmacology Unit, Department of Clinical Fundamentals, Faculty of Medicine, Barcelona University, Barcelona, Spain (Marmol); and the Department of Psychiatry and Behavioral and Clinical Neuroscience Institute, University of Cambridge, United Kingdom (Fernández-Egea)
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Gutman BA, van Erp TG, Alpert K, Ching CRK, Isaev D, Ragothaman A, Jahanshad N, Saremi A, Zavaliangos‐Petropulu A, Glahn DC, Shen L, Cong S, Alnæs D, Andreassen OA, Doan NT, Westlye LT, Kochunov P, Satterthwaite TD, Wolf DH, Huang AJ, Kessler C, Weideman A, Nguyen D, Mueller BA, Faziola L, Potkin SG, Preda A, Mathalon DH, Bustillo J, Calhoun V, Ford JM, Walton E, Ehrlich S, Ducci G, Banaj N, Piras F, Piras F, Spalletta G, Canales‐Rodríguez EJ, Fuentes‐Claramonte P, Pomarol‐Clotet E, Radua J, Salvador R, Sarró S, Dickie EW, Voineskos A, Tordesillas‐Gutiérrez D, Crespo‐Facorro B, Setién‐Suero E, van Son JM, Borgwardt S, Schönborn‐Harrisberger F, Morris D, Donohoe G, Holleran L, Cannon D, McDonald C, Corvin A, Gill M, Filho GB, Rosa PGP, Serpa MH, Zanetti MV, Lebedeva I, Kaleda V, Tomyshev A, Crow T, James A, Cervenka S, Sellgren CM, Fatouros‐Bergman H, Agartz I, Howells F, Stein DJ, Temmingh H, Uhlmann A, de Zubicaray GI, McMahon KL, Wright M, Cobia D, Csernansky JG, Thompson PM, Turner JA, Wang L. A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium. Hum Brain Mapp 2022; 43:352-372. [PMID: 34498337 PMCID: PMC8675416 DOI: 10.1002/hbm.25625] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 01/06/2023] Open
Abstract
Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
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Affiliation(s)
- Boris A. Gutman
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Institute for Information Transmission Problems (Kharkevich Institute)MoscowRussia
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Kathryn Alpert
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Dmitry Isaev
- Department of Biomedical EngineeringDuke UniversityDurhamNorth CarolinaUSA
| | - Anjani Ragothaman
- Department of biomedical engineeringOregon Health and Science universityPortlandOregonUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Arvin Saremi
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Artemis Zavaliangos‐Petropulu
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - David C. Glahn
- Department of PsychiatryBoston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Li Shen
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Shan Cong
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dag Alnæs
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Ole Andreas Andreassen
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Nhat Trung Doan
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Lars T. Westlye
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Peter Kochunov
- Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Theodore D. Satterthwaite
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Daniel H. Wolf
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alexander J. Huang
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Charles Kessler
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Andrea Weideman
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Dana Nguyen
- Department of PediatricsUniversity of California IrvineIrvineCaliforniaUSA
| | - Bryon A. Mueller
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Lawrence Faziola
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Steven G. Potkin
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Adrian Preda
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Daniel H. Mathalon
- Department of Psychiatry and Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
| | - Juan Bustillo
- Departments of Psychiatry & NeuroscienceUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Vince Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology]Emory UniversityAtlantaGeorgiaUSA
- Department of Electrical and Computer EngineeringThe University of New MexicoAlbuquerqueNew MexicoUSA
| | - Judith M. Ford
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | - Stefan Ehrlich
- Division of Psychological & Social Medicine and Developmental NeurosciencesFaculty of Medicine, TU‐DresdenDresdenGermany
| | | | - Nerisa Banaj
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Fabrizio Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Federica Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Gianfranco Spalletta
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
- Menninger Department of Psychiatry and Behavioral SciencesBaylor College of MedicineHoustonTexasUSA
| | | | | | | | - Joaquim Radua
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
- Institut d'Investigacions Biomdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Erin W. Dickie
- Centre for Addiction and Mental Health (CAMH)TorontoCanada
| | | | | | | | | | | | - Stefan Borgwardt
- Department of PsychiatryUniversity of BaselBaselSwitzerland
- Department of Psychiatry and PsychotherapyUniversity of LübeckLübeckGermany
| | | | - Derek Morris
- Centre for Neuroimaging and Cognitive Genomics, Discipline of BiochemistryNational University of Ireland GalwayGalwayIreland
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Dara Cannon
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Geraldo Busatto Filho
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Pedro G. P. Rosa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Mauricio H. Serpa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
- Hospital Sirio‐LibanesSao PauloSPBrazil
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Vasily Kaleda
- Department of Endogenous Mental DisordersMental Health Research CenterMoscowRussia
| | - Alexander Tomyshev
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Tim Crow
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Anthony James
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Simon Cervenka
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Carl M Sellgren
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden
| | - Helena Fatouros‐Bergman
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Ingrid Agartz
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Fleur Howells
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
| | - Dan J. Stein
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
- SA MRC Unit on Risk & Resilience in Mental DisordersUniversity of Cape TownCape TownWCSouth Africa
| | - Henk Temmingh
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Department of Child and Adolescent PsychiatryTU DresdenGermany
| | - Greig I. de Zubicaray
- School of Psychology, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Katie L. McMahon
- School of Clinical SciencesQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Margie Wright
- Queensland Brain InstituteUniversity of QueenslandBrisbaneQLDAustralia
| | - Derin Cobia
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychology and Neuroscience CenterBrigham Young UniversityProvoUtahUSA
| | - John G. Csernansky
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Lei Wang
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychiatry and Behavioral HealthOhio State University Wexner Medical CenterColumbusOhioUSA
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Rajendran R, Menon KN, Nair SC. Nanotechnology Approaches for Enhanced CNS Drug Delivery in the Management of Schizophrenia. Adv Pharm Bull 2021; 12:490-508. [PMID: 35935056 PMCID: PMC9348538 DOI: 10.34172/apb.2022.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 06/02/2021] [Accepted: 09/27/2021] [Indexed: 11/09/2022] Open
Abstract
Schizophrenia is a neuropsychiatric disorder mainly affecting the central nervous system, presented with auditory and visual hallucinations, delusion and withdrawal from society. Abnormal dopamine levels mainly characterise the disease; various theories of neurotransmitters explain the pathophysiology of the disease. The current therapeutic approach deals with the systemic administration of drugs other than the enteral route, altering the neurotransmitter levels within the brain and providing symptomatic relief. Fluid biomarkers help in the early detection of the disease, which would improve the therapeutic efficacy. However, the major challenge faced in CNS drug delivery is the blood-brain barrier. Nanotherapeutic approaches may overcome these limitations, which will improve safety, efficacy, and targeted drug delivery. This review article addresses the main challenges faced in CNS drug delivery and the significance of current therapeutic strategies and nanotherapeutic approaches for a better understanding and enhanced drug delivery to the brain, which improve the quality of life of schizophrenia patients.
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Affiliation(s)
| | - Krishnakumar Neelakandha Menon
- Amrita Centre for Nanosciences and Molecular Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi-682041, Kerala, India
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9
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Implications for Early Diagnosis and Treatment in Schizophrenia Due to Correlation between Auditory Perceptual Deficits and Cognitive Impairment. J Clin Med 2021; 10:jcm10194557. [PMID: 34640571 PMCID: PMC8509531 DOI: 10.3390/jcm10194557] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 09/27/2021] [Indexed: 11/17/2022] Open
Abstract
It is indicated that auditory perception deficits are present in schizophrenia and related to formal thought disorder. The purpose of the present study was to investigate the association of auditory deficits with cognitive impairment in schizophrenia. An experimental group of 50 schizophrenia patients completed a battery of auditory processing evaluation and a neuropsychological battery of tests. Correlations between neuropsychological battery scores and auditory processing scores were examined. Cognitive impairment was correlated with auditory processing deficits in schizophrenia patients. All neuropsychological test scores were significantly correlated with at least one auditory processing test score. Our findings support the coexistence of auditory processing disorder, severe cognitive impairment, and formal thought disorder in a subgroup of schizophrenia patients. This may have important implications in schizophrenia research, as well as in early diagnosis and nonpharmacological treatment of the disorder.
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10
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Cuesta MJ, Lecumberri P, Moreno-Izco L, López-Ilundain JM, Ribeiro M, Cabada T, Lorente-Omeñaca R, de Erausquin G, García-Martí G, Sanjuan J, Sánchez-Torres AM, Gómez M, Peralta V. Motor abnormalities and basal ganglia in first-episode psychosis (FEP). Psychol Med 2021; 51:1625-1636. [PMID: 32114994 DOI: 10.1017/s0033291720000343] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Motor abnormalities (MAs) are the primary manifestations of schizophrenia. However, the extent to which MAs are related to alterations of subcortical structures remains understudied. METHODS We aimed to investigate the associations of MAs and basal ganglia abnormalities in first-episode psychosis (FEP) and healthy controls. Magnetic resonance imaging was performed on 48 right-handed FEP and 23 age-, gender-, handedness-, and educational attainment-matched controls, to obtain basal ganglia shape analysis, diffusion tensor imaging techniques (fractional anisotropy and mean diffusivity), and relaxometry (R2*) to estimate iron load. A comprehensive motor battery was applied including the assessment of parkinsonism, catatonic signs, and neurological soft signs (NSS). A fully automated model-based segmentation algorithm on 1.5T MRI anatomical images and accurate corregistration of diffusion and T2* volumes and R2* was used. RESULTS FEP patients showed significant local atrophic changes in left globus pallidus nucleus regarding controls. Hypertrophic changes in left-side caudate were associated with higher scores in sensory integration, and in right accumbens with tremor subscale. FEP patients showed lower fractional anisotropy measures than controls but no significant differences regarding mean diffusivity and iron load of basal ganglia. However, iron load in left basal ganglia and right accumbens correlated significantly with higher extrapyramidal and motor coordination signs in FEP patients. CONCLUSIONS Taken together, iron load in left basal ganglia may have a role in the emergence of extrapyramidal signs and NSS of FEP patients and in consequence in the pathophysiology of psychosis.
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Affiliation(s)
- Manuel J Cuesta
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Pablo Lecumberri
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Movalsys S. L., NavarraBiomed, Pamplona, Spain
| | - Lucia Moreno-Izco
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Jose M López-Ilundain
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - María Ribeiro
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Teresa Cabada
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Department of Neuroradiology, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Ruth Lorente-Omeñaca
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Gabriel de Erausquin
- Zachry Foundation, The Glenn Biggs Institute of Alzheimer's & Neurodegenerative Disorders, UT Heath San Antonio, Texas, USA
| | - Gracian García-Martí
- Radiology Department, CIBERSAM, Valencia, España, Quirón Salud Hospital, Valencia, España
| | - Julio Sanjuan
- Research Institute of Clinic University Hospital of Valencia (INCLIVA), Valencia, Spain
- CIBERSAM, Biomedical Research Network on Mental Health Area, Madrid, Spain
- Department of Psychiatric, University of Valencia School of Medicine, Valencia, Spain
| | - Ana M Sánchez-Torres
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Marisol Gómez
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Movalsys S. L., NavarraBiomed, Pamplona, Spain
- Department of Statistics, Computer Science and Mathematics, Universidad Pública de Navarra (UPNA), Pamplona, Spain
| | - Victor Peralta
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud, Pamplona, Spain
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Sampedro F, Roldán A, Alonso-Solís A, Grasa E, Portella MJ, Aguilar EJ, Núñez-Marín F, Gómez-Ansón B, Corripio I. Grey matter microstructural alterations in schizophrenia patients with treatment-resistant auditory verbal hallucinations. J Psychiatr Res 2021; 138:130-138. [PMID: 33852993 DOI: 10.1016/j.jpsychires.2021.03.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 03/16/2021] [Accepted: 03/19/2021] [Indexed: 01/07/2023]
Abstract
Treatment-resistant auditory verbal hallucinations (TRAVH) are a relatively prevalent and devastating symptom in patients with schizophrenia (SCZ). Even though their pathological mechanisms are poorly understood, they seem to differ from those underlying non-hallucinating SCZ. In this study, we characterise structural brain changes in SCZ patients with TRAVH. With respect to non-hallucinating patients and healthy controls, we studied macrostructural grey matter changes through cortical thickness and subcortical volumetric data. Additionally, we analysed microstructural differences across groups using intracortical and subcortical mean diffusivity data. This latter imaging metric has been claimed to detect incipient neuronal damage, as water can diffuse more freely in regions with reduced neural density. We found brain macrostructrural and microstructural alterations in SCZ patients with TRAVH (n = 29), both with respect to non-hallucinating (n = 20) patients and healthy controls (n = 27). Importantly, a microstructural -rather than a macrostructural- compromise was found in key brain regions such as the ventral ACC, the NAcc and the hippocampus. These microstructural alterations correlated, in turn, with clinical severity. TRAVH patients also showed accentuated age-related cortical deterioration and an abnormal longitudinal loss of cortical integrity over a one-year period. These findings highlight the potential role of microstructural imaging biomarkers in SCZ. Notably, they could be used both to detect and to monitor subtle grey matter alterations in critical brain regions such as deep brain stimulation targets. Moreover, our results support the existence of a more aggressive and active pathological mechanism in patients with TRAVH, providing new insight into the aetiology of this debilitating illness.
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Affiliation(s)
- Frederic Sampedro
- Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spain
| | - Alexandra Roldán
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain
| | - Anna Alonso-Solís
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain.
| | - Eva Grasa
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
| | - Maria J Portella
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
| | - Eduardo J Aguilar
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; INCLIVA, School of Medicine, University of Valencia, Valencia, Spain
| | - Fidel Núñez-Marín
- Neuroradiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB) Barcelona, Spain
| | - Beatriz Gómez-Ansón
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spain; Neuroradiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB) Barcelona, Spain
| | - Iluminada Corripio
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
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12
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Smucny J, Lesh TA, Zarubin VC, Niendam TA, Ragland JD, Tully LM, Carter CS. One-Year Stability of Frontoparietal Cognitive Control Network Connectivity in Recent Onset Schizophrenia: A Task-Related 3T fMRI Study. Schizophr Bull 2020; 46:1249-1258. [PMID: 31903495 PMCID: PMC7505169 DOI: 10.1093/schbul/sbz122] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Kraepelinian theory posits that schizophrenia (SZ) is a degenerative disorder that worsens throughout the lifespan. Behavioral studies of cognition have since challenged that viewpoint, particularly in the early phases of illness. Nonetheless, the extent to which cognition remains functionally stable during the early course of illness is unclear, particularly with regard to task-associated connectivity in cognition-related brain networks. In this study, we examined the 1-year stability of the frontoparietal control network during the AX-Continuous Performance Task (AX-CPT) from a new baseline sample of 153 participants scanned at 3T, of which 29 recent onset individuals with SZ and 42 healthy control (HC) participants had follow-up data available for analysis. Among individuals that had both baseline and follow-up data, reduced functional connectivity in SZ was observed between the dorsolateral prefrontal cortex (DLPFC) and superior parietal cortex (SPC) during the high control (B cue) condition. Furthermore, this deficit was stable over time, as no significant time × diagnosis interaction or effects of time were observed and intraclass correlation coefficients were greater than 0.6 in HCs and SZ. Previous 1.5T findings showing stable deficits with no evidence of degeneration in performance or DLPFC activation in an independent SZ sample were replicated. Overall, these results suggest that the neuronal circuitry supporting cognitive control is stably impaired during the early course of illness in SZ across multiple levels of analysis with no evidence of functional decline.
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Affiliation(s)
- Jason Smucny
- Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, CA
| | - Tyler A Lesh
- Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, CA
| | - Vanessa C Zarubin
- Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, CA
| | - Tara A Niendam
- Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, CA
| | - J Daniel Ragland
- Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, CA
| | - Laura M Tully
- Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, CA
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, Center for Neuroscience, University of California, Davis, CA
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Neuroanatomy of Patients with Deficit Schizophrenia: An Exploratory Quantitative Meta-Analysis of Structural Neuroimaging Studies. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17176227. [PMID: 32867189 PMCID: PMC7503710 DOI: 10.3390/ijerph17176227] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 08/17/2020] [Accepted: 08/19/2020] [Indexed: 11/29/2022]
Abstract
Little is known regarding the neuroanatomical correlates of patients with deficit schizophrenia or persistent negative symptoms. In this meta-analysis, we aimed to determine whether patients with deficit schizophrenia have characteristic brain abnormalities. We searched PubMed, CINAHL and Ovid to identify studies that examined the various regions of interest amongst patients with deficit schizophrenia, patients with non-deficit schizophrenia and healthy controls. A total of 24 studies met our inclusion criteria. A random-effects model was used to calculate a combination of outcome measures, and heterogeneity was assessed by the I2 statistic and Cochran’s Q statistic. Our findings suggested that there was statistically significant reduction in grey matter volume (−0.433, 95% confidence interval (CI): −0.853 to −0.014, p = 0.043) and white matter volume (−0.319, 95% CI: −0.619 to −0.018, p = 0.038) in patients with deficit schizophrenia compared to healthy controls. There is also statistically significant reduction in total brain volume (−0.212, 95% CI: −0.384 to −0.041, p = 0.015) and white matter volume (−0.283, 95% CI: −0.546 to −0.021, p = 0.034) in patients with non-deficit schizophrenia compared to healthy controls. Between patients with deficit and non-deficit schizophrenia, there were no statistically significant differences in volumetric findings across the various regions of interest.
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14
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Mow JL, Gandhi A, Fulford D. Imaging the "social brain" in schizophrenia: A systematic review of neuroimaging studies of social reward and punishment. Neurosci Biobehav Rev 2020; 118:704-722. [PMID: 32841653 DOI: 10.1016/j.neubiorev.2020.08.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 06/20/2020] [Accepted: 08/07/2020] [Indexed: 10/23/2022]
Abstract
Decreased social functioning and high levels of loneliness and social isolation are common in schizophrenia spectrum disorders (SSD), contributing to reduced quality of life. One key contributor to social impairment is low social motivation, which may stem from aberrant neural processing of socially rewarding or punishing stimuli. To summarize research on the neurobiology of social motivation in SSD, we performed a systematic literature review of neuroimaging studies involving the presentation of social stimuli intended to elicit feelings of reward and/or punishment. Across 11 studies meeting criteria, people with SSD demonstrated weaker modulation of brain activity in regions within a proposed social interaction network, including prefrontal, cingulate, and striatal regions, as well as the amygdala and insula. Firm conclusions regarding neural differences in SSD in these regions, as well as connections within networks, are limited due to conceptual and methodological inconsistencies across the available studies. We conclude by making recommendations for the study of social reward and punishment processing in SSD in future research.
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Affiliation(s)
- Jessica L Mow
- Department of Psychological & Brain Sciences, Boston University, 64 Cummington Mall, Boston, MA, 02215, United States.
| | - Arti Gandhi
- Sargent College of Health and Rehabilitation Sciences, Boston University, 635 Commonwealth Avenue, Boston, MA, 02215, United States
| | - Daniel Fulford
- Department of Psychological & Brain Sciences, Boston University, 64 Cummington Mall, Boston, MA, 02215, United States; Sargent College of Health and Rehabilitation Sciences, Boston University, 635 Commonwealth Avenue, Boston, MA, 02215, United States
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15
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Güleken MD, Akbaş T, Erden SÇ, Akansel V, Al ZC, Özer ÖA. The effect of bilateral high frequency repetitive transcranial magnetic stimulation on cognitive functions in schizophrenia. SCHIZOPHRENIA RESEARCH-COGNITION 2020; 22:100183. [PMID: 32714846 PMCID: PMC7371913 DOI: 10.1016/j.scog.2020.100183] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 06/02/2020] [Accepted: 06/03/2020] [Indexed: 11/30/2022]
Abstract
Despite their major effects on positive symptoms, antipsychotics do not have a significant effect on cognition in schizophrenia Bilateral high frequency rTMS targeting dorsolateral prefrontal cortices has been effective on working memory Bilateral 20 Hz rTMS improved attention and verbal working memory in schizophrenia patients, It also improved the competence of switching the perceptional set up under a disruptive effect towards new instructions, in this study
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Affiliation(s)
- Mehmet Diyaddin Güleken
- Department of Psychiatry, Gazi Yaşargil Training and Research Hospital, Sağlık Bilimleri Üniversitesi, Diyarbakır, Turkey
| | - Taner Akbaş
- Department of Psychiatry, Şişli Hamidiye Etfal Training and Research Hospital, Sağlık Bilimleri Üniversitesi, İstanbul, Turkey
| | - Selime Çelik Erden
- Department of Psychiatry, Şişli Hamidiye Etfal Training and Research Hospital, Sağlık Bilimleri Üniversitesi, İstanbul, Turkey
| | - Veysel Akansel
- Department of Psychiatry, Kanuni Sultan Süleyman Training and Research Hospital, İstanbul, Turkey
| | - Zeliha Cengiz Al
- Department of Psychiatry, Dr. Cevdet Aykan Psychiatry Hospital, Tokat, Turkey
| | - Ömer Akil Özer
- Department of Psychiatry, Şişli Hamidiye Etfal Training and Research Hospital, Sağlık Bilimleri Üniversitesi, İstanbul, Turkey
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16
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Chand GB, Dwyer DB, Erus G, Sotiras A, Varol E, Srinivasan D, Doshi J, Pomponio R, Pigoni A, Dazzan P, Kahn RS, Schnack HG, Zanetti MV, Meisenzahl E, Busatto GF, Crespo-Facorro B, Pantelis C, Wood SJ, Zhuo C, Shinohara RT, Shou H, Fan Y, Gur RC, Gur RE, Satterthwaite TD, Koutsouleris N, Wolf DH, Davatzikos C. Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning. Brain 2020; 143:1027-1038. [PMID: 32103250 DOI: 10.1093/brain/awaa025] [Citation(s) in RCA: 143] [Impact Index Per Article: 35.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 11/19/2019] [Accepted: 12/16/2019] [Indexed: 11/14/2022] Open
Abstract
Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium. Regional volumetric measures of grey matter, white matter, and CSF were used to identify distinct and reproducible neuroanatomical subtypes of schizophrenia. Two distinct neuroanatomical subtypes were found. Subtype 1 showed widespread lower grey matter volumes, most prominent in thalamus, nucleus accumbens, medial temporal, medial prefrontal/frontal and insular cortices. Subtype 2 showed increased volume in the basal ganglia and internal capsule, and otherwise normal brain volumes. Grey matter volume correlated negatively with illness duration in Subtype 1 (r = -0.201, P = 0.016) but not in Subtype 2 (r = -0.045, P = 0.652), potentially indicating different underlying neuropathological processes. The subtypes did not differ in age (t = -1.603, df = 305, P = 0.109), sex (chi-square = 0.013, df = 1, P = 0.910), illness duration (t = -0.167, df = 277, P = 0.868), antipsychotic dose (t = -0.439, df = 210, P = 0.521), age of illness onset (t = -1.355, df = 277, P = 0.177), positive symptoms (t = 0.249, df = 289, P = 0.803), negative symptoms (t = 0.151, df = 289, P = 0.879), or antipsychotic type (chi-square = 6.670, df = 3, P = 0.083). Subtype 1 had lower educational attainment than Subtype 2 (chi-square = 6.389, df = 2, P = 0.041). In conclusion, we discovered two distinct and highly reproducible neuroanatomical subtypes. Subtype 1 displayed widespread volume reduction correlating with illness duration, and worse premorbid functioning. Subtype 2 had normal and stable anatomy, except for larger basal ganglia and internal capsule, not explained by antipsychotic dose. These subtypes challenge the notion that brain volume loss is a general feature of schizophrenia and suggest differential aetiologies. They can facilitate strategies for clinical trial enrichment and stratification, and precision diagnostics.
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Affiliation(s)
- Ganesh B Chand
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Dominic B Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Guray Erus
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Aristeidis Sotiras
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, USA
| | - Erdem Varol
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Statistics, Zuckerman Institute, Columbia University, New York, USA
| | - Dhivya Srinivasan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Jimit Doshi
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Raymond Pomponio
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Alessandro Pigoni
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany.,Department of Neurosciences and Mental Health, University of Milan, Milan, Italy
| | - Paola Dazzan
- Institute of Psychiatry, King's College London, London, UK
| | - Rene S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Hugo G Schnack
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marcus V Zanetti
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.,Hospital Sírio-Libanês, São Paulo, Brazil
| | - Eva Meisenzahl
- LVR-Klinikum Düsseldorf, Kliniken der Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Geraldo F Busatto
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Benedicto Crespo-Facorro
- University of Cantabria; IDIVAL-CIBERSAM, Cantabria, Spain.,Department of Psychiatry, School of Medicine, University Hospital Virgen del Rocio, University of Sevilla, Spain
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, Australia
| | - Stephen J Wood
- Orygen, National Centre of Excellence for Youth Mental Health, Melbourne, Australia.,Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia.,School of Psychology, University of Birmingham, Edgbaston, UK
| | - Chuanjun Zhuo
- Department of Psychiatric-Neuroimaging-Genetics and Co-morbidity Laboratory (PNGC-Lab), Nankai University Affiliated Tianjin Anding Hospital, Tianjin Medical University, Tianjin, China.,Department of Psychiatry, Tianjin Medical University, Tianjin, China
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Haochang Shou
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Ruben C Gur
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Raquel E Gur
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Theodore D Satterthwaite
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Daniel H Wolf
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Christos Davatzikos
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
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17
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Predicting response to electroconvulsive therapy combined with antipsychotics in schizophrenia using multi-parametric magnetic resonance imaging. Schizophr Res 2020; 216:262-271. [PMID: 31826827 DOI: 10.1016/j.schres.2019.11.046] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 09/04/2019] [Accepted: 11/25/2019] [Indexed: 12/23/2022]
Abstract
Electroconvulsive therapy (ECT) has been shown to be effective in schizophrenia, particularly when rapid symptom reduction is needed or in cases of resistance to drug treatment. However, there are no markers available to predict response to ECT. Here, we examine whether multi-parametric magnetic resonance imaging (MRI)-based radiomic features can predict response to ECT for individual patients. A total of 57 treatment-resistant schizophrenia patients, or schizophrenia patients with an acute episode or suicide attempts were randomly divided into primary (42 patients) and test (15 patients) cohorts. We collected T1-weighted structural MRI and diffusion MRI for 57 patients before receiving ECT and extracted 600 radiomic features for feature selection and prediction. To predict a continuous improvement in symptoms (ΔPANSS), the prediction process was performed with a support vector regression model based on a leave-one-out cross-validation framework in primary cohort and was tested in test cohort. The multi-parametric MRI-based radiomic model, including four structural MRI feature from left inferior frontal gyrus, right insula, left middle temporal gyrus and right superior temporal gyrus respectively and six diffusion MRI features from tracts connecting frontal or temporal gyrus possessed a low root mean square error of 15.183 in primary cohort and 14.980 in test cohort. The Pearson's correlation coefficients between predicted and actual values were 0.671 and 0.777 respectively. These results demonstrate that multi-parametric MRI-based radiomic features may predict response to ECT for individual patients. Such features could serve as prognostic neuroimaging biomarkers that provide a critical step toward individualized treatment response prediction in schizophrenia.
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18
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Xiao Y, Yan Z, Zhao Y, Tao B, Sun H, Li F, Yao L, Zhang W, Chandan S, Liu J, Gong Q, Sweeney JA, Lui S. Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI. Schizophr Res 2019; 214:11-17. [PMID: 29208422 DOI: 10.1016/j.schres.2017.11.037] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 11/19/2017] [Accepted: 11/27/2017] [Indexed: 02/05/2023]
Abstract
Although regional brain deficits have been demonstrated in schizophrenia patients by structural MRI studies, one important question that remains largely unanswered is whether the complex and subtle deficits revealed by MRI could be used as objective biomarkers to discriminate patients from healthy controls individually. To address this question, a total of 326 right-handed participants were recruited, including 163 drug-naïve first-episode schizophrenia (FES) patients and 163 demographically matched healthy controls. High-resolution anatomic data were acquired from all subjects and processed via Freesurfer software to obtain cortical thickness and surface area measurements. Subsequently, the Support Vector Machine (SVM) was used to explore the potential utility for cortical thickness and surface area measurements in the differentiation of individual patients and healthy controls. The accuracy of correct classification of patients and controls was 85.0% (specificity 87.0%, sensitivity 83.0%) for surface area and 81.8% (specificity 85.0%, sensitivity 76.9%) for cortical thickness (p<0.001 after permutation testing). Regions contributing to classification accuracy mainly included the gray matter in default mode, central executive, salience, and visual networks. Current findings, in a sample of never-treated FES patients, suggest that the patterns of illness-related gray matter changes has potential as a biomarker for identifying structural brain alterations in individuals with schizophrenia. Future prospective studies are needed to evaluate the utility of imaging biomarkers for research and potentially for clinical purpose.
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Affiliation(s)
- Yuan Xiao
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Zhihan Yan
- Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, China
| | - Youjin Zhao
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Bo Tao
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Huaiqiang Sun
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Fei Li
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Li Yao
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Wenjing Zhang
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Shah Chandan
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Jieke Liu
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - Qiyong Gong
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China
| | - John A Sweeney
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, USA
| | - Su Lui
- Department of Radiology, the Center for Medical Imaging, West China Hospital of Sichuan University, China.
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19
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Guo F, Zhu YQ, Li C, Wang XR, Wang HN, Liu WM, Wang LX, Tian P, Kang XW, Cui LB, Xi YB, Yin H. Gray matter volume changes following antipsychotic therapy in first-episode schizophrenia patients: A longitudinal voxel-based morphometric study. J Psychiatr Res 2019; 116:126-132. [PMID: 31233895 DOI: 10.1016/j.jpsychires.2019.06.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 06/13/2019] [Accepted: 06/14/2019] [Indexed: 12/15/2022]
Abstract
Despite evidence of structural brain abnormalities in schizophrenia, the current study aimed to explore the effects of antipsychotic treatment on gray matter (GM) volume using structural magnetic resonance imaging (MRI) and investigate the relationship between brain structure and treatment response. The GM volumes of 33 patients with first-episode schizophrenia were calculated with voxel-based morphometry (VBM), with 33 matched healthy controls. Longitudinal volume changes within subjects after 4-month antipsychotic treatment were also evaluated. Correlation between volumetric changes and clinical symptoms derived from the Positive and Negative Syndrome Scale (PANSS) were further investigated. Compared with healthy controls, decreased GM volumes in the frontal gyrus were observed in schizophrenia patients. After 4-month treatment, patients showed significantly decreased GM volume primarily in the bilateral frontal, temporal and left parietal brain regions. In addition, the GM volume changes of the left postcentral gyrus was positively correlated with negative symptoms improvement, and the correlation analysis revealed the total PANSS scores changes were associated with GM volume changes in the right inferior frontal gyrus and the right superior temporal gyrus. Besides, non-responders had reduced GM volume in the bilateral middle frontal gyrus and the right superior frontal gyrus compared with responders and healthy controls. Our results suggest that the abnormality in the right frontal gyrus exists in the early stage of schizophrenia. Moreover, the relationship between antipsychotics and structural changes was identified. The GM volume might have the potential to reflect the symptom improvement in schizophrenia patients. And MRI may assist in predicting the antipsychotic treatment response in first-episode schizophrenia patients.
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Affiliation(s)
- Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Key Laboratory of Molecular Imaging of the Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Yuan-Qiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Xing-Rui Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Wen-Ming Liu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Liu-Xian Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Ping Tian
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Xiao-Wei Kang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Long-Biao Cui
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China
| | - Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
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20
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Acar E, Schenker C, Levin-Schwartz Y, Calhoun VD, Adali T. Unraveling Diagnostic Biomarkers of Schizophrenia Through Structure-Revealing Fusion of Multi-Modal Neuroimaging Data. Front Neurosci 2019; 13:416. [PMID: 31130835 PMCID: PMC6509223 DOI: 10.3389/fnins.2019.00416] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 04/11/2019] [Indexed: 11/13/2022] Open
Abstract
Fusing complementary information from different modalities can lead to the discovery of more accurate diagnostic biomarkers for psychiatric disorders. However, biomarker discovery through data fusion is challenging since it requires extracting interpretable and reproducible patterns from data sets, consisting of shared/unshared patterns and of different orders. For example, multi-channel electroencephalography (EEG) signals from multiple subjects can be represented as a third-order tensor with modes: subject, time, and channel, while functional magnetic resonance imaging (fMRI) data may be in the form of subject by voxel matrices. Traditional data fusion methods rearrange higher-order tensors, such as EEG, as matrices to use matrix factorization-based approaches. In contrast, fusion methods based on coupled matrix and tensor factorizations (CMTF) exploit the potential multi-way structure of higher-order tensors. The CMTF approach has been shown to capture underlying patterns more accurately without imposing strong constraints on the latent neural patterns, i.e., biomarkers. In this paper, EEG, fMRI, and structural MRI (sMRI) data collected during an auditory oddball task (AOD) from a group of subjects consisting of patients with schizophrenia and healthy controls, are arranged as matrices and higher-order tensors coupled along the subject mode, and jointly analyzed using structure-revealing CMTF methods [also known as advanced CMTF (ACMTF)] focusing on unique identification of underlying patterns in the presence of shared/unshared patterns. We demonstrate that joint analysis of the EEG tensor and fMRI matrix using ACMTF reveals significant and biologically meaningful components in terms of differentiating between patients with schizophrenia and healthy controls while also providing spatial patterns with high resolution and improving the clustering performance compared to the analysis of only the EEG tensor. We also show that these patterns are reproducible, and study reproducibility for different model parameters. In comparison to the joint independent component analysis (jICA) data fusion approach, ACMTF provides easier interpretation of EEG data by revealing a single summary map of the topography for each component. Furthermore, fusion of sMRI data with EEG and fMRI through an ACMTF model provides structural patterns; however, we also show that when fusing data sets from multiple modalities, hence of very different nature, preprocessing plays a crucial role.
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Affiliation(s)
- Evrim Acar
- Machine Intelligence Department, Simula Metropolitan Center for Digital Engineering, Oslo, Norway
| | - Carla Schenker
- Machine Intelligence Department, Simula Metropolitan Center for Digital Engineering, Oslo, Norway
| | - Yuri Levin-Schwartz
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Vince D. Calhoun
- The Mind Research Network, Albuquerque, NM, United States
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, United States
| | - Tülay Adali
- Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, United States
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21
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Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect. PLoS One 2018; 13:e0205369. [PMID: 30300425 PMCID: PMC6177186 DOI: 10.1371/journal.pone.0205369] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2018] [Accepted: 09/23/2018] [Indexed: 01/01/2023] Open
Abstract
Several studies have produced extensive evidence on white matter abnormalities in schizophrenia (SZ). However, optimum consistency and reproducibility have not been achieved, and reported low white matter tract integrity in patients with SZ varies between studies. A whole-brain imaging study with a large sample size is needed. This study aimed to investigate white matter integrity in the corpus callosum and connections between regions of interests (ROIs) in the same hemisphere in 122 patients with SZ and 129 healthy controls with public neuroimaging data from SchizConnect. For each diffusion-weighted image (DWI), two-tensor full-brain tractography was performed; DWIs were parcellated by processing and registering T1 images with FreeSurfer and Advanced Normalization Tools. White matter query language was used to extract white matter fiber tracts. We evaluated group differences in means of diffusion measures between the patients and controls, and correlations of diffusion measures with the severity of clinical symptoms and cognitive impairment in the patients using the Positive and Negative Syndrome Scale (PANSS), a letter-number sequencing (LNS) test, vocabulary test, letter fluency test, category fluency test, and trail-making test, part A. To correct for multiple comparisons, a false discovery rate of q < 0.05 was applied. In patients with SZ, we observed significant radial diffusivity (RD) and trace (TR) increases in left thalamo-occipital tracts and the right uncinate fascicle, and a significant RD increase in the right middle longitudinal fascicle (MDLF) and the right superior longitudinal fascicle ii. Correlations were present between TR of left thalamo-occipital tracts, and the letter fluency test and the LNS test, and RD in the right MDLF and PANSS positive subscale score. However, these correlations were not significant after correction for multiple comparisons. These results indicated widespread white matter fiber tract abnormalities in patients with SZ, contributing to SZ pathophysiology.
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22
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Du Y, Ning Y, Wen Y, Liu L, Liang X, Li P, Ding M, Zhao Y, Cheng B, Ma M, Zhang L, Cheng S, Yu W, Hu S, Guo X, Zhang F. A genome-wide pathway enrichment analysis identifies brain region related biological pathways associated with intelligence. Psychiatry Res 2018; 268:238-242. [PMID: 30071386 DOI: 10.1016/j.psychres.2018.07.029] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 05/31/2018] [Accepted: 07/17/2018] [Indexed: 01/15/2023]
Abstract
Intelligence is an important quantitative trait associated with human cognitive ability. The genetic basis of intelligence remains unclear now. Utilizing the latest chromosomal enhancer maps of brain regions, we explored brain region related biological pathways associated with intelligence. Summary data was derived from a large scale genome-wide association study (GWAS) of human, involving 78,308 unrelated individuals from 13 cohorts. The chromosomal enhancer maps of 8 brain regions were then aligned with the GWAS summary data to obtain the association testing results of enhancer regions for intelligence. Gene set enrichment analysis was then conducted to identify the biological pathways associated with intelligence for 8 brain regions, respectively. A total of 178 KEGG pathways was analyzed in this study. We detected multiple biological pathways showing cross brain regions or brain region specific association signals for human intelligence. For instance, KEGG_SYSTEMIC_LUPUS_ERYTHEMATOSUS pathway presented association signals for intelligence across 8 brain regions (all P value < 0.01). KEGG_GLYCOSPHINGOLIPID_BIOSYNTHESIS_GANGLIO_SERIES was detected for 5 brain regions. We also identified several brain region specific pathways, such as AMINO_SUGAR_AND_NUCLEOTIDE_SUGAR_METABOLISM for Germinal Matrix (P value = 0.009) and FRUCTOSE_AND_MANNOSE_METABOLISM for Anterior Caudate (P value = 0.005). Our study results provided novel clues for understanding the genetic mechanism of intelligence.
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Affiliation(s)
- Yanan Du
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China.
| | - Yujie Ning
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Yan Wen
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Li Liu
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Xiao Liang
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Ping Li
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Miao Ding
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Yan Zhao
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Bolun Cheng
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Mei Ma
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Lu Zhang
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Shiqiang Cheng
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Wenxing Yu
- Department of Osteonecrosis and Joint Reconstruction, Xi'an Red Cross Hospital, Xi'an Jiaotong University, Shaanxi Province, PR China
| | - Shouye Hu
- Department of Osteonecrosis and Joint Reconstruction, Xi'an Red Cross Hospital, Xi'an Jiaotong University, Shaanxi Province, PR China
| | - Xiong Guo
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China
| | - Feng Zhang
- School of Public Health, Health Science Center, Xi'an Jiaotong University, No., 76 Yan Ta West Road, Xi'an 710061, PR China.
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Prendergast DM, Karlsgodt KH, Fales CL, Ardekani BA, Szeszko PR. Corpus callosum shape and morphology in youth across the psychosis Spectrum. Schizophr Res 2018; 199:266-273. [PMID: 29656909 DOI: 10.1016/j.schres.2018.04.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/12/2018] [Accepted: 04/03/2018] [Indexed: 11/16/2022]
Abstract
The corpus callosum is the largest white matter tract in the human brain connecting and coordinating homologous regions of the right and left hemispheres and has been strongly implicated in the pathogenesis of psychosis. We investigated corpus callosum morphology in a large community cohort of 917 individuals (aged 8-21), including 267 endorsing subsyndromal or threshold psychotic symptoms (207 on the psychosis spectrum and 60 with limited psychosis based on previously published criteria) and 650 non-psychotic volunteers. We used a highly reliable and previously published algorithm to automatically identify the midsagittal plane and to align the corpus callosum along the anterior and posterior commissures for segmentation, thereby eliminating these sources of error variance in dependent measures, which included perimeter, length, mean thickness and shape (circularity). The parcellation scheme divided the corpus callosum into 7 subregions that consisted of the rostrum, genu, rostral body, anterior midbody, posterior midbody, isthmus, and splenium. Both individuals endorsing psychotic symptoms and those with limited psychosis had significantly (p<.05) smaller area and lower thickness measures compared to healthy volunteers, but did not differ significantly from each other. Findings were relatively widespread indicating a relatively global effect not circumscribed to any particular corpus callosum subregion. These data are consistent with the hypothesis that corpus callosum abnormalities may be evident early in the course of illness and predate the onset of frank psychosis. Given that these measures can be easily obtained and are highly reliable they may assist in the identification of individuals at future risk for psychosis.
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Affiliation(s)
| | - K H Karlsgodt
- Department of Psychology, University of California at Los Angeles, Los Angeles, CA, USA
| | - C L Fales
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - B A Ardekani
- Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - P R Szeszko
- James J. Peters VA Medical Center, Mental Health Patient Care Center and Mental Illness Research Education Clinical Center (MIRECC), Bronx, NY, USA; Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY, USA
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24
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Mitelman SA, Bralet MC, Haznedar MM, Hollander E, Shihabuddin L, Hazlett EA, Buchsbaum MS. Diametrical relationship between gray and white matter volumes in autism spectrum disorder and schizophrenia. Brain Imaging Behav 2018; 11:1823-1835. [PMID: 27882449 DOI: 10.1007/s11682-016-9648-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Autism spectrum disorders and schizophrenia have been variously characterized as separate nosological entities with overlapping deficits in social cognition or diametrical extremes of a phenotypic continuum. This study aimed to determine how these models apply to comparative morphometric data. MRI scans of the brain were obtained in 49 subjects with schizophrenia, 20 subjects with autism and 39 healthy controls. Images were parcellated into 40 Brodmann areas and entered into repeated-measures ANOVA for between-group comparison of global and localized gray and white matter volumes. A pattern of lower gray mater volumes and greater white matter volumes was found in subjects with schizophrenia in comparison to subjects with autism. For both gray and white matter, this pattern was most pronounced in regions associated with motor-premotor and anterior frontal cortex, anterior cingulate, fusiform, superior and middle temporal gyri. Patient groups tended to diverge from healthy controls in opposite directions, with greater-than-normal gray matter volumes and lower-than-normal white matter volumes in subjects with autism and reversed patterns in subjects with schizophrenia. White matter reductions in subjects with autism were seen in posterior frontal lobe and along the cingulate arch. Normal hemispheric asymmetry in the temporal lobe was effaced in subjects with autism and schizophrenia, especially in the latter. Nearly identical distribution of changes and diametrically divergent volumetry suggest that autism and schizophrenia may occupy opposite extremes of the same cognitive continuum.
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Affiliation(s)
- Serge A Mitelman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. .,Department of Psychiatry, Division of Child and Adolescent Psychiatry, Elmhurst Hospital Center, 79-01 Broadway, Elmhurst, NY, 11373, USA.
| | - Marie-Cecile Bralet
- Crisalid Unit (FJ5), CHI Clermont de l'Oise, 2 rue des finets, 60607, Clermont, France.,Inserm Unit U669, Maison de Solenn, Universities Paris 5-11, 75014, Paris, France.,GDR 3557 Recherche Psychiatrie, Paris, France
| | - M Mehmet Haznedar
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.,Outpatient Psychiatry Care Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Eric Hollander
- Autism and Obsessive-Compulsive Spectrum Program, Anxiety and Depression Program, Department of Psychiatry and Behavioral Science, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, 10467, USA
| | - Lina Shihabuddin
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Erin A Hazlett
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.,Research and Development and VISN 3 Mental Illness Research, Education, and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Monte S Buchsbaum
- Departments of Psychiatry and Radiology, San Diego School of Medicine, NeuroPET Center, University of California, 11388 Sorrento Valley Road, Suite #100, San Diego, CA, 92121, USA
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25
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Chan CC, Szeszko PR, Wong E, Tang CY, Kelliher C, Penner JD, Perez-Rodriguez MM, Rosell DR, McClure M, Roussos P, New AS, Siever LJ, Hazlett EA. Frontal and temporal cortical volume, white matter tract integrity, and hemispheric asymmetry in schizotypal personality disorder. Schizophr Res 2018; 197:226-232. [PMID: 29454512 PMCID: PMC8043048 DOI: 10.1016/j.schres.2018.01.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 11/29/2017] [Accepted: 01/21/2018] [Indexed: 12/29/2022]
Abstract
Abnormalities in temporal and frontal cortical volume, white matter tract integrity, and hemispheric asymmetry have been implicated in schizophrenia-spectrum disorders. Schizotypal personality disorder can provide insight into vulnerability and protective factors in these disorders without the confounds associated with chronic psychosis. However, multimodal imaging and asymmetry studies in SPD are sparse. Thirty-seven individuals with SPD and 29 healthy controls (HC) received clinical interviews and 3T magnetic resonance T1-weighted and diffusion tensor imaging scans. Mixed ANOVAs were performed on gray matter volumes of the lateral temporal regions involved in auditory and language processing and dorsolateral prefrontal cortex involved in executive functioning, as well as fractional anisotropy (FA) of prominent white matter tracts that connect frontal and temporal lobes. In the temporal lobe regions, there were no group differences in volume, but SPD had reduced right>left middle temporal gyrus volume asymmetry compared to HC and lacked the right>left asymmetry in the inferior temporal gyrus volume seen in HC. In the frontal regions, there were no differences between groups on volume or asymmetry. In the white matter tracts, SPD had reduced FA in the left sagittal stratum and superior longitudinal fasciculus, and increased right>left asymmetry in sagittal stratum FA compared to HC. In the SPD group, lower left superior longitudinal fasciculus FA was associated with greater severity of disorganization symptoms. Findings suggest that abnormities in structure and asymmetry of temporal regions and frontotemporal white matter tract integrity are implicated in SPD pathology.
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Affiliation(s)
- Chi C. Chan
- VISN 2 Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Corresponding author at: Mental Illness Research, Education, and Clinical Center, James J. Peters VA Medical Center, 130 West Kingsbridge Road, Room 6A-41G, Bronx, NY 10468, USA, (C.C. Chan)
| | - Philip R. Szeszko
- VISN 2 Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edmund Wong
- Translational and Molecular Imaging Institute, Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Cheuk Y. Tang
- Translational and Molecular Imaging Institute, Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Caitlin Kelliher
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Justin D. Penner
- VISN 2 Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Daniel R. Rosell
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Margaret McClure
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- VISN 2 Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Department of Genetics and Genomic Sciences and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Antonia S. New
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Larry J. Siever
- VISN 2 Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Erin A. Hazlett
- VISN 2 Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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26
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Lemaitre AL, Lafargue G, Duffau H, Herbet G. Damage to the left uncinate fasciculus is associated with heightened schizotypal traits: A multimodal lesion-mapping study. Schizophr Res 2018; 197:240-248. [PMID: 29499963 DOI: 10.1016/j.schres.2018.02.027] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 02/07/2018] [Accepted: 02/17/2018] [Indexed: 12/11/2022]
Abstract
A growing body of evidence suggests that individuals with pronounced schizotypal traits also display particular neurophysiological and morphological features - notably with regard to left frontotemporal connectivity. However, the studies published to date have focused on subclinical subjects and psychiatric patients, rather than brain-damaged patients. Here, we used the French version of the Schizotypal Personality Questionnaire to assess schizotypal traits in a sample of 97 patients having undergone surgical resection of a diffuse low-grade glioma. Patients having received other neurooncological treatments (including chemotherapy and radiotherapy) were not included. A combination of ROI-based based voxel-wise and tract-wise lesion-symptom mapping and a disconnectome analysis were performed, in order to identify the putative neural network associated with schizotypy. The ROI-based lesion-symptom mapping revealed a significant relationship between the cognitive-perceptual (positive) dimension of schizotypy and the left inferior gyrus (including the pars opercularis and the pars orbitalis). Importantly, we found that disconnection of the left uncinate fasciculus (UF) was a powerful predictor of the positive dimension of schizotypy. Lastly, the disconnection analysis indicated that the positive dimension of schizotypy was significantly associated with the white matter fibres deep in the left orbital and inferior frontal gyri and the left superior temporal pole, which mainly correspond to the spatial topography of the left UF. Taken as a whole, our results suggest that dysconnectivity of the neural network supplied by the left UF is associated with heightened positive schizotypal traits. Our new findings may be of value in interpreting current research in the field of biological psychiatry.
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Affiliation(s)
- Anne-Laure Lemaitre
- Univ. Lille, EA 4072 - PSITEC - Psychologie: Interactions, Temps, Emotions, Cognition, F-59000 Lille, France; Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34295 Montpellier, France
| | - Gilles Lafargue
- Laboratoire Cognition, Santé, Société, C2S, EA 6291, Université de Reims Champagne-Ardenne, F-51096 Reims, France
| | - Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34295 Montpellier, France; Institute for Neuroscience of Montpellier, INSERM U1051 (Plasticity of Central Nervous System, Human Stem Cells and Glial Tumors research group), Saint Eloi Hospital, Montpellier University Medical Center, F-34091 Montpellier, France; University of Montpellier, F-34090 Montpellier, France
| | - Guillaume Herbet
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34295 Montpellier, France; Institute for Neuroscience of Montpellier, INSERM U1051 (Plasticity of Central Nervous System, Human Stem Cells and Glial Tumors research group), Saint Eloi Hospital, Montpellier University Medical Center, F-34091 Montpellier, France; University of Montpellier, F-34090 Montpellier, France.
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27
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Guenette JP, Stern RA, Tripodis Y, Chua AS, Schultz V, Sydnor VJ, Somes N, Karmacharya S, Lepage C, Wrobel P, Alosco ML, Martin BM, Chaisson CE, Coleman MJ, Lin AP, Pasternak O, Makris N, Shenton ME, Koerte IK. Automated versus manual segmentation of brain region volumes in former football players. NEUROIMAGE-CLINICAL 2018; 18:888-896. [PMID: 29876273 PMCID: PMC5988230 DOI: 10.1016/j.nicl.2018.03.026] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 02/02/2018] [Accepted: 03/21/2018] [Indexed: 12/14/2022]
Abstract
Objectives To determine whether or not automated FreeSurfer segmentation of brain regions considered important in repetitive head trauma can be analyzed accurately without manual correction. Materials and methods 3 T MR neuroimaging was performed with automated FreeSurfer segmentation and manual correction of 11 brain regions in former National Football League (NFL) players with neurobehavioral symptoms and in control subjects. Automated segmentation and manually-corrected volumes were compared using an intraclass correlation coefficient (ICC). Linear mixed effects regression models were also used to estimate between-group mean volume comparisons and to correlate former NFL player brain volumes with neurobehavioral factors. Results Eighty-six former NFL players (55.2 ± 8.0 years) and 22 control subjects (57.0 ± 6.6 years) were evaluated. ICC was highly correlated between automated and manually-corrected corpus callosum volumes (0.911), lateral ventricular volumes (right 0.980, left 0.967), and amygdala-hippocampal complex volumes (right 0.713, left 0.731), but less correlated when amygdalae (right -0.170, left -0.090) and hippocampi (right 0.539, left 0.637) volumes were separately delineated and also less correlated for cingulate gyri volumes (right 0.639, left 0.351). Statistically significant differences between former NFL player and controls were identified in 8 of 11 regions with manual correction but in only 4 of 11 regions without such correction. Within NFL players, manually corrected brain volumes were significantly associated with 3 neurobehavioral factors, but a different set of 3 brain regions and neurobehavioral factor correlations was observed for brain region volumes segmented without manual correction. Conclusions Automated FreeSurfer segmentation of the corpus callosum, lateral ventricles, and amygdala-hippocampus complex may be appropriate for analysis without manual correction. However, FreeSurfer segmentation of the amygdala, hippocampus, and cingulate gyrus need further manual correction prior to performing group comparisons and correlations with neurobehavioral measures.
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Affiliation(s)
- Jeffrey P Guenette
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Robert A Stern
- BU Alzheimer's Disease and CTE Center, Boston University, Boston, MA, United States; Departments of Neurology, Neurosurgery, and Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Yorghos Tripodis
- BU Alzheimer's Disease and CTE Center, Boston University, Boston, MA, United States; Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Alicia S Chua
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Vivian Schultz
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Valerie J Sydnor
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Nathaniel Somes
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Sarina Karmacharya
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Christian Lepage
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Pawel Wrobel
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Michael L Alosco
- BU Alzheimer's Disease and CTE Center, Boston University, Boston, MA, United States
| | - Brett M Martin
- Data Coordinating Center, Boston University School of Public Health, Boston, MA, United States
| | - Christine E Chaisson
- BU Alzheimer's Disease and CTE Center, Boston University, Boston, MA, United States; Data Coordinating Center, Boston University School of Public Health, Boston, MA, United States
| | - Michael J Coleman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Alexander P Lin
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Center for Clinical Spectroscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Center for Neural Systems Investigations, Massachusetts General Hospital, Boston, MA, United States
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; VA Boston Healthcare System, Brockton Division, Brockton, MA, United States
| | - Inga K Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany.
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28
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Lysaker PH, Pattison ML, Leonhardt BL, Phelps S, Vohs JL. Insight in schizophrenia spectrum disorders: relationship with behavior, mood and perceived quality of life, underlying causes and emerging treatments. World Psychiatry 2018; 17:12-23. [PMID: 29352540 PMCID: PMC5775127 DOI: 10.1002/wps.20508] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Poor insight in schizophrenia is prevalent across cultures and phases of illness. In this review, we examine the recent research on the relationship of insight with behavior, mood and perceived quality of life, on its complex roots, and on the effects of existing and emerging treatments. This research indicates that poor insight predicts poorer treatment adherence and therapeutic alliance, higher symptom severity and more impaired community function, while good insight predicts a higher frequency of depression and demoralization, especially when coupled with stigma and social disadvantage. This research also suggests that poor insight may arise in response to biological, experiential, neuropsychological, social-cognitive, metacognitive and socio-political factors. Studies of the effects of existing and developing treatments indicate that they may influence insight. In the context of earlier research and historical models, these findings support an integrative model of poor insight. This model suggests that insight requires the integration of information about changes in internal states, external circumstances, others' perspectives and life trajectory as well as the multifaceted consequences and causes of each of those changes. One implication is that treatments should, beyond providing education, seek to assist persons with schizophrenia to integrate the broad range of complex and potentially deeply painful experiences which are associated with mental illness into their own personally meaningful, coherent and adaptive picture.
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Affiliation(s)
- Paul H Lysaker
- Roudebush VA Medical Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Michelle L Pattison
- College of Applied Behavioral Sciences, University of Indianapolis, Indianapolis, IN, USA
| | - Bethany L Leonhardt
- Indiana University School of Medicine, Eskenazi Health-Midtown Community Mental Health, Indianapolis, IN, USA
| | | | - Jenifer L Vohs
- Indiana University School of Medicine, Indianapolis, IN, USA
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29
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Vitolo E, Tatu MK, Pignolo C, Cauda F, Costa T, Ando' A, Zennaro A. White matter and schizophrenia: A meta-analysis of voxel-based morphometry and diffusion tensor imaging studies. Psychiatry Res Neuroimaging 2017; 270:8-21. [PMID: 28988022 DOI: 10.1016/j.pscychresns.2017.09.014] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2017] [Revised: 09/20/2017] [Accepted: 09/20/2017] [Indexed: 12/15/2022]
Abstract
Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) are the most implemented methodologies to detect alterations of both gray and white matter (WM). However, the role of WM in mental disorders is still not well defined. We aimed at clarifying the role of WM disruption in schizophrenia and at identifying the most frequently involved brain networks. A systematic literature search was conducted to identify VBM and DTI studies focusing on WM alterations in patients with schizophrenia compared to control subjects. We selected studies reporting the coordinates of WM reductions and we performed the anatomical likelihood estimation (ALE). Moreover, we labeled the WM bundles with an anatomical atlas and compared VBM and DTI ALE-scores of each significant WM tract. A total of 59 studies were eligible for the meta-analysis. WM alterations were reported in 31 and 34 foci with VBM and DTI methods, respectively. The most occurred WM bundles in both VBM and DTI studies and largely involved in schizophrenia were long projection fibers, callosal and commissural fibers, part of motor descending fibers, and fronto-temporal-limbic pathways. The meta-analysis showed a widespread WM disruption in schizophrenia involving specific cerebral circuits instead of well-defined regions.
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Affiliation(s)
- Enrico Vitolo
- Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy.
| | - Mona Karina Tatu
- Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy.
| | - Claudia Pignolo
- Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy.
| | - Franco Cauda
- Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy; GCS-fMRI, Koelliker Hospital, Corso Galileo Ferraris 247/255, 10134 Turin, TO, Italy.
| | - Tommaso Costa
- Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy.
| | - Agata Ando'
- Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy.
| | - Alessandro Zennaro
- Department of Psychology, University of Turin, Via Po 14, 10123 Turin, TO, Italy.
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Lerner Y, Bleich-Cohen M, Solnik-Knirsh S, Yogev-Seligmann G, Eisenstein T, Madah W, Shamir A, Hendler T, Kremer I. Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia. NEUROIMAGE-CLINICAL 2017; 17:1047-1060. [PMID: 29349038 PMCID: PMC5768152 DOI: 10.1016/j.nicl.2017.12.030] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 11/28/2017] [Accepted: 12/20/2017] [Indexed: 01/10/2023]
Abstract
Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia (N = 15), their non-manifesting siblings (N = 14) and healthy controls (N = 15) listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC) approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings - high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale) revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.
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Affiliation(s)
- Yulia Lerner
- Tel Aviv Center for Brain Functions, Tel Aviv, Sourasky Medical Center, Tel Aviv, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neurosceince, Tel Aviv University, Tel Aviv, Israel.
| | - Maya Bleich-Cohen
- Tel Aviv Center for Brain Functions, Tel Aviv, Sourasky Medical Center, Tel Aviv, Israel
| | - Shimrit Solnik-Knirsh
- Tel Aviv Center for Brain Functions, Tel Aviv, Sourasky Medical Center, Tel Aviv, Israel
| | - Galit Yogev-Seligmann
- Tel Aviv Center for Brain Functions, Tel Aviv, Sourasky Medical Center, Tel Aviv, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Tamir Eisenstein
- Tel Aviv Center for Brain Functions, Tel Aviv, Sourasky Medical Center, Tel Aviv, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | - Alon Shamir
- MAZOR Mental Health Center, Acre, Israel; The Ruth and Bruce Rappaport Faculty of Medicine, Technion, Haifa, Israel
| | - Talma Hendler
- Tel Aviv Center for Brain Functions, Tel Aviv, Sourasky Medical Center, Tel Aviv, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neurosceince, Tel Aviv University, Tel Aviv, Israel; School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Ilana Kremer
- MAZOR Mental Health Center, Acre, Israel; The Ruth and Bruce Rappaport Faculty of Medicine, Technion, Haifa, Israel
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Fusar-Poli P, Meyer-Lindenberg A. Forty years of structural imaging in psychosis: promises and truth. Acta Psychiatr Scand 2016; 134:207-24. [PMID: 27404479 DOI: 10.1111/acps.12619] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/09/2016] [Indexed: 12/25/2022]
Abstract
OBJECTIVE Since the first study published in the Lancet in 1976, structural neuroimaging has been used in psychosis with the promise of imminent clinical utility. The actual impact of structural neuroimaging in psychosis is still unclear. METHOD We present here a critical review of studies involving structural magnetic resonance imaging techniques in patients with psychosis published between 1976 and 2015 in selected journals of relevance for the field. For each study, we extracted summary descriptive variables. Additionally, we qualitatively described the main structural findings of each article in summary notes and we employed a biomarker rating system based on quality of evidence (scored 1-4) and effect size (scored 1-4). RESULTS Eighty studies meeting the inclusion criteria were retrieved. The number of studies increased over time, reflecting an increased structural imaging research in psychosis. However, quality of evidence was generally impaired by small samples and unclear biomarker definitions. In particular, there was little attempt of replication of previous findings. The effect sizes ranged from small to modest. No diagnostic or prognostic biomarker for clinical use was identified. CONCLUSIONS Structural neuroimaging in psychosis research has not yet delivered on the clinical applications that were envisioned.
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Affiliation(s)
- P Fusar-Poli
- Institute of Psychiatry Psychology Neuroscience, King's College London, London, UK.,OASIS Clinic, SLaM NHS Foundation Trust, London, UK
| | - A Meyer-Lindenberg
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
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Factors associated with relapse in schizophrenia despite adherence to long-acting injectable antipsychotic therapy. Int Clin Psychopharmacol 2016; 31:202-9. [PMID: 26974214 DOI: 10.1097/yic.0000000000000125] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Many patients with schizophrenia will relapse despite uninterrupted antipsychotic (AP) long-acting therapy (LAT). This exploratory analysis examined variables associated with relapse despite ensured adherence to LAT. This was a post-hoc exploratory analysis of a 1-year study of risperidone long-acting injection in patients with stable schizophrenia or schizoaffective disorder (NCT00297388; N=323). Patients were discontinued from previous oral APs and randomly assigned to biweekly intramuscular injections of risperidone long-acting injectable 50 (n=163) or 25 mg (n=161) for 52 weeks. Cox proportional hazards regression models examined variables putatively associated with relapse. A total of 59/323 (18.3%) patients relapsed over 12 months despite continuous AP LAT. Variables associated with the risk of relapse included illness duration (6.0% increase each year; P=0.0003) and country (Canada vs. USA, 4.7-fold risk increase; P=0.0008). When illness duration was further categorized as ≤5, 6-10, and >10 years, patients with an illness duration of >10 versus ≤5 years were at greatest risk of relapse (>10 vs. ≤5 years associated with a 4.4-fold increase in the risk of relapse; P=0.0181). Findings suggest that patients with more chronic illness have a greater risk of relapse despite ensured treatment adherence, supporting the need for early intervention to prevent the deleterious effects of chronicity.
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Sato C, Hane M, Kitajima K. Relationship between ST8SIA2, polysialic acid and its binding molecules, and psychiatric disorders. Biochim Biophys Acta Gen Subj 2016; 1860:1739-52. [PMID: 27105834 DOI: 10.1016/j.bbagen.2016.04.015] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2015] [Revised: 04/15/2016] [Accepted: 04/16/2016] [Indexed: 12/21/2022]
Abstract
Polysialic acid (polySia, PSA) is a unique and functionally important glycan, particularly in vertebrate brains. It is involved in higher brain functions such as learning, memory, and social behaviors. Recently, an association between several genetic variations and single nucleotide polymorphisms (SNPs) of ST8SIA2/STX, one of two polysialyltransferase genes in vertebrates, and psychiatric disorders, such as schizophrenia (SZ), bipolar disorder (BD), and autism spectrum disorder (ASD), was reported based on candidate gene approaches and genome-wide studies among normal and mental disorder patients. It is of critical importance to determine if the reported mutations and SNPs in ST8SIA2 lead to impairments of the structure and function of polySia, which is the final product of ST8SIA2. To date, however, only a few such forward-directed studies have been conducted. In addition, the molecular mechanisms underlying polySia-involved brain functions remain unknown, although polySia was shown to have an anti-adhesive effect. In this report, we review the relationships between psychiatric disorders and polySia and/or ST8SIA2, and describe a new function of polySia as a regulator of neurologically active molecules, such as brain-derived neurotrophic factor (BDNF) and dopamine, which are deeply involved in psychiatric disorders. This article is part of a Special Issue entitled "Glycans in personalised medicine" Guest Editor: Professor Gordan Lauc.
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Affiliation(s)
- Chihiro Sato
- Bioscience and Biotechnology Center, Nagoya University, Chikusa, Nagoya 464-8601, Japan.
| | - Masaya Hane
- Bioscience and Biotechnology Center, Nagoya University, Chikusa, Nagoya 464-8601, Japan
| | - Ken Kitajima
- Bioscience and Biotechnology Center, Nagoya University, Chikusa, Nagoya 464-8601, Japan
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Regional Abnormality of Grey Matter in Schizophrenia: Effect from the Illness or Treatment? PLoS One 2016; 11:e0147204. [PMID: 26789520 PMCID: PMC4720276 DOI: 10.1371/journal.pone.0147204] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 12/30/2015] [Indexed: 12/25/2022] Open
Abstract
Both schizophrenia and antipsychotic treatment are known to modulate brain morphology. However, it is difficult to establish whether observed structural brain abnormalities are due to disease or the effects of treatment. The aim of this study was to investigate the effects of illness and antipsychotic treatment on brain structures in antipsychotic-naïve first-episode schizophrenia based on a longitudinal short-term design. Twenty antipsychotic-naïve subjects with first-episode schizophrenia and twenty-four age- and sex-matched healthy controls underwent 3T MRI scans. Voxel-based morphometry (VBM) was used to examine the brain structural abnormality in patients compared to healthy controls. Nine patients were included in the follow-up examination after 8 weeks of treatment. Tensor-based morphometry (TBM) was used to identify longitudinal brain structural changes. We observed significantly reduced grey matter volume in the right superior temporal gyrus in antipsychotic-naïve patients with schizophrenia compared with healthy controls. After 8 weeks of treatment, patients showed significantly increased grey matter volume primarily in the bilateral prefrontal cortex, insula, right thalamus, left superior occipital cortex and the bilateral cerebellum. In addition, a greater enlargement of the prefrontal cortex is associated with the improvement in negative symptoms, and a more enlarged thalamus is associated with greater improvement in positive symptoms. Our results suggest the following: (1) the abnormality in the right superior temporal gyrus is present in the early stages of schizophrenia, possibly representing the core region related to schizophrenia; and (2) atypical antipsychotics could modulate brain morphology involving the thalamus, cortical grey matter and cerebellum. In addition, examination of the prefrontal cortex and thalamus might facilitate an efficient response to atypical antipsychotics in terms of symptom improvement.
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Landek-Salgado MA, Faust TE, Sawa A. Molecular substrates of schizophrenia: homeostatic signaling to connectivity. Mol Psychiatry 2016; 21:10-28. [PMID: 26390828 PMCID: PMC4684728 DOI: 10.1038/mp.2015.141] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2014] [Revised: 06/24/2015] [Accepted: 06/25/2015] [Indexed: 02/06/2023]
Abstract
Schizophrenia (SZ) is a devastating psychiatric condition affecting numerous brain systems. Recent studies have identified genetic factors that confer an increased risk of SZ and participate in the disease etiopathogenesis. In parallel to such bottom-up approaches, other studies have extensively reported biological changes in patients by brain imaging, neurochemical and pharmacological approaches. This review highlights the molecular substrates identified through studies with SZ patients, namely those using top-down approaches, while also referring to the fruitful outcomes of recent genetic studies. We have subclassified the molecular substrates by system, focusing on elements of neurotransmission, targets in white matter-associated connectivity, immune/inflammatory and oxidative stress-related substrates, and molecules in endocrine and metabolic cascades. We further touch on cross-talk among these systems and comment on the utility of animal models in charting the developmental progression and interaction of these substrates. Based on this comprehensive information, we propose a framework for SZ research based on the hypothesis of an imbalance in homeostatic signaling from immune/inflammatory, oxidative stress, endocrine and metabolic cascades that, at least in part, underlies deficits in neural connectivity relevant to SZ. Thus, this review aims to provide information that is translationally useful and complementary to pathogenic hypotheses that have emerged from genetic studies. Based on such advances in SZ research, it is highly expected that we will discover biomarkers that may help in the early intervention, diagnosis or treatment of SZ.
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Affiliation(s)
- M A Landek-Salgado
- Department of Psychiatry, John Hopkins University School of Medicine, Baltimore, MD, USA
| | - T E Faust
- Department of Psychiatry, John Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Neuroscience, John Hopkins University School of Medicine, Baltimore, MD, USA
| | - A Sawa
- Department of Psychiatry, John Hopkins University School of Medicine, Baltimore, MD, USA
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In the grey zone between epilepsy and schizophrenia: alterations in group II metabotropic glutamate receptors. Acta Neurol Belg 2015; 115:221-32. [PMID: 25539775 DOI: 10.1007/s13760-014-0407-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2014] [Accepted: 12/05/2014] [Indexed: 01/09/2023]
Abstract
Glutamate is the major excitatory neurotransmitter in the brain. The glutamate system plays an important role in the formation of synapses during brain development and synaptic plasticity. Dysfunctions in glutamate regulation may lead to hyperexcitatory neuronal networks and neurotoxicity. Glutamate excess is possibly of great importance in the pathophysiology of several neurological and psychiatric disorders such as epilepsy and schizophrenia. Interestingly, cross talk between these disorders has been well documented: psychiatric comorbidities are frequent in epilepsy and temporal lobe epilepsy is one of the highest risk factors for developing psychosis. Therefore, dysfunctions in glutamatergic neurotransmission might constitute a common pathological mechanism. A major negative feedback system is regulated by the presynaptic group II metabotropic glutamate (mGlu) receptors including mGlu2/3 receptors. These receptors are predominantly localised extrasynaptically in basal ganglia and limbic structures. Hence, mGlu2/3 receptors are an interesting target for the treatment of disorders like epilepsy and schizophrenia. A dysfunction in the glutamate system may be associated with alterations in mGlu2/3 receptor expression. In this review, we describe the localization of mGlu2/3 receptors in the healthy brain of mice, rats and humans. Secondly, changes in mGlu2/3 receptor density of the brain regions affected in epilepsy and schizophrenia are summarised. Increased mGlu2/3 receptor density might represent a compensatory mechanism of the brain to regulate elevated glutamate levels, while reduced mGlu2/3 receptor density in some brain regions may further contribute to the aberrant hyperexcitability. Further research considering the mGlu2/3 receptor can contribute significantly to the understanding of the etiological and therapeutic role of group II mGlu receptor in epilepsy, epilepsy with psychosis and schizophrenia.
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Juuhl-Langseth M, Hartberg CB, Holmén A, Thormodsen R, Groote IR, Rimol LM, Emblem KE, Agartz I, Rund BR. Impaired Verbal Learning Is Associated with Larger Caudate Volumes in Early Onset Schizophrenia Spectrum Disorders. PLoS One 2015; 10:e0130435. [PMID: 26230626 PMCID: PMC4521864 DOI: 10.1371/journal.pone.0130435] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2014] [Accepted: 05/20/2015] [Indexed: 01/31/2023] Open
Abstract
Background Both brain structural abnormalities and neurocognitive impairments are core features of schizophrenia. We have previously reported enlargements in subcortical brain structure volumes and impairment of neurocognitive functioning as measured by the MATRICS Cognitive Consensus Battery (MCCB) in early onset schizophrenia spectrum disorders (EOS). To our knowledge, no previous study has investigated whether neurocognitive performance and volumetric abnormalities in subcortical brain structures are related in EOS. Methods Twenty-four patients with EOS and 33 healthy controls (HC) were included in the study. Relationships between the caudate nucleus, the lateral and fourth ventricles volumes and neurocognitive performance were investigated with multivariate linear regression analyses. Intracranial volume, age, antipsychotic medication and IQ were included as independent predictor-variables. Results The caudate volume was negatively correlated with verbal learning performance uniquely in the EOS group (r=-.454, p=.034). There were comparable positive correlations between the lateral ventricular volume and the processing speed, attention and reasoning and problem solving domains for both the EOS patients and the healthy controls. Antipsychotic medication was related to ventricular enlargements, but did not affect the brain structure-function relationship. Conclusion Enlargement of the caudate volume was related to poorer verbal learning performance in patients with EOS. Despite a 32% enlargement of the lateral ventricles in the EOS group, associations to processing speed, attention and reasoning and problem solving were similar for both the EOS and the HC groups.
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Affiliation(s)
- Monica Juuhl-Langseth
- Research Unit Child and Adolescent Mental Health, Oslo University Hospital, Oslo Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- * E-mail:
| | - Cecilie B. Hartberg
- NORMENT and K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Aina Holmén
- Department of Psychology, University of Oslo, Oslo, Norway
- Mental Health Services, Akershus University Hospital, Lørenskog, Norway
| | | | - Inge R. Groote
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Lars M. Rimol
- Department of Laboratory Medicine, Children's and Women's Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kyrre E. Emblem
- The Intervention Centre, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- NORMENT and K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Bjørn R. Rund
- Department of Psychology, University of Oslo, Oslo, Norway
- Vestre Viken Hospital Trust, Drammen, Norway
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Modenato C, Draganski B. The concept of schizotypy - A computational anatomy perspective. SCHIZOPHRENIA RESEARCH-COGNITION 2015; 2:89-92. [PMID: 29114458 PMCID: PMC5609650 DOI: 10.1016/j.scog.2015.05.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Revised: 05/09/2015] [Accepted: 05/11/2015] [Indexed: 11/26/2022]
Abstract
Despite major progress in diagnostic accuracy and symptomatic treatment of mental disorders, there is an ongoing debate about their classification aiming to follow current advances in neurobiology. The main goal of this review is to provide a comprehensive summary of the put forward schizotypy concept that follows the needs for objective assessment of schizophrenia-like personality traits in the general population. We focus on major achievements in the field from the perspective of magnetic resonance imaging-based computational anatomy of the brain. Particular interest is devoted to overlapping brain structure findings in schizotypy and schizophrenia to promote a dimensional view on schizophrenia as extension of phenotype traits in the non-clinical general population.
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Affiliation(s)
- C Modenato
- LREN, University of Lausanne, Dept. of clinical neurosciences, CHUV, Lausanne Switzerland
| | - B Draganski
- LREN, University of Lausanne, Dept. of clinical neurosciences, CHUV, Lausanne Switzerland.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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40
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John JP, Lukose A, Bagepally BS, Halahalli HN, Moily NS, Vijayakumari AA, Jain S. A systematic examination of brain volumetric abnormalities in recent-onset schizophrenia using voxel-based, surface-based and region-of-interest-based morphometric analyses. J Negat Results Biomed 2015; 14:11. [PMID: 26065881 PMCID: PMC4464994 DOI: 10.1186/s12952-015-0030-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 06/01/2015] [Indexed: 12/11/2022] Open
Abstract
Background Brain morphometric abnormalities in schizophrenia have been extensively reported in the literature. Whole-brain volumetric reductions are almost universally reported by most studies irrespective of the characteristics of the samples studied (e.g., chronic/recent-onset; medicated/neuroleptic-naïve etc.). However, the same cannot be said of the reported regional morphometric abnormalities in schizophrenia. While certain regional morphometric abnormalities are more frequently reported than others, there are no such abnormalities that are universally reported across studies. Variability of socio-demographic and clinical characteristics across study samples as well as technical and methodological issues related to acquisition and analyses of brain structural images may contribute to inconsistency of brain morphometric findings in schizophrenia. The objective of the present study therefore was to systematically examine brain morphometry in patients with recent-onset schizophrenia to find out if there are significant whole-brain or regional volumetric differences detectable at the appropriate significance threshold, after attempting to control for various confounding factors that could impact brain volumes. Methods Structural magnetic resonance images of 90 subjects (schizophrenia = 45; healthy subjects = 45) were acquired using a 3 Tesla magnet. Morphometric analyses were carried out following standard analyses pipelines of three most commonly used strategies, viz., whole-brain voxel-based morphometry, whole-brain surface-based morphometry, and between-group comparisons of regional volumes generated by automated segmentation and parcellation. Results In our sample of patients having recent-onset schizophrenia with limited neuroleptic exposure, there were no significant whole brain or regional brain morphometric abnormalities noted at the appropriate statistical significance thresholds with or without including age, gender and intracranial volume or total brain volume in the statistical analyses. Conclusions In the background of the conflicting findings in the literature, our findings indicate that brain morphometric abnormalities may not be directly related to the schizophrenia phenotype. Analysis of the reasons for the inconsistent results across studies as well as consideration of alternate sources of variability of brain morphology in schizophrenia such as epistatic and epigenetic mechanisms could perhaps advance our understanding of structural brain alterations in schizophrenia. Electronic supplementary material The online version of this article (doi:10.1186/s12952-015-0030-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- John P John
- Additional Professor of Psychiatry & Adjunct Faculty of Clinical Neurosciences, Multimodal Brain Image Analysis Laboratory (MBIAL), National Institute of Mental Health and Neurosciences (NIMHANS), P.B. No. 2900, Dharmaram P.O., Hosur Road, Bangalore, 560 029, Karnataka, India. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India. .,Department of Clinical Neurosciences, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India.
| | - Ammu Lukose
- Additional Professor of Psychiatry & Adjunct Faculty of Clinical Neurosciences, Multimodal Brain Image Analysis Laboratory (MBIAL), National Institute of Mental Health and Neurosciences (NIMHANS), P.B. No. 2900, Dharmaram P.O., Hosur Road, Bangalore, 560 029, Karnataka, India. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India.
| | - Bhavani Shankara Bagepally
- Additional Professor of Psychiatry & Adjunct Faculty of Clinical Neurosciences, Multimodal Brain Image Analysis Laboratory (MBIAL), National Institute of Mental Health and Neurosciences (NIMHANS), P.B. No. 2900, Dharmaram P.O., Hosur Road, Bangalore, 560 029, Karnataka, India. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India. .,Department of Clinical Neurosciences, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India.
| | - Harsha N Halahalli
- Additional Professor of Psychiatry & Adjunct Faculty of Clinical Neurosciences, Multimodal Brain Image Analysis Laboratory (MBIAL), National Institute of Mental Health and Neurosciences (NIMHANS), P.B. No. 2900, Dharmaram P.O., Hosur Road, Bangalore, 560 029, Karnataka, India. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India. .,Department of Neurophysiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India.
| | - Nagaraj S Moily
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India. .,Molecular Genetics Laboratory, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India.
| | - Anupa A Vijayakumari
- Additional Professor of Psychiatry & Adjunct Faculty of Clinical Neurosciences, Multimodal Brain Image Analysis Laboratory (MBIAL), National Institute of Mental Health and Neurosciences (NIMHANS), P.B. No. 2900, Dharmaram P.O., Hosur Road, Bangalore, 560 029, Karnataka, India. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India.
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India. .,Molecular Genetics Laboratory, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India.
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Brucato N, Guadalupe T, Franke B, Fisher SE, Francks C. A schizophrenia-associated HLA locus affects thalamus volume and asymmetry. Brain Behav Immun 2015; 46:311-8. [PMID: 25728236 DOI: 10.1016/j.bbi.2015.02.021] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Revised: 01/20/2015] [Accepted: 02/07/2015] [Indexed: 02/02/2023] Open
Abstract
Genes of the Major Histocompatibility Complex (MHC) have recently been shown to have neuronal functions in the thalamus and hippocampus. Common genetic variants in the Human Leukocyte Antigens (HLA) region, human homologue of the MHC locus, are associated with small effects on susceptibility to schizophrenia, while volumetric changes of the thalamus and hippocampus have also been linked to schizophrenia. We therefore investigated whether common variants of the HLA would affect volumetric variation of the thalamus and hippocampus. We analysed thalamus and hippocampus volumes, as measured using structural magnetic resonance imaging, in 1.265 healthy participants. These participants had also been genotyped using genome-wide single nucleotide polymorphism (SNP) arrays. We imputed genotypes for single nucleotide polymorphisms at high density across the HLA locus, as well as HLA allotypes and HLA amino acids, by use of a reference population dataset that was specifically targeted to the HLA region. We detected a significant association of the SNP rs17194174 with thalamus volume (nominal P=0.0000017, corrected P=0.0039), as well as additional SNPs within the same region of linkage disequilibrium. This effect was largely lateralized to the left thalamus and is localized within a genomic region previously associated with schizophrenia. The associated SNPs are also clustered within a potential regulatory element, and a region of linkage disequilibrium that spans genes expressed in the thalamus, including HLA-A. Our data indicate that genetic variation within the HLA region influences the volume and asymmetry of the human thalamus. The molecular mechanisms underlying this association may relate to HLA influences on susceptibility to schizophrenia.
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Affiliation(s)
- Nicolas Brucato
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands; Leiden University Centre for Linguistics, Leiden, The Netherlands.
| | - Tulio Guadalupe
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands; International Max Planck Research School for Language Sciences, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Barbara Franke
- Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands; Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands; Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Simon E Fisher
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, The Netherlands
| | - Clyde Francks
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, The Netherlands
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Lopes R, Soares R, Coelho R, Figueiredo-Braga M. Angiogenesis in the pathophysiology of schizophrenia — A comprehensive review and a conceptual hypothesis. Life Sci 2015; 128:79-93. [DOI: 10.1016/j.lfs.2015.02.010] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Revised: 01/27/2015] [Accepted: 02/12/2015] [Indexed: 01/11/2023]
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Vijayakumari AA, John JP, Halahalli HN, Paul P, Thirunavukkarasu P, Purushottam M, Jain S. Effect of polymorphisms of three genes mediating monoamine signalling on brain morphometry in schizophrenia and healthy subjects. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2015; 13:68-82. [PMID: 25912540 PMCID: PMC4423152 DOI: 10.9758/cpn.2015.13.1.68] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 08/18/2014] [Accepted: 10/19/2014] [Indexed: 01/11/2023]
Abstract
OBJECTIVE We examined the effect of risk alleles of polymorphisms of three schizophrenia risk genes that mediate monoamine signalling in the brain on regional brain volumes of schizophrenia and healthy control subjects. The risk alleles and the gene polymorphisms studied were: Val allele of catechol o-methyltransferase (COMT) rs4680 polymorphism; short allele of 5-hydroxy tryptamine transporter linked polymorphic region (5HTTLPR) polymorphism; and T allele of 5-hydroxy tryptamine 2A (5HT2A) rs6314 polymorphism. METHODS The study was carried out on patients with recent onset schizophrenia (n=41) recruited from the outpatient department of National Institute of Mental Health and Neurosciences, Bangalore, India and healthy control subjects (n=39), belonging to South Indian Dravidian ethnicity. Individual and additive effects of risk alleles of the above gene polymorphisms on brain morphometry were explored using voxel-based morphometry. RESULTS Irrespective of phenotypes, individuals with the risk allele T of the rs6314 polymorphism of 5HT2A gene showed greater (at cluster-extent equivalent to family wise error-correction [FWEc] p<0.05) regional brain volumes in the left inferior temporal and left inferior occipital gyri. Those with the risk alleles of the other two polymorphisms showed a trend (at p<0.001, uncorrected) towards lower regional brain volumes. A trend (at p<0.001, uncorrected) towards additive effects of the above 3 risk alleles (subjects with 2 or 3 risk alleles vs. those with 1 or no risk alleles) on brain morphology was also noted. CONCLUSIONS The findings of the present study have implications in understanding the role of individual and additive effects of genetic variants in mediating regional brain morphometry in health and disease.
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Affiliation(s)
- Anupa A Vijayakumari
- Multimodal Brain Image Analysis Laboratory (MBIAL), India.,Departments of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - John P John
- Multimodal Brain Image Analysis Laboratory (MBIAL), India.,Departments of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India.,Departments of Clinical Neuroscience, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Harsha N Halahalli
- Departments of Neurophysiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Pradip Paul
- Departments of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Priyadarshini Thirunavukkarasu
- Multimodal Brain Image Analysis Laboratory (MBIAL), India.,Departments of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Meera Purushottam
- Departments of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Sanjeev Jain
- Departments of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
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Stoos C, Nelsen L, Schissler KA, Elliott AJ, Kinney HC. Fetal alcohol syndrome and secondary schizophrenia: a unique neuropathologic study. J Child Neurol 2015; 30:601-5. [PMID: 24563476 PMCID: PMC8312346 DOI: 10.1177/0883073814520976] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We report the unique neuropathologic study of an adult brain of a patient with fetal alcohol syndrome who developed the well-recognized complication of schizophrenia in adolescence. The major finding was asymmetric formation of the lateral temporal lobes, with marked enlargement of the right superior temporal gyrus, suggesting that alcohol is preferentially toxic to temporal lobe patterning during gestation. Critical maturational changes unique to adolescence can unmask psychotic symptomatology mediated by temporal lobe pathology that has been clinically dormant since birth. Elucidating the neuropathologic basis of the secondary psychiatric disorders in fetal alcohol syndrome can help provide insight into their putative developmental origins.
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Affiliation(s)
- Catherine Stoos
- Department of Pathology, Sanford Health, Sioux Falls, SD, USA
| | - Laura Nelsen
- Department of Pathology, MaineGeneral Health, Augusta, MA, USA
| | - Kathryn A Schissler
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, MA, USA
| | - Amy J Elliott
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, MA, USA
| | - Hannah C Kinney
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, MA, USA
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45
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Zhou Y, Fan L, Qiu C, Jiang T. Prefrontal cortex and the dysconnectivity hypothesis of schizophrenia. Neurosci Bull 2015; 31:207-19. [PMID: 25761914 DOI: 10.1007/s12264-014-1502-8] [Citation(s) in RCA: 126] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2014] [Accepted: 11/20/2014] [Indexed: 12/15/2022] Open
Abstract
Schizophrenia is hypothesized to arise from disrupted brain connectivity. This "dysconnectivity hypothesis" has generated interest in discovering whether there is anatomical and functional dysconnectivity between the prefrontal cortex (PFC) and other brain regions, and how this dysconnectivity is linked to the impaired cognitive functions and aberrant behaviors of schizophrenia. Critical advances in neuroimaging technologies, including diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), make it possible to explore these issues. DTI affords the possibility to explore anatomical connectivity in the human brain in vivo and fMRI can be used to make inferences about functional connections between brain regions. In this review, we present major advances in the understanding of PFC anatomical and functional dysconnectivity and their implications in schizophrenia. We then briefly discuss future prospects that need to be explored in order to move beyond simple mapping of connectivity changes to elucidate the neuronal mechanisms underlying schizophrenia.
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Affiliation(s)
- Yuan Zhou
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
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46
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Dannlowski U, Grabe HJ, Wittfeld K, Klaus J, Konrad C, Grotegerd D, Redlich R, Suslow T, Opel N, Ohrmann P, Bauer J, Zwanzger P, Laeger I, Hohoff C, Arolt V, Heindel W, Deppe M, Domschke K, Hegenscheid K, Völzke H, Stacey D, Meyer Zu Schwabedissen H, Kugel H, Baune BT. Multimodal imaging of a tescalcin (TESC)-regulating polymorphism (rs7294919)-specific effects on hippocampal gray matter structure. Mol Psychiatry 2015; 20:398-404. [PMID: 24776739 DOI: 10.1038/mp.2014.39] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2013] [Revised: 02/09/2014] [Accepted: 03/17/2014] [Indexed: 02/07/2023]
Abstract
In two large genome-wide association studies, an intergenic single-nucleotide polymorphism (SNP; rs7294919) involved in TESC gene regulation has been associated with hippocampus volume. Further characterization of neurobiological effects of the TESC gene is warranted using multimodal brain-wide structural and functional imaging. Voxel-based morphometry (VBM8) was used in two large, well-characterized samples of healthy individuals of West-European ancestry (Münster sample, N=503; SHIP-TREND, N=721) to analyze associations between rs7294919 and local gray matter volume. In subsamples, white matter fiber structure was investigated using diffusion tensor imaging (DTI) and limbic responsiveness was measured by means of functional magnetic resonance imaging (fMRI) during facial emotion processing (N=220 and N=264, respectively). Furthermore, gene x environment (G × E) interaction and gene x gene interaction with SNPs from genes previously found to be associated with hippocampal size (FKBP5, Reelin, IL-6, TNF-α, BDNF and 5-HTTLPR/rs25531) were explored. We demonstrated highly significant effects of rs7294919 on hippocampal gray matter volumes in both samples. In whole-brain analyses, no other brain areas except the hippocampal formation and adjacent temporal structures were associated with rs7294919. There were no genotype effects on DTI and fMRI results, including functional connectivity measures. No G × E interaction with childhood maltreatment was found in both samples. However, an interaction between rs7294919 and rs2299403 in the Reelin gene was found that withstood correction for multiple comparisons. We conclude that rs7294919 exerts highly robust and regionally specific effects on hippocampal gray matter structures, but not on other neuropsychiatrically relevant imaging markers. The biological interaction between TESC and RELN pointing to a neurodevelopmental origin of the observed findings warrants further mechanistic investigations.
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Affiliation(s)
- U Dannlowski
- 1] Department of Psychiatry, University of Münster, Münster, Germany [2] Department of Psychiatry, University of Marburg, Marburg, Germany
| | - H J Grabe
- 1] Department of Psychiatry, University Medicine Greifswald, HELIOS-Hospital Stralsund, Stralsund, Germany [2] German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - K Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - J Klaus
- Department of Psychiatry, University of Münster, Münster, Germany
| | - C Konrad
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - D Grotegerd
- Department of Psychiatry, University of Münster, Münster, Germany
| | - R Redlich
- Department of Psychiatry, University of Münster, Münster, Germany
| | - T Suslow
- 1] Department of Psychiatry, University of Münster, Münster, Germany [2] Department of Psychosomatic Medicine and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - N Opel
- Department of Psychiatry, University of Münster, Münster, Germany
| | - P Ohrmann
- Department of Psychiatry, University of Münster, Münster, Germany
| | - J Bauer
- Department of Psychiatry, University of Münster, Münster, Germany
| | - P Zwanzger
- Department of Psychiatry, University of Münster, Münster, Germany
| | - I Laeger
- Department of Psychiatry, University of Münster, Münster, Germany
| | - C Hohoff
- Department of Psychiatry, University of Münster, Münster, Germany
| | - V Arolt
- Department of Psychiatry, University of Münster, Münster, Germany
| | - W Heindel
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - M Deppe
- Department of Neurology, University of Münster, Münster, Germany
| | - K Domschke
- Department of Psychiatry, University of Würzburg, Würzburg, Germany
| | - K Hegenscheid
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - H Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - D Stacey
- Discipline of Psychiatry, School of Medicine, University of Adelaide: North Terrace, Adelaide, SA, Australia
| | | | - H Kugel
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - B T Baune
- Discipline of Psychiatry, School of Medicine, University of Adelaide: North Terrace, Adelaide, SA, Australia
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Comparing free water imaging and magnetization transfer measurements in schizophrenia. Schizophr Res 2015; 161:126-32. [PMID: 25454797 PMCID: PMC4277708 DOI: 10.1016/j.schres.2014.09.046] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2014] [Revised: 09/27/2014] [Accepted: 09/30/2014] [Indexed: 01/09/2023]
Abstract
Diffusion weighted imaging (DWI) has been extensively used to study the microarchitecture of white matter in schizophrenia. However, popular DWI-derived measures such as fractional anisotropy (FA) may be sensitive to many types of pathologies, and thus the interpretation of reported differences in these measures remains difficult. Combining DWI with magnetization transfer ratio (MTR) - a putative measure of white matter myelination - can help us reveal the underlying mechanisms. Previous findings hypothesized that MTR differences in schizophrenia are associated with free water concentrations, which also affect the DWIs. In this study we use a recently proposed DWI-derived method called free-water imaging to assess this hypothesis. We have reanalyzed data from a previous study by using a fiber-based analysis of free-water imaging, providing a free-water fraction, as well as mean diffusivity and FA corrected for free-water, in addition to MTR along twelve major white matter fiber bundles in 40 schizophrenia patients and 40 healthy controls. We tested for group differences in each fiber bundle and for each measure separately and computed correlations between the MTR and the DWI-derived measures separately for both groups. Significant higher average MTR values in patients were found for the right uncinate fasciculus, the right arcuate fasciculus and the right inferior-frontal occipital fasciculus. No significant results were found for the other measures. No significant differences in correlations were found between MTR and the DWI-derived measures. The results suggest that MTR and free-water imaging measures can be considered complementary, promoting the acquisition of MTR in addition to DWI to identify group differences, as well as to better understand the underlying mechanisms in schizophrenia.
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Voineskos AN. Genetic underpinnings of white matter 'connectivity': heritability, risk, and heterogeneity in schizophrenia. Schizophr Res 2015; 161:50-60. [PMID: 24893906 DOI: 10.1016/j.schres.2014.03.034] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2014] [Revised: 03/11/2014] [Accepted: 03/12/2014] [Indexed: 12/14/2022]
Abstract
Schizophrenia is a highly heritable disorder. Thus, the combination of genetics and brain imaging may be a useful strategy to investigate the effects of risk genes on anatomical connectivity, and for gene discovery, i.e. discovering the genetic correlates of white matter phenotypes. Following a database search, I review evidence for heritability of white matter phenotypes. I also review candidate gene investigations, examining association of putative risk variants with white matter phenotypes, as well as the recent flurry of research exploring relationships of genome-wide significant risk loci with white matter phenotypes. Finally, I review multivariate and polygene approaches, which constitute a new wave of imaging-genetics research, including large collaborative initiatives aiming to discover new genes that may predict aspects of white matter microstructure. The literature supports the heritability of white matter phenotypes. Loci in genes intimately implicated in oligodendrocyte and myelin development, growth and maintenance, and neurotrophic systems are associated with white matter microstructure. GWAS variants have not yet sufficiently been explored using DTI-based evaluation of white matter to draw conclusions, although micro-RNA 137 is promising due to its potential regulation of other GWAS schizophrenia genes. Many imaging-genetic studies only include healthy participants, which, while helping control for certain confounds, cannot address questions related to disease heterogeneity or symptom expression, and thus more studies should include participants with schizophrenia. With sufficiently large sample sizes, the future of this field lies in polygene strategies aimed at risk prediction and heterogeneity dissection of schizophrenia that can translate to personalized interventions.
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Affiliation(s)
- Aristotle N Voineskos
- Kimel Family Translational Imaging-Genetics Laboratory, Research Imaging Centre, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada.
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49
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Fitzsimmons J, Schneiderman JS, Whitford TJ, Swisher T, Niznikiewicz MA, Pelavin PE, Terry DP, Mesholam-Gately RI, Seidman LJ, Goldstein JM, Kubicki M. Cingulum bundle diffusivity and delusions of reference in first episode and chronic schizophrenia. Psychiatry Res 2014; 224:124-32. [PMID: 25174840 PMCID: PMC4195812 DOI: 10.1016/j.pscychresns.2014.08.002] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Revised: 06/18/2014] [Accepted: 08/02/2014] [Indexed: 01/12/2023]
Abstract
The goal of this study was to assess integrity of the cingulum bundle in patients diagnosed with first episode schizophrenia, chronic schizophrenia, and matched controls as well as to determine the relationship between diffusion measures of cingulum bundle integrity and severity of patients' delusions of reference. Participants, who comprised 18 first episode patients, 20 chronic patients, and two groups of matched controls (20 subjects in each), underwent 3 T MRI diffusion tensor imaging. Patients diagnosed with schizophrenia (chronic+first episode) showed decreased fractional anisotropy in the right cingulum bundle compared with controls. First episode patients exhibited higher trace bilaterally, compared with matched controls, and on the left compared with chronic patients. Axial diffusivity was increased in first episode patients, bilaterally, compared with matched controls and chronic patients. Radial diffusivity was also higher, bilaterally, in first episode patients compared with matched controls, and on the right compared with chronic patients. Trace diffusity and radial diffusivity in first episode patients were significantly correlated with increased severity of delusions of reference. Given that the abnormalities were present only in first episode patients and were not observed in chronic cases, it appears that they normalize over time. These abnormalities in first episode patients involved diffusivity measures in all directions (trace, radial and axial), suggesting a likely acute, partially reversible process in which there is an increase in brain water content, i.e., swelling, edema, or inflammation, that may reflect an early neuroinflammatory response in first episode patients.
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Affiliation(s)
- Jennifer Fitzsimmons
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women׳s Hospital, Harvard Medical School, Boston, MA, USA.
| | - Jason S. Schneiderman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA,Wyle, Houston, TX; USA
| | - Thomas J. Whitford
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA,School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Tali Swisher
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA
| | - Margaret A. Niznikiewicz
- Cognitive Neuroscience Laboratory, Veterans Affairs Boston Healthcare System, Brockton Division, Brockton, MA; USA
| | - Paula E. Pelavin
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA
| | - Douglas P. Terry
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA
| | - Raquelle I. Mesholam-Gately
- Beth Israel Deaconess Medical Center-Massachusetts Mental Health Center, Public Psychiatry Division, Harvard Medical School, Boston, MA; USA
| | - Larry J. Seidman
- Beth Israel Deaconess Medical Center-Massachusetts Mental Health Center, Public Psychiatry Division, Harvard Medical School, Boston, MA; USA
| | - Jill M. Goldstein
- Beth Israel Deaconess Medical Center-Massachusetts Mental Health Center, Public Psychiatry Division, Harvard Medical School, Boston, MA; USA,Division of Women's Health, Connors Center for Women's Health & Gender Biology, Departments of Psychiatry and Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA,Surgical Planning Laboratory, MRI Division, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; USA
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50
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Copy number deletion burden is associated with cognitive, structural, and resting-state network differences in patients with schizophrenia. Behav Brain Res 2014; 272:324-34. [DOI: 10.1016/j.bbr.2014.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2014] [Revised: 06/29/2014] [Accepted: 07/01/2014] [Indexed: 01/20/2023]
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