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Del Campo CMZM, Nicolson GL, Sfera A. Neurolipidomics in schizophrenia: A not so well-oiled machine. Neuropharmacology 2024; 260:110117. [PMID: 39153730 DOI: 10.1016/j.neuropharm.2024.110117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 08/03/2024] [Accepted: 08/14/2024] [Indexed: 08/19/2024]
Abstract
Most patients with schizophrenia (SCZ) do not exhibit violent behaviors and are more likely to be victims rather than perpetrators of violent acts. However, a subgroup of forensic detainees with SCZ exhibit tendencies to engage in criminal violations. Although numerous models have been proposed, ranging from substance use, serotonin transporter gene, and cognitive dysfunction, the molecular underpinnings of violence in SCZ patients remains elusive. Lithium and clozapine have established anti-aggression properties and recent studies have linked low cholesterol levels and ultraviolet (UV) radiation with human aggression, while vitamin D3 reduces violent behaviors. A recent study found that vitamin D3, omega-3 fatty acids, magnesium, and zinc lower aggression in forensic population. In this review article, we take a closer look at aryl hydrocarbon receptor (AhR) and the dysfunctional lipidome in neuronal membranes, with emphasis on cholesterol and vitamin D3 depletion, as sources of aggressive behavior. We also discuss modalities to increase the fluidity of neuronal double layer via membrane lipid replacement (MLR) and natural or synthetic compounds. This article is part of the Special Issue on "Personality Disorders".
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Affiliation(s)
| | - Garth L Nicolson
- Department of Molecular Pathology, The Institute for Molecular Medicine, Huntington Beach, CA, 92647, USA
| | - Adonis Sfera
- Patton State Hospital, Loma Linda University, Department of Psychiatry, University of California, Riverside, USA.
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2
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Ozdikici M. Morphometric Study of the Intracranial Fluid Spaces in Schizophrenia. Neurol India 2024; 72:817-823. [PMID: 39216040 DOI: 10.4103/neurol-india.ni_552_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 01/18/2023] [Indexed: 09/04/2024]
Abstract
BACKGROUND The intracranial fluid spaces (IFS), also known as "the extra-axial spaces," consist of the superficial cerebral sulci, the Sylvian fissures, the basal cisterns, the third ventricle, the fourth ventricle, and the two lateral ventricles. In diseases such as schizophrenia, Alzheimer's, Parkinson's, and especially hydrocephalus, IFS' enlargements are observed. OBJECTIVE Our study aimed to determine the mean values of IFS measurements in patients with schizophrenia and compare them with healthy controls. MATERIAL AND METHODS This work has been carried out on 188 cases, out of which 88 schizophrenia patients (56 men and 32 women) met the diagnostic criteria according to DSM-5 for schizophrenia and 100 healthy controls (50 men and 50 women). The 10 parameters have been used to evaluate IFS on magnetic resonance imaging (MRI) scans. RESULTS The parameters showing statistically significant differences were higher in favor of the individual with schizophrenia. Except for the bifrontal index and Evan's index, most parameters (the bicaudate index, the fourth ventricle width, the fourth ventricle index, the maximum width of the anterior interhemispheric fissure, the maximum width of the right frontal subarachnoid space, the maximum width of the left frontal subarachnoid space, the maximum width of the right Sylvian fissure, and the maximum width of the left Sylvian fissure) were obtained statistically highly significant differences between the examined and control groups. CONCLUSIONS In schizophrenia, it is more practical to evaluate brain atrophy using some parameters, especially the width of the Sylvian fissure and the bicaudate index.
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Affiliation(s)
- Mete Ozdikici
- Department of Radiology, Istanbul Sultan 2. Abdulhamid Han Training and Research Hospital, Istanbul, Turkey
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3
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Papazova I, Wunderlich S, Papazov B, Vogelmann U, Keeser D, Karali T, Falkai P, Rospleszcz S, Maurus I, Schmitt A, Hasan A, Malchow B, Stöcklein S. Characterizing cognitive subtypes in schizophrenia using cortical curvature. J Psychiatr Res 2024; 173:131-138. [PMID: 38531143 DOI: 10.1016/j.jpsychires.2024.03.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 03/11/2024] [Accepted: 03/19/2024] [Indexed: 03/28/2024]
Abstract
Cognitive deficits are a core symptom of schizophrenia, but research on their neural underpinnings has been challenged by the heterogeneity in deficits' severity among patients. Here, we address this issue by combining logistic regression and random forest to classify two neuropsychological profiles of patients with high (HighCog) and low (LowCog) cognitive performance in two independent samples. We based our analysis on the cortical features grey matter volume (VOL), cortical thickness (CT), and mean curvature (MC) of N = 57 patients (discovery sample) and validated the classification in an independent sample (N = 52). We investigated which cortical feature would yield the best classification results and expected that the 10 most important features would include frontal and temporal brain regions. The model based on MC had the best performance with area under the curve (AUC) values of 76% and 73%, and identified fronto-temporal and occipital brain regions as the most important features for the classification. Moreover, subsequent comparison analyses could reveal significant differences in MC of single brain regions between the two cognitive profiles. The present study suggests MC as a promising neuroanatomical parameter for characterizing schizophrenia cognitive subtypes.
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Affiliation(s)
- Irina Papazova
- Psychiatry and Psychotherapy, Faculty of Medicine, University of Augsburg, Geschwister-Schönert-Straße 1, 86156, Augsburg, Germany; Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany; DZPG (German Center for Mental Health), partner site München, Augsburg, Germany.
| | - Stephan Wunderlich
- Department of Radiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany; Department of Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Boris Papazov
- Department of Radiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Ulrike Vogelmann
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany; Department of Radiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Temmuz Karali
- Department of Radiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany; Max Planck Institute of Psychiatry, Munich, Germany
| | - Susanne Rospleszcz
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Munich, Germany; Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Isabel Maurus
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Andrea Schmitt
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany; Laboratory of Neuroscience (LIM27), Institute of Psychiatry, University of São Paulo (USP), São Paulo, Brazil
| | - Alkomiet Hasan
- Psychiatry and Psychotherapy, Faculty of Medicine, University of Augsburg, Geschwister-Schönert-Straße 1, 86156, Augsburg, Germany; DZPG (German Center for Mental Health), partner site München, Augsburg, Germany
| | - Berend Malchow
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Sophia Stöcklein
- Department of Radiology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany
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4
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Konttajärvi T, Haapea M, Huhtaniska S, Björnholm L, Miettunen J, Isohanni M, Penttilä M, Murray GK, Koponen H, Vernon AC, Jääskeläinen E, Lieslehto J. The contribution of first-episode illness characteristics and cumulative antipsychotic usage to progressive structural brain changes over a long-term follow-up in schizophrenia. Psychiatry Res Neuroimaging 2024; 339:111790. [PMID: 38354478 DOI: 10.1016/j.pscychresns.2024.111790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 11/26/2023] [Accepted: 01/08/2024] [Indexed: 02/16/2024]
Abstract
Exposure to antipsychotics as well as certain first-episode illness characteristics have been associated with greater gray matter (GM) deficits in the early phase of schizophrenia. Whether the first-episode illness characteristics affect the long-term progression of the structural brain changes remain unexplored. We therefore assessed the role of first-episode illness characteristics and life-time antipsychotic use in relation to long-term structural brain GM changes in schizophrenia. Individuals with schizophrenia (SZ, n = 29) and non-psychotic controls (n = 61) from the Northern Finland Birth Cohort 1966 underwent structural MRI at the ages of 34 (baseline) and 43 (follow-up) years. At follow-up, the average duration of illness was 19.8 years. Voxel-based morphometry was used to assess the effects of predictors on longitudinal GM changes in schizophrenia-relevant brain areas. Younger age of onset (AoO), higher cumulative antipsychotic dose and severity of symptoms were associated with greater GM deficits in the SZ group at follow-up. None of the first-episode illness characteristics were associated with longitudinal GM changes during 9-year follow-up period. We conclude that a younger AoO and high life-time antipsychotic use may contribute to progression of structural brain changes in schizophrenia. Apart from AoO, other first-episode illness characteristics may not contribute to longitudinal GM changes in midlife.
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Affiliation(s)
| | - Marianne Haapea
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Psychiatry, Oulu University of Hospital, Finland; Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Sanna Huhtaniska
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Lassi Björnholm
- Department of Psychiatry, Oulu University of Hospital, Finland; Research Unit of Clinical Neuroscience, University of Oulu, Finland
| | - Jouko Miettunen
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland
| | - Matti Isohanni
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Matti Penttilä
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Graham K Murray
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Hannu Koponen
- University of Helsinki, Helsinki University Hospital, Psychiatry, Helsinki, Finland
| | - Anthony C Vernon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London,United Kingdom
| | - Erika Jääskeläinen
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Psychiatry, Oulu University of Hospital, Finland
| | - Johannes Lieslehto
- Research Unit of Population Health, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University of Hospital and University of Oulu, Finland; Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland; Department of Clinical Neuroscience, Division of Insurance Medicine, Karolinska Institutet, Stockholm, Sweden
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Davidson M, Carpenter WT. Targeted Treatment of Schizophrenia Symptoms as They Manifest, or Continuous Treatment to Reduce the Risk of Psychosis Recurrence. Schizophr Bull 2024; 50:14-21. [PMID: 37929893 PMCID: PMC10754173 DOI: 10.1093/schbul/sbad145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
Current pharmacological treatment of schizophrenia employs drugs that interfere with dopamine neurotransmission, aiming to suppress acute exacerbation of psychosis and maintenance treatment to reduce the risk of psychosis recurrence. According to this treatment scheme, available psychotropic drugs intended to treat negative symptoms, cognitive impairment, or anxiety are administered as add-ons to treatment with antipsychotics. However, an alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, while negative symptoms, cognitive impairment, or anxiety are treated with specific psychotropics as monotherapy. Along these lines, antipsychotics are renewed only in the event of recurrence of psychotic symptoms. This 50-year-old debate between targeted and continuous treatment schemes arises from disagreements about interpreting scientific evidence and discordant views regarding benefit/risk assessment. Among the debate's questions are: (1) what is the percentage of individuals who can maintain stability without antipsychotic maintenance treatment, and what is the percentage of those who exacerbate despite antipsychotic treatment? (2) how to interpret results of placebo-controlled 9- to 18-month-long maintenance trials in a life-long chronic disorder, and how to interpret results of the targeted trials, some of which are open label or not randomized; (3) how to weigh the decreased risk for psychotic recurrence vs the almost certainty of adverse effects on patient's quality of life. Patients' profiles, preferences, and circumstances of the care provision should be considered as the targeted vs continuous treatment options are considered.
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Affiliation(s)
- Michael Davidson
- Department of Basic and Clinical Sciences, Psychiatry, University of Nicosia Medical School, 2414, Nicosia, Cyprus and Minerva Neurosciences, 1500 District Avenue, Burlington, MA 01803, USA
| | - William T Carpenter
- University of Maryland School of Medicine, Department of Psychiatry, Maryland Psychiatric Research Center, Baltimore, MD, USA
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6
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Walther S, Nadesalingam N, Nuoffer M, Kyrou A, Wüthrich F, Lefebvre S. Structural alterations of the motor cortex and higher order cortical areas suggest early neurodevelopmental origin of catatonia in schizophrenia. Schizophr Res 2024; 263:131-138. [PMID: 36272843 DOI: 10.1016/j.schres.2022.10.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 11/07/2022]
Abstract
The neurobiology of catatonia is still poorly understood. Particularly structural MRI studies yielded conflicting results. Heterogeneity of findings was suggested to stem from specifics of different rating scales. This study sought to test grey matter differences between patients with catatonia, patients without catatonia, and healthy controls using the two main instruments of catatonia rating. We included 98 patients with schizophrenia spectrum disorders and 42 healthy controls. Catatonia was measured using the Bush Francis Catatonia Rating Scale and the Northoff Catatonia Rating Scale. According to these scales, patients were classified into those with and those without catatonia. We tested whole brain grey matter volume, cortical thickness, and local gyrification across groups. Both catatonia rating scales correlated at tau = 0.65 but failed to classify identical subjects as catatonia patients. However, group differences in grey matter parameters were broadly similar with either rating scale to identify catatonia cases. Catatonia patients had reduced grey matter volume compared to controls in a large network including orbitofrontal cortex, cingulate, thalamus, and amygdala. While there was no group difference in cortical thickness, catatonia patients had increased local gyrification in premotor, motor, and parietal cortices compared to controls. Hypergyrification of the motor cortex and higher order cortical areas was found in catatonia patients compared to patients without catatonia. Both catatonia rating scales find similar symptom severity and group differences in grey matter indices. Catatonia is linked to reduced grey matter volume and increased local gyrification, suggesting some impact of early neurodevelopmental insults.
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Affiliation(s)
- Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.
| | - Niluja Nadesalingam
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland; Graduate School for Health Sciences, University of Bern, Switzerland
| | - Melanie Nuoffer
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland; Graduate School for Health Sciences, University of Bern, Switzerland
| | - Alexandra Kyrou
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Florian Wüthrich
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Graduate School for Health Sciences, University of Bern, Switzerland
| | - Stephanie Lefebvre
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
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7
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Gao T, Wang X, Cen H, Li X, Zhai Z, Lu C, Dong Y, Zhang S, Zhuo K, Xiang Q, Wang Y, Liu D. Cross-modal associative memory impairment in schizophrenia. Neuropsychologia 2023; 191:108721. [PMID: 37918479 DOI: 10.1016/j.neuropsychologia.2023.108721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 10/30/2023] [Accepted: 10/30/2023] [Indexed: 11/04/2023]
Abstract
Impaired associative memory function in patients with schizophrenia has received considerable attention. However, previous studies have primarily concentrated on unisensory materials, which limits our understanding of the broader implications of this impairment. In this study, we sought to expand on this knowledge by examining two types of associative memory domains in individuals with schizophrenia, leveraging both visual (Vis) and auditory (Aud) materials. A total of 32 patients with schizophrenia and 29 healthy controls were recruited to participate in the study. Each participant participated in an experiment composed of three paradigms in which different abstract materials (Aud-Aud, Aud-Vis, and Vis-Vis) were presented. Subsequently, the discriminability scores of the two groups were calculated and compared in different modal tasks. Results from the study indicated that individuals with schizophrenia demonstrated varying degrees of associative memory dysfunction in both the same and cross-modalities, with the latter having a significantly lower score than healthy controls (t = 4.120, p < 0.001). Additionally, the cross-modal associative memory function was significantly and negatively correlated with the severity of negative symptoms among individuals diagnosed with schizophrenia (r = -0.362, p = 0.042). This study provides evidence of abnormalities in the processing and memorization of information that integrates multiple sensory modalities in individuals with schizophrenia. This is of great significance for further understanding the cognitive symptoms and pathological mechanisms of schizophrenia, potentially guiding the development of relevant interventions and treatment methods.
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Affiliation(s)
- Tianhao Gao
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Xiaoliang Wang
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Haixin Cen
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Xuan Li
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Zhaolin Zhai
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Chang Lu
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Yuke Dong
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Suzhen Zhang
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Kaiming Zhuo
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Qiong Xiang
- Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China
| | - Yan Wang
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China.
| | - Dengtang Liu
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, 200040, China; Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Clinical Center for Psychotic Disorders, National Center for Mental Disorders, Shanghai, 200030, China; Institute of Mental Health, Fudan University, Shanghai, 200030, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
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8
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Emsley R. Antipsychotics and structural brain changes: could treatment adherence explain the discrepant findings? Ther Adv Psychopharmacol 2023; 13:20451253231195258. [PMID: 37701891 PMCID: PMC10493054 DOI: 10.1177/20451253231195258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 07/11/2023] [Indexed: 09/14/2023] Open
Abstract
Progressive structural brain changes are well documented in schizophrenia and have been linked to both illness progression and the extent of antipsychotic treatment exposure. Literature reporting longitudinal changes in brain structure in individuals with schizophrenia is selectively reviewed to assess the roles of illness, antipsychotic treatment, adherence and other factors in the genesis of these changes. This narrative review considers literature investigating longitudinal changes in brain structure in individuals with schizophrenia. The review focusses on structural changes in the cortex, basal ganglia and white matter. It also examines effects of medication non-adherence and relapse on the clinical course of the illness and on structural brain changes. Studies investigating structural magnetic resonance imaging changes in patients treated with long-acting injectable antipsychotics are reviewed. Temporal changes in brain structure in schizophrenia can be divided into those that are associated with antipsychotic treatment and those that are not. Changes associated with treatment include increases in basal ganglia and white matter volumes. Relapse episodes may be a critical factor in illness progression and brain volume reductions. Medication adherence may be an important factor that could explain the findings that brain volume reductions are associated with poor treatment response, higher intensity of antipsychotic treatment exposure and more time spent in relapse. Improved adherence via long-acting injectable antipsychotics and adherence focussed psychosocial interventions could maximize protective effects of antipsychotics against illness progression.
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Affiliation(s)
- Robin Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Tygerberg Campus, Cape Town 8000, South Africa
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9
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Wang C, Zhang Y, Lim LG, Cao W, Zhang W, Wan X, Fan L, Liu Y, Zhang X, Tian Z, Liu X, Pan X, Zheng Y, Pan R, Tan Y, Zhang Z, McIntyre RS, Li Z, Ho RCM, Tang TB. An fNIRS investigation of novel expressed emotion stimulations in schizophrenia. Sci Rep 2023; 13:11141. [PMID: 37429942 DOI: 10.1038/s41598-023-38057-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 07/02/2023] [Indexed: 07/12/2023] Open
Abstract
Living in high expressed emotion (EE) environments tends to increase the relapse rate in schizophrenia (SZ). At present, the neural substrates responsible for high EE in SZ remain poorly understood. Functional near-infrared spectroscopy (fNIRS) may be of great use to quantitatively assess cortical hemodynamics and elucidate the pathophysiology of psychiatric disorders. In this study, we designed novel low- (positivity and warmth) and high-EE (criticism, negative emotion, and hostility) stimulations, in the form of audio, to investigate cortical hemodynamics. We used fNIRS to measure hemodynamic signals while participants listened to the recorded audio. Healthy controls (HCs, [Formula: see text]) showed increased hemodynamic activation in the major language centers across EE stimulations, with stronger activation in Wernicke's area during the processing of negative emotional language. Compared to HCs, people with SZ ([Formula: see text]) exhibited smaller hemodynamic activation in the major language centers across EE stimulations. In addition, people with SZ showed weaker or insignificant hemodynamic deactivation in the medial prefrontal cortex. Notably, hemodynamic activation in SZ was found to be negatively correlated with the negative syndrome scale score at high EE. Our findings suggest that the neural mechanisms in SZ are altered and disrupted, especially during negative emotional language processing. This supports the feasibility of using the designed EE stimulations to assess people who are vulnerable to high-EE environments, such as SZ. Furthermore, our findings provide preliminary evidence for future research on functional neuroimaging biomarkers for people with psychiatric disorders.
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Affiliation(s)
| | | | - Lam Ghai Lim
- Department of Electrical and Robotics Engineering, School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, 47500, Bandar Sunway, Selangor, Malaysia.
| | - Weiqi Cao
- Huaibei Normal University, Huaibei, China
| | - Wei Zhang
- Huaibei Mental Health Center, Huaibei, China
| | | | - Lijun Fan
- Huaibei Normal University, Huaibei, China
| | - Ying Liu
- Huaibei Normal University, Huaibei, China
| | - Xi Zhang
- Huaibei Mental Health Center, Huaibei, China
| | | | | | - Xiuzhi Pan
- Huaibei Normal University, Huaibei, China
| | - Yuan Zheng
- Huaibei Normal University, Huaibei, China
| | - Riyu Pan
- Anqing Normal University, Anqing, China
| | - Yilin Tan
- Huaibei Normal University, Huaibei, China
| | | | - Roger S McIntyre
- Mood Disorders Psychopharmacology Unit, Poul Hansen Family Centre for Depression, Toronto, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Brain and Cognition Discovery Foundation, Toronto, Canada
| | - Zhifei Li
- Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore, 117599, Singapore
| | - Roger C M Ho
- Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore, 117599, Singapore
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Tong Boon Tang
- Centre for Intelligent Signal and Imaging Research (CISIR), Universiti Teknologi PETRONAS, 32610, Seri Iskandar, Perak, Malaysia
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10
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Emsley R, du Plessis S, Phahladira L, Luckhoff HK, Scheffler F, Kilian S, Smit R, Buckle C, Chiliza B, Asmal L. Antipsychotic treatment effects and structural MRI brain changes in schizophrenia. Psychol Med 2023; 53:2050-2059. [PMID: 35441587 PMCID: PMC10106303 DOI: 10.1017/s0033291721003809] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 07/21/2021] [Accepted: 09/01/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Progressive brain structural MRI changes are described in schizophrenia and have been ascribed to both illness progression and antipsychotic treatment. We investigated treatment effects, in terms of total cumulative antipsychotic dose, efficacy and tolerability, on brain structural changes over the first 24 months of treatment in schizophrenia. METHODS A prospective, 24-month, single-site cohort study in 99 minimally treated patients with first-episode schizophrenia, schizophreniform and schizoaffective disorder, and 98 matched healthy controls. We treated the patients according to a fixed protocol with flupenthixol decanoate, a long-acting injectable antipsychotic. We assessed psychopathology, cognition, extrapyramidal symptoms and BMI, and acquired MRI scans at months 0, 12 and 24. We selected global cortical thickness, white matter volume and basal ganglia volume as the regions of interest. RESULTS The only significant group × time interaction was for basal ganglia volumes. However, patients, but not controls, displayed cortical thickness reductions and increases in white matter and basal ganglia volumes. Cortical thickness reductions were unrelated to treatment. White matter volume increases were associated with lower cumulative antipsychotic dose, greater improvements in psychopathology and cognition, and more extrapyramidal symptoms. Basal ganglia volume increases were associated with greater improvements in psychopathology, greater increases in BMI and more extrapyramidal symptoms. CONCLUSIONS We provide evidence for plasticity in white matter and basal ganglia associated with antipsychotic treatment in schizophrenia, most likely linked to the dopamine blocking actions of these agents. Cortical changes may be more closely related to the neurodevelopmental, non-dopaminergic aspects of the illness.
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Affiliation(s)
- Robin Emsley
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Stefan du Plessis
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Lebogang Phahladira
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Hilmar K. Luckhoff
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Frederika Scheffler
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Sanja Kilian
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Retha Smit
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Chanelle Buckle
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
| | - Bonginkosi Chiliza
- Department of Psychiatry, Nelson R Mandela School of Medicine, University of Kwazulu-Natal, Durban, South Africa
| | - Laila Asmal
- Department of Psychiatry, Stellenbosch University, Tygerberg Campus, Cape Town, South Africa
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11
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Golimbet V, Lezheiko T, Mikhailova V, Korovaitseva G, Kolesina N, Plakunova V, Kostyuk G. A study of the association between polymorphisms in the genes for interleukins IL-6 and IL-10 and negative symptoms subdomains in schizophrenia. Indian J Psychiatry 2022; 64:484-488. [PMID: 36458089 PMCID: PMC9707661 DOI: 10.4103/indianjpsychiatry.indianjpsychiatry_212_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 06/07/2022] [Accepted: 07/29/2022] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Schizophrenia is a severe mental illness manifested by various symptoms. Negative symptoms (NS) are associated with disability and poor function of patients. The study of NS neurobiology is complicated by their heterogeneity. Factor analysis revealed two distinct NS subdomains with different pathophysiological mechanisms: volitional pathology, including avolition and apathy (AA), and diminished expression (DE). Inflammation is one mechanism that may underlie NS, including their heterogeneity. AIMS To search for the association between genes for interleukins (IL-6 -174 G/C, IL-10 -592 C/A, and IL-10 -1082 G/A) and NS subdomains. MATERIALS AND METHODS The study included 275 patients with schizophrenia. NS factors were calculated based on the Positive and Negative Syndromes Scale. RESULTS There was a significant main effect of IL-10 polymorphisms on the AA, but not the DE subdomain. Mean score on the AA subdomain was higher in the IL-10 -592 AA compared to the CC genotype. Differences between IL-10 -1082 G/A genotypes were dose dependent. The lowest score was observed for the IL-10 -1082 GG genotype. The association between the IL-6 -174 G/C polymorphism and AA scores was close to the level of significance. Patients with the IL-6 -174 GG genotype had higher score compared to the AA genotype. CONCLUSION The results provide further neurobiological evidence for the validity of the NS factor categorization. An imbalance between pro-inflammatory and anti-inflammatory cytokines because of genetic variations is associated with the AA NS subdomain that is supposed to be a more severe aspect of psychopathology compared to the DE.
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Affiliation(s)
- Vera Golimbet
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow, Russia
| | - Tatyana Lezheiko
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow, Russia
| | - Vera Mikhailova
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow, Russia
| | - Galina Korovaitseva
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow, Russia
| | - Nadezhda Kolesina
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow, Russia
| | - Victoria Plakunova
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow, Russia
| | - Georgy Kostyuk
- Moscow Healthcare Department, Clinical Research Center, Mental-Health Clinic No. 1 Named After N.A. Alexeev, Moscow, Russia
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12
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Zhang YJ, Li Y, Wang YM, Wang SK, Pu CC, Zhou SZ, Ma YT, Wang Y, Lui SSY, Yu X, Chan RCK. Hub-connected functional connectivity within social brain network weakens the association with real-life social network in schizophrenia patients. Eur Arch Psychiatry Clin Neurosci 2022; 272:1033-1043. [PMID: 34626218 DOI: 10.1007/s00406-021-01344-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 10/04/2021] [Indexed: 01/10/2023]
Abstract
Hubs in the brain network are the regions with high centrality and are crucial in the network communication and information integration. Patients with schizophrenia (SCZ) exhibit wide range of abnormality in the hub regions and their connected functional connectivity (FC) at the whole-brain network level. Study of the hubs in the brain networks supporting complex social behavior (social brain network, SBN) would contribute to understand the social dysfunction in patients with SCZ. Forty-nine patients with SCZ and 27 healthy controls (HC) were recruited to undertake the resting-state magnetic resonance imaging scanning and completed a social network (SN) questionnaire. The resting-state SBN was constructed based on the automatic analysis results from the NeuroSynth. Our results showed that the left temporal lobe was the only hub of SBN, and its connected FCs strength was higher than the remaining FCs in both two groups. SCZ patients showed the lower association between the hub-connected FCs (compared to the FCs not connected to the hub regions) with the real-life SN characteristics. These results were replicated in another independent sample (30 SCZ and 28 HC). These preliminary findings suggested that the hub-connected FCs of SBN in SCZ patients exhibit the abnormality in predicting real-life SN characteristics.
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Affiliation(s)
- Yi-Jing Zhang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Ying Li
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Yong-Ming Wang
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Shuang-Kun Wang
- Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Cheng-Cheng Pu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Shu-Zhe Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yan-Tao Ma
- Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Simon S Y Lui
- Department of Psychiatry, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Xin Yu
- Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China. .,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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13
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Koutsouleris N, Pantelis C, Velakoulis D, McGuire P, Dwyer DB, Urquijo-Castro MF, Paul R, Dong S, Popovic D, Oeztuerk O, Kambeitz J, Salokangas RKR, Hietala J, Bertolino A, Brambilla P, Upthegrove R, Wood SJ, Lencer R, Borgwardt S, Maj C, Nöthen M, Degenhardt F, Polyakova M, Mueller K, Villringer A, Danek A, Fassbender K, Fliessbach K, Jahn H, Kornhuber J, Landwehrmeyer B, Anderl-Straub S, Prudlo J, Synofzik M, Wiltfang J, Riedl L, Diehl-Schmid J, Otto M, Meisenzahl E, Falkai P, Schroeter ML. Exploring Links Between Psychosis and Frontotemporal Dementia Using Multimodal Machine Learning: Dementia Praecox Revisited. JAMA Psychiatry 2022; 79:907-919. [PMID: 35921104 PMCID: PMC9350851 DOI: 10.1001/jamapsychiatry.2022.2075] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 06/12/2022] [Indexed: 12/04/2022]
Abstract
Importance The behavioral and cognitive symptoms of severe psychotic disorders overlap with those seen in dementia. However, shared brain alterations remain disputed, and their relevance for patients in at-risk disease stages has not been explored so far. Objective To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant frontotemporal dementia (bvFTD), Alzheimer disease (AD), and schizophrenia; estimate predictability in patients with bvFTD and schizophrenia based on sociodemographic, clinical, and biological data; and examine prognostic value, genetic underpinnings, and progression in patients with clinical high-risk (CHR) states for psychosis or recent-onset depression (ROD). Design, Setting, and Participants This study included 1870 individuals from 5 cohorts, including (1) patients with bvFTD (n = 108), established AD (n = 44), mild cognitive impairment or early-stage AD (n = 96), schizophrenia (n = 157), or major depression (n = 102) to derive and compare diagnostic patterns and (2) patients with CHR (n = 160) or ROD (n = 161) to test patterns' prognostic relevance and progression. Healthy individuals (n = 1042) were used for age-related and cohort-related data calibration. Data were collected from January 1996 to July 2019 and analyzed between April 2020 and April 2022. Main Outcomes and Measures Case assignments based on diagnostic patterns; sociodemographic, clinical, and biological data; 2-year functional outcomes and genetic separability of patients with CHR and ROD with high vs low pattern expression; and pattern progression from baseline to follow-up MRI scans in patients with nonrecovery vs preserved recovery. Results Of 1870 included patients, 902 (48.2%) were female, and the mean (SD) age was 38.0 (19.3) years. The bvFTD pattern comprising prefrontal, insular, and limbic volume reductions was more expressed in patients with schizophrenia (65 of 157 [41.2%]) and major depression (22 of 102 [21.6%]) than the temporo-limbic AD patterns (28 of 157 [17.8%] and 3 of 102 [2.9%], respectively). bvFTD expression was predicted by high body mass index, psychomotor slowing, affective disinhibition, and paranoid ideation (R2 = 0.11). The schizophrenia pattern was expressed in 92 of 108 patients (85.5%) with bvFTD and was linked to the C9orf72 variant, oligoclonal banding in the cerebrospinal fluid, cognitive impairment, and younger age (R2 = 0.29). bvFTD and schizophrenia pattern expressions forecasted 2-year psychosocial impairments in patients with CHR and were predicted by polygenic risk scores for frontotemporal dementia, AD, and schizophrenia. Findings were not associated with AD or accelerated brain aging. Finally, 1-year bvFTD/schizophrenia pattern progression distinguished patients with nonrecovery from those with preserved recovery. Conclusions and Relevance Neurobiological links may exist between bvFTD and psychosis focusing on prefrontal and salience system alterations. Further transdiagnostic investigations are needed to identify shared pathophysiological processes underlying the neuroanatomical interface between the 2 disease spectra.
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Affiliation(s)
- Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Max-Planck Institute of Psychiatry, Munich, Germany
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Australia
| | - Philip McGuire
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Dominic B. Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | | | - Riya Paul
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Sen Dong
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - David Popovic
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Oemer Oeztuerk
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | | | - Jarmo Hietala
- Department of Psychiatry, University of Turku, Turku, Finland
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Rachel Upthegrove
- Institute of Mental Health, University of Birmingham, Birmingham, United Kingdom
- Early Intervention Service, Birmingham Women’s and Children’s NHS Foundation Trust, Birmingham, United Kingdom
| | - Stephen J. Wood
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Institute for Translational Psychiatry, University Muenster, Muenster, Germany
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Department of Psychiatry, University Psychiatric Clinics (UPK), University of Basel, Basel, Switzerland
| | - Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Markus Nöthen
- Institute of Human Genetics, School of Medicine, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, School of Medicine, University Hospital Bonn, University of Bonn, Bonn, Germany
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Duisburg, Germany
| | - Maryna Polyakova
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Karsten Mueller
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Adrian Danek
- Department of Neurology, Ludwig Maximilian University Munich, Munich, Germany
| | - Klaus Fassbender
- Department of Neurology, Saarland University Hospital, Homburg, Germany
| | - Klaus Fliessbach
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
| | - Holger Jahn
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg, Hamburg, Germany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | | | | | - Johannes Prudlo
- Department of Neurology, University Medicine Rostock, Rostock, Germany
| | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Neurodegenerative Diseases, Center of Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Psychiatry and Psychotherapy, Medical University Göttingen, Göttingen, Germany
| | - Lina Riedl
- Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University, Munich, Germany
| | - Matthias L. Schroeter
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
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14
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Sadeghi D, Shoeibi A, Ghassemi N, Moridian P, Khadem A, Alizadehsani R, Teshnehlab M, Gorriz JM, Khozeimeh F, Zhang YD, Nahavandi S, Acharya UR. An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works. Comput Biol Med 2022; 146:105554. [DOI: 10.1016/j.compbiomed.2022.105554] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 04/11/2022] [Accepted: 04/11/2022] [Indexed: 12/21/2022]
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15
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Moghimi P, Dang AT, Do Q, Netoff TI, Lim KO, Atluri G. Evaluation of functional MRI-based human brain parcellation: a review. J Neurophysiol 2022; 128:197-217. [PMID: 35675446 DOI: 10.1152/jn.00411.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.
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Affiliation(s)
- Pantea Moghimi
- Department of Neurobiology, University of Chicago, Chicago, Illinois
| | - Anh The Dang
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio
| | - Quan Do
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio
| | - Theoden I Netoff
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Kelvin O Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota
| | - Gowtham Atluri
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio
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An observational study of antipsychotic medication discontinuation in first-episode psychosis: clinical and functional outcomes. Soc Psychiatry Psychiatr Epidemiol 2022; 57:1329-1340. [PMID: 35041015 DOI: 10.1007/s00127-022-02230-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 01/06/2022] [Indexed: 10/19/2022]
Abstract
PURPOSE To study the impact of supervised antipsychotic medication discontinuation on clinical and functional outcomes in first-episode psychosis (FEP) in two different cultural environments. METHOD FEP patients(N = 253), treated in two early intervention services (Montreal, Canada and Chennai, India) for 2 years, were assessed for medication use, positive and negative symptom remission and social-occupational functioning at regular intervals. RESULTS Between months 4 and 24 of treatment, 107 patients discontinued medication ('Off'group) as compared to 146 who stayed on medication ('On'group). Medication discontinuation was higher in Chennai as compared to Montreal (n = 80, 49.07% vs n = 27, 16.87%; χ2 37.80, p < 0.001), with no difference in time to discontinuation [Means(SDs) = 10.64(6.82) and 10.04(5.43), respectively, p = 0.71). At month 24 (N = 235), there were no differences in the rate of positive symptom remission between the on and Off groups (81.5 vs 88.0%, respectively) at both sites. The rate of negative symptom remission was lower among patients in the On compared to the Off group (63.2 vs 87.9%, respectively, χ2 = 17.91, p < 0.001), but only in Montreal (55.4% vs 80.0%, respectively, χ2 = 4.12, p < 0.05). Social and Occupational Functioning Assessment Scale scores were equally high in both Off and On medication groups in Chennai [Means (SDs) = 79.43(12.95) and 73.59(17.63), respectively] but higher in the Off compared to the On group in Montreal Means (SDs) = 77.47(14.97) and 64.94(19.02), respectively; Time × site interaction F = 3.96(1,217), p < 0.05]. Medication status (On-Off) had no impact on the outcomes, independent of other variables known to influence outcomes. CONCLUSION Certain cultural environments and patient characteristics may facilitate supervised discontinuation of antipsychotic medication following treatment of an FEP without negative consequences.
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17
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Zhu D, Wang C, Guo L, Si D, Liu M, Cai M, Ma L, Fu D, Fu J, Wang J, Liu F. Total Brain Volumetric Measures and Schizophrenia Risk: A Two-Sample Mendelian Randomization Study. Front Genet 2022; 13:782476. [PMID: 35432453 PMCID: PMC9008758 DOI: 10.3389/fgene.2022.782476] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 03/02/2022] [Indexed: 01/10/2023] Open
Abstract
Schizophrenia (SCZ) is an idiopathic psychiatric disorder with a heritable component and a substantial public health impact. Although abnormalities in total brain volumetric measures (TBVMs) have been found in patients with SCZ, it is still unknown whether these abnormalities have a causal effect on the risk of SCZ. Here, we performed a Mendelian randomization (MR) study to investigate the possible causal associations between each TBVM and SCZ risk. Specifically, genome-wide association study (GWAS) summary statistics of total gray matter volume, total white matter volume, total cerebrospinal fluid volume, and total brain volume were obtained from the United Kingdom Biobank database (33,224 individuals), and SCZ GWAS summary statistics were provided by the Psychiatric Genomics Consortium (150,064 individuals). The main MR analysis was conducted using the inverse variance weighted method, and other MR methods, including MR-Egger, weighted median, simple mode, and weighted mode methods, were performed to assess the robustness of our findings. For pleiotropy analysis, we employed three approaches: MR-Egger intercept, MR-PRESSO, and heterogeneity tests. No TBVM was causally associated with SCZ risk according to the MR results, and no significant pleiotropy or heterogeneity was found for instrumental variables. Taken together, this study suggested that alterations in TBVMs were not causally associated with the risk of SCZ.
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Affiliation(s)
- Dan Zhu
- Department of Radiology, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chunyang Wang
- Department of Scientific Research, Tianjin Medical University General Hospital, Tianjin, China
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Daojun Si
- National Supercomputer Center in Tianjin, Tianjin, China
| | - Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Dianxun Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Feng Liu, ; Junping Wang, ; Jilian Fu,
| | - Junping Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Feng Liu, ; Junping Wang, ; Jilian Fu,
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Feng Liu, ; Junping Wang, ; Jilian Fu,
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Present and future antipsychotic drugs: a systematic review of the putative mechanisms of action for efficacy and a critical appraisal under a translational perspective. Pharmacol Res 2022; 176:106078. [PMID: 35026403 DOI: 10.1016/j.phrs.2022.106078] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/23/2021] [Accepted: 01/07/2022] [Indexed: 01/10/2023]
Abstract
Antipsychotics represent the mainstay of schizophrenia pharmacological therapy, and their role has been expanded in the last years to mood disorders treatment. Although introduced in 1952, many years of research were required before an accurate picture of how antipsychotics work began to emerge. Despite the well-recognized characterization of antipsychotics in typical and atypical based on their liability to induce motor adverse events, their main action at dopamine D2R to elicit the "anti-psychotic" effect, as well as the multimodal action at other classes of receptors, their effects on intracellular mechanisms starting with receptor occupancy is still not completely understood. Significant lines of evidence converge on the impact of these compounds on multiple molecular signaling pathways implicated in the regulation of early genes and growth factors, dendritic spine shape, brain inflammation, and immune response, tuning overall the function and architecture of the synapse. Here we present, based on PRISMA approach, a comprehensive and systematic review of the above mechanisms under a translational perspective to disentangle those intracellular actions and signaling that may underline clinically relevant effects and represent potential targets for further innovative strategies in antipsychotic therapy.
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19
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Kanahara N, Yamanaka H, Shiko Y, Kawasaki Y, Iyo M. The effects of cumulative antipsychotic dose on brain structures in patients with schizophrenia: Observational study of multiple CT scans over a long-term clinical course. Psychiatry Res Neuroimaging 2022; 319:111422. [PMID: 34856453 DOI: 10.1016/j.pscychresns.2021.111422] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 10/23/2021] [Accepted: 10/28/2021] [Indexed: 10/19/2022]
Abstract
Multiple lines of evidence indicate that antipsychotic agents could affect brain structures of schizophrenia patients. However, the effect of antipsychotic dosage or type on brain structure is uncertain. The present study retrospectively analyzed brain computed tomography (CT) images from a psychiatric hospital to examine the relationship between cumulative dose of antipsychotics and brain volume reduction in schizophrenia patients. A total of 43 patients with repeated relapse episode of psychosis were included and CT scans that were performed an average of 3.2 times per patient during nearly 13 years of follow-up were analyzed. The results revealed significant positive relationships of expansion of cerebrospinal fluid space with cumulative dosage of all antipsychotics and that of typical antipsychotics. Patients treated with antipsychotics including typical antipsychotics exhibited a greater volume reduction compared to patients treated with only atypical antipsychotics. The present study was one of the longest longitudinal studies examining the effects of antipsychotics on brain volume in schizophrenia patients. These results suggest a relation between cumulative lifetime antipsychotic dosage and progressive brain volume reduction in patients with schizophrenia. However, the effects of specific agent on brain structure are still uncertain, and more detailed analysis is needed.
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Affiliation(s)
- Nobuhisa Kanahara
- Division of Medical Treatment and Rehabilitation, Center for Forensic Mental Health, Chiba University, Chiba, Japan; Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan.
| | - Hiroshi Yamanaka
- Department of Psychiatry, Chiba Psychiatric Medical Center, Chiba, Japan
| | - Yuki Shiko
- Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
| | - Yohei Kawasaki
- Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
| | - Masaomi Iyo
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
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20
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Zhang YJ, Cai XL, Hu HX, Zhang RT, Wang Y, Lui SSY, Cheung EFC, Chan RCK. Social brain network predicts real-world social network in individuals with social anhedonia. Psychiatry Res Neuroimaging 2021; 317:111390. [PMID: 34537603 DOI: 10.1016/j.pscychresns.2021.111390] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 08/11/2021] [Accepted: 09/08/2021] [Indexed: 01/10/2023]
Abstract
Social anhedonia (SA) impairs social functioning in schizophrenia. Previous evidence suggested that certain brain regions predict longitudinal change of real-world social outcomes, yet previous study designs have failed to capture the corresponding functional connectivity among the brain regions involved. This study measured the real-world social network in 22 pairs of individuals with high and low levels of SA, and followed up them for 21 months. We further explored whether resting-state social brain network characteristics could predict the longitudinal variations of real-world social network. Our results showed that social brain network characteristics could predict the change of real-world social networks in both the high SA and low SA groups. However, the results differed between the two groups, i.e., the topological characteristics of the social brain network predicted real-world social network change in the high SA group; whereas the functional connectivity within the social brain network predicted real-world social network change in the low SA group. Principal component analysis and linear regression analysis on the entire sample showed that the functional connectivity component centered at the right orbital inferior frontal gyrus could best predict social network change. Our findings support the notion that social brain network characteristics could predict social network development.
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Affiliation(s)
- Yi-Jing Zhang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Xin-Lu Cai
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China
| | - Hui-Xin Hu
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Rui-Ting Zhang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Simon S Y Lui
- Castle Peak Hospital, Hong Kong Special Administrative Region, China; Department of Psychiatry, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Eric F C Cheung
- Department of Psychiatry, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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21
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Shan X, Zhang H, Dong Z, Chen J, Liu F, Zhao J, Zhang H, Guo W. Increased subcortical region volume induced by electroconvulsive therapy in patients with schizophrenia. Eur Arch Psychiatry Clin Neurosci 2021; 271:1285-1295. [PMID: 34275006 DOI: 10.1007/s00406-021-01303-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 07/04/2021] [Indexed: 02/08/2023]
Abstract
Electroconvulsive therapy (ECT) has been widely used to treat patients with schizophrenia. However, the underlying mechanisms of ECT remain unknown. In the present study, the treatment effects of ECT on brain structure in patients with schizophrenia were explored. Seventy patients with schizophrenia were scanned using structural magnetic resonance imaging. Patients in the drug group were scanned at baseline (time 1) and follow-up (time 2, 6 weeks of treatment). Patients in the ECT group were scanned before ECT treatment (baseline, time 1) and 10-12 h after the last ECT treatment (time 2). Voxel-based morphometry was applied to analyze the imaging data. Patients in the ECT group showed significantly increased gray matter volume (GMV) in the bilateral hippocampus/amygdala and left superior temporal gyrus (STG)/middle temporal gyrus (MTG) after ECT combined with antipsychotic therapy at time 2. In contrast, patients in the drug group showed decreased GMV in widespread brain regions. Correlation analysis results showed significantly negative correlations between the increased GMV in the bilateral hippocampus/amygdala and PANSS scores at baseline in the ECT group. ECT may modulate brain structure in patients with schizophrenia. The GMV in distinct subcortical regions was related to the individual therapeutic response in patients with schizophrenia.
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Affiliation(s)
- Xiaoxiao Shan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Haisan Zhang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China.,Xinxiang Key Laboratory of Multimodal Brain Imaging, Xinxiang, 453002, Henan, China
| | - Zhao Dong
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China.,Zhumadian Psychiatric Hospital, Zhumadian, 463000, Henan, China
| | - Jindong Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300000, China
| | - Jingping Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Hongxing Zhang
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China. .,Xinxiang Key Laboratory of Multimodal Brain Imaging, Xinxiang, 453002, Henan, China. .,School of Psychology, Xinxiang Medical University, Xinxiang, 453003, Henan, China.
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. .,Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China.
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22
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The progression of disorder-specific brain pattern expression in schizophrenia over 9 years. NPJ SCHIZOPHRENIA 2021; 7:32. [PMID: 34127678 PMCID: PMC8203625 DOI: 10.1038/s41537-021-00157-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 04/21/2021] [Indexed: 11/16/2022]
Abstract
Age plays a crucial role in the performance of schizophrenia vs. controls (SZ-HC) neuroimaging-based machine learning (ML) models as the accuracy of identifying first-episode psychosis from controls is poor compared to chronic patients. Resolving whether this finding reflects longitudinal progression in a disorder-specific brain pattern or a systematic but non-disorder-specific deviation from a normal brain aging (BA) trajectory in schizophrenia would help the clinical translation of diagnostic ML models. We trained two ML models on structural MRI data: an SZ-HC model based on 70 schizophrenia patients and 74 controls and a BA model (based on 561 healthy individuals, age range = 66 years). We then investigated the two models’ predictions in the naturalistic longitudinal Northern Finland Birth Cohort 1966 (NFBC1966) following 29 schizophrenia and 61 controls for nine years. The SZ-HC model’s schizophrenia-specificity was further assessed by utilizing independent validation (62 schizophrenia, 95 controls) and depression samples (203 depression, 203 controls). We found better performance at the NFBC1966 follow-up (sensitivity = 75.9%, specificity = 83.6%) compared to the baseline (sensitivity = 58.6%, specificity = 86.9%). This finding resulted from progression in disorder-specific pattern expression in schizophrenia and was not explained by concomitant acceleration of brain aging. The disorder-specific pattern’s progression reflected longitudinal changes in cognition, outcomes, and local brain changes, while BA captured treatment-related and global brain alterations. The SZ-HC model was also generalizable to independent schizophrenia validation samples but classified depression as control subjects. Our research underlines the importance of taking account of longitudinal progression in a disorder-specific pattern in schizophrenia when developing ML classifiers for different age groups.
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23
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Clinicopathological investigation of the background of cognitive decline in elderly schizophrenia. Acta Neuropsychiatr 2021; 33:85-91. [PMID: 33143788 DOI: 10.1017/neu.2020.40] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
OBJECTIVE We have often observed dementia symptoms or severe neurocognitive decline in the long-term course of schizophrenia. While there are epidemiological reports that patients with schizophrenia are at an increased risk of developing dementia, there are also neuropathological reports that the prevalence of Alzheimer's disease (AD) in schizophrenia is similar to that in normal controls. It is difficult to distinguish, based solely on the clinical symptoms, whether the remarkable dementia symptoms and cognitive decline seen in elderly schizophrenia are due to the course of the disease itself or a concomitant neurocognitive disease. Neuropathological observation is needed for discrimination. METHODS We conducted a neuropathological search on three cases of schizophrenia that developed cognitive decline or dementia symptoms after a long illness course of schizophrenia. The clinical symptoms of total disease course were confirmed retrospectively in the medical record. We have evaluated neuropathological diagnosis based on not only Hematoxylin-Eosin and Klüver-Barrera staining specimens but also immunohistochemical stained specimens including tau, β-amyloid, pTDP-43 and α-synuclein protein throughout clinicopathological conference with multiple neuropathologists and psychiatrists. RESULTS The three cases showed no significant pathological findings or preclinical degenerative findings, and poor findings consistent with symptoms of dementia were noted. CONCLUSION Although the biological background of dementia symptoms in elderly schizophrenic patients is still unclear, regarding the brain capacity/cognitive reserve ability, preclinical neurodegeneration changes in combination with certain brain vulnerabilities due to schizophrenia itself are thought to induce dementia syndrome and severe cognitive decline.
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24
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Enache D, Nikkheslat N, Fathalla D, Morgan BP, Lewis S, Drake R, Deakin B, Walters J, Lawrie SM, Egerton A, MacCabe JH, Mondelli V. Peripheral immune markers and antipsychotic non-response in psychosis. Schizophr Res 2021; 230:1-8. [PMID: 33667853 PMCID: PMC8224180 DOI: 10.1016/j.schres.2020.12.020] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 12/19/2020] [Accepted: 12/30/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Peripheral immune markers have previously been linked to a poor response to antipsychotic medication and more severe negative symptoms at the onset of psychosis. The present study investigated the association of blood cytokines and complement markers with the presence of antipsychotic non-response and symptom severity in patients with psychosis. METHODS This cross-sectional study recruited 94 patients with schizophrenia and other psychoses, of whom 47 were defined as antipsychotic responders and 47 as antipsychotic non-responders. In all subjects we measured plasma levels of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, and IFN-γ), complement markers (C1-inhibitor, C3, C4, C3a, C3b, Bb, factor D, C5a, terminal complement complex) and high sensitivity C-reactive protein (hsCRP). Symptom severity was recorded using the Positive and Negative Syndrome scale for Schizophrenia (PANSS). Binary logistic regression tested each immune marker as predictor of response status while covarying for relevant socio-demographic variables. Correlation analyses tested the association between immune markers and the severity of symptoms. RESULTS Interleukin (IL)-8 significantly predicted antipsychotic non-response (OR=24.70, 95% CI, 1.35-453.23, p = 0.03). Other immune markers were not associated with antipsychotic response. IL-6, IL-8, IL-10 and TNF-α significantly positively correlated with negative psychotic symptoms. CONCLUSIONS Higher levels of IL-8 are associated with a poor response to antipsychotic treatment. Increased cytokines levels are specifically associated with more severe negative symptoms in patients with schizophrenia and other psychoses.
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Affiliation(s)
- Daniela Enache
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK; Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Naghmeh Nikkheslat
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK
| | - Dina Fathalla
- Dementia Research Institute, Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK
| | - B Paul Morgan
- Dementia Research Institute, Division of Infection and Immunity, School of Medicine, Cardiff University, Cardiff, UK
| | - Shôn Lewis
- Department of Psychiatry, University of Manchester, Manchester, UK
| | - Richard Drake
- Department of Psychiatry, University of Manchester, Manchester, UK
| | - Bill Deakin
- Department of Psychiatry, University of Manchester, Manchester, UK
| | - James Walters
- MRC Centre for Neuropsychiatric Genetics, Cardiff University, Cardiff, UK
| | - Stephen M Lawrie
- Department of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Alice Egerton
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychosis Studies, London, UK; National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King's College London, UK
| | - James H MacCabe
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychosis Studies, London, UK; National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King's College London, UK
| | - Valeria Mondelli
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK; National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King's College London, UK.
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25
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Li Y, Zhang L, Zhang Y, Wen H, Huang J, Shen Y, Li H. A Random Forest Model for Predicting Social Functional Improvement in Chinese Patients with Schizophrenia After 3 Months of Atypical Antipsychotic Monopharmacy: A Cohort Study. Neuropsychiatr Dis Treat 2021; 17:847-857. [PMID: 33776440 PMCID: PMC7989048 DOI: 10.2147/ndt.s280757] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/02/2021] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Impaired social functions contribute to the burden of schizophrenia patients and their families, but predictive tools of social functioning prognosis and specific factors are undefined in Chinese clinical practice. This article explores a machine learning tool to identify whether patients will achieve significant social functional improvement after 3 months of atypical antipsychotic monopharmacy and finds the defined risk factors using a multicenter clinical study. PATIENTS AND METHODS A multicenter study on atypical antipsychotic (AAP) treatment in Chinese patients with schizophrenia (SALT-C) was conducted from July 2011 to August 2018. Data from 550 patients with AAP monopharmacy from their baseline to their 3-month follow-up were used to establish machine learning tools after screening. The positive outcome was an increase in the Personal and Social Performance (PSP) scale score by ≥10 points. The predictors were a range of investigator-rated assessments on symptoms, functioning, the safety of AAPs and illness history. The Least Absolute Shrinkage and Selection Operator (LASSO) was used for the feature screening and ranking of the predicted variables. The random forest algorithm and five-fold cross-validation for optimizing the model were selected to ensure the generalizability and precision. RESULTS There were 137 patients (mean [SD] age, 41.1 [16.8] years; 77 [58.8%] female) who had a good social functional prognosis. A lower PSP score, taking a mood stabilizer, a high total Positive and Negative Symptom Scale (PANSS) and PANSS general subscale score, unemployment, a hepatic injury with medication, comorbid cardiovascular disease and being male predicted poor PSP outcomes. The generalizability of the PSP predictive tool was estimated with the precision-recall curve (accuracy of 79.5%, negative predictive value of 92.6% and positive predictive value of 57.1%) and receiver operating characteristic curve (ROC) (specificity of 81.8% and sensitivity of 78.7%). CONCLUSION The machine learning tool established using our current real-world data could assist in predicting PSP outcome by several clinical factors.
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Affiliation(s)
- Yange Li
- Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Lei Zhang
- Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yan Zhang
- Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Hui Wen
- Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jingjing Huang
- Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Key Laboratory of Psychotic Disorders, Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yifeng Shen
- Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Key Laboratory of Psychotic Disorders, Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Clinical Research Center for Mental Health, Shanghai, People's Republic of China
| | - Huafang Li
- Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Key Laboratory of Psychotic Disorders, Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.,Shanghai Clinical Research Center for Mental Health, Shanghai, People's Republic of China
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26
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Yin P, Zhao C, Li Y, Liu X, Chen L, Hong N. Changes in Brain Structure, Function, and Network Properties in Patients With First-Episode Schizophrenia Treated With Antipsychotics. Front Psychiatry 2021; 12:735623. [PMID: 34916969 PMCID: PMC8668948 DOI: 10.3389/fpsyt.2021.735623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 11/09/2021] [Indexed: 01/10/2023] Open
Abstract
Purpose: Comprehensive and longitudinal brain analysis is of great significance for understanding the pathological changes of antipsychotic drug treatment in patients with schizophrenia. This study aimed to investigate the changes of structure, function, and network properties in patients with first-episode schizophrenia (FES) after antipsychotic therapy and their relationship with clinical symptoms. Materials and Methods: A total of 30 patients diagnosed with FES and 30 healthy subjects matched for sex and age were enrolled in our study. Patients at baseline were labeled as antipsychotic-naive first-episode schizophrenia (AN-FES), and patients after antipsychotic treatment were labeled as antipsychotic treatment first-episode schizophrenia (AT-FES). The severity of illness was measured by using the PANSS and CGI score. Structural and functional MRI data were also performed. Differences in GMV, ALFF, and ReHo between the FES group and healthy control group were tested using a voxel-wise two-sample t-test, and the comparison of AN-FES group and AT-FES group was evaluated by paired-sample t-test. Results: After the 1-year follow-up, the FES patients showed increased GMV in the right cerebellum, right inferior temporal gyrus, left middle frontal gyrus, parahippocampal gyrus, bilateral inferior parietal lobule, and reduced GMV in the left occipital lobe, gyrus rectus, right orbital frontal cortex. The patients also showed increased ALFF in the medial superior frontal gyrus and right precentral gyrus. For network properties, the patients showed reduced characteristic path length and increased global efficiency. The GMV of the right inferior parietal lobule was negatively correlated with the clinical symptoms. Conclusions: Our study showed that the antipsychotic treatment contributed to the structural alteration and functional improvement, and the GMV alteration may be associated with the improvement of clinical symptoms.
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Affiliation(s)
- Ping Yin
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Chao Zhao
- Department of Interventional Radiology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yang Li
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Xiaoyi Liu
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Lei Chen
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Nan Hong
- Department of Radiology, Peking University People's Hospital, Beijing, China
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27
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Akudjedu TN, Tronchin G, McInerney S, Scanlon C, Kenney JPM, McFarland J, Barker GJ, McCarthy P, Cannon DM, McDonald C, Hallahan B. Progression of neuroanatomical abnormalities after first-episode of psychosis: A 3-year longitudinal sMRI study. J Psychiatr Res 2020; 130:137-151. [PMID: 32818662 DOI: 10.1016/j.jpsychires.2020.07.034] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 07/09/2020] [Accepted: 07/22/2020] [Indexed: 02/08/2023]
Abstract
The location, extent and progression of longitudinal morphometric changes after first-episode of psychosis (FEP) remains unclear. We investigated ventricular and cortico-subcortical regions over a 3-year period in FEP patients compared with healthy controls. High resolution 1.5T T1-weighted MR images were obtained at baseline from 28 FEP patients at presentation and 28 controls, and again after 3-years. The longitudinal FreeSurfer pipeline (v.5.3.0) was used for regional volumetric and cortical reconstruction image analyses. Repeated-measures ANCOVA and vertex-wise linear regression analyses compared progressive changes between groups in subcortical structures and cortical thickness respectively. Compared with controls, patients displayed progressively reduced volume of the caudate [F (1,51)=5.86, p=0.02, Hedges' g=0.66], putamen [F (1,51)=6.06, p=0.02, g=0.67], thalamus [F (1,51)=6.99, p=0.01, g=0.72] and increased right lateral ventricular volume [F (1, 51)=4.03, p=0.05], and significantly increased rate of cortical thinning [F (1,52)=5.11, p=0.028)] at a mean difference of 0.84% [95% CI (0.10, 1.59)] in the left lateral orbitofrontal region over the 3-year period. In patients, greater reduction in putamen volume over time was associated with lower cumulative antipsychotic medication dose (r=0.49, p=0.01), and increasing lateral ventricular volume over time was associated with worsening negative symptoms (r=0.41, p=0.04) and poorer global functioning (r= -0.41, p=0.04). This study demonstrates localised progressive structural abnormalities in the cortico-striato-thalamo-cortical circuit after the onset of psychosis, with increasing ventricular volume noted as a neuroanatomical marker of poorer clinical and functional outcome.
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Affiliation(s)
- Theophilus N Akudjedu
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland; Institute of Medical Imaging & Visualisation, Department of Medical Science and Public Health, Faculty of Health and Social Sciences, Bournemouth University, Bournemouth, UK.
| | - Giulia Tronchin
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland
| | - Shane McInerney
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland; Department of Psychiatry, University of Toronto, 250 College Street, 8th Floor, Toronto, Canada
| | - Cathy Scanlon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland
| | - Joanne P M Kenney
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - John McFarland
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland
| | - Gareth J Barker
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Department of Neuroimaging, London, UK
| | - Peter McCarthy
- Department of Radiology, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland
| | - Dara M Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland
| | - Brian Hallahan
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91TK33, Galway, Ireland
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28
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Palaniyappan L, Sukumar N. Reconsidering brain tissue changes as a mechanistic focus for early intervention in psychiatry. J Psychiatry Neurosci 2020; 44:373-378. [PMID: 33119489 PMCID: PMC7595740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/31/2024] Open
Affiliation(s)
- Lena Palaniyappan
- From the Robarts Research Institute, Western University (Palaniyappan); the Department of Psychiatry, Western University (Palaniyappan, Sukumar); the Lawson Health Research Institute, Imaging Division (Palaniyappan); and the Department of Medical Biophysics, Western University (Palaniyappan), London, Ont., Canada
| | - Niron Sukumar
- From the Robarts Research Institute, Western University (Palaniyappan); the Department of Psychiatry, Western University (Palaniyappan, Sukumar); the Lawson Health Research Institute, Imaging Division (Palaniyappan); and the Department of Medical Biophysics, Western University (Palaniyappan), London, Ont., Canada
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29
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Palaniyappan L, Sukumar N. Reconsidering brain tissue changes as a mechanistic focus for early intervention in psychiatry. J Psychiatry Neurosci 2020; 45. [PMID: 33119489 PMCID: PMC7595740 DOI: 10.1503/jpn.200172] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Affiliation(s)
- Lena Palaniyappan
- From the Robarts Research Institute, Western University (Palaniyappan); the Department of Psychiatry, Western University (Palaniyappan, Sukumar); the Lawson Health Research Institute, Imaging Division (Palaniyappan); and the Department of Medical Biophysics, Western University (Palaniyappan), London, Ont., Canada
| | - Niron Sukumar
- From the Robarts Research Institute, Western University (Palaniyappan); the Department of Psychiatry, Western University (Palaniyappan, Sukumar); the Lawson Health Research Institute, Imaging Division (Palaniyappan); and the Department of Medical Biophysics, Western University (Palaniyappan), London, Ont., Canada
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Avery SN, Armstrong K, McHugo M, Vandekar S, Blackford JU, Woodward ND, Heckers S. Relational Memory in the Early Stage of Psychosis: A 2-Year Follow-up Study. Schizophr Bull 2020; 47:75-86. [PMID: 32657351 PMCID: PMC7825006 DOI: 10.1093/schbul/sbaa081] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Relational memory, the ability to bind information into complex memories, is moderately impaired in early psychosis and severely impaired in chronic schizophrenia, suggesting relational memory may worsen throughout the course of illness. METHODS We examined relational memory in 66 early psychosis patients and 64 healthy control subjects, with 59 patients and 52 control subjects assessed longitudinally at baseline and 2-year follow-up. Relational memory was assessed with 2 complementary tasks, to test how individuals learn relationships between items (face-scene binding task) and make inferences about trained relationships (associative inference task). RESULTS The early psychosis group showed impaired relational memory in both tasks relative to the healthy control group. The ability to learn relationships between items remained impaired in early psychosis patients, while the ability to make inferences about trained relationships improved, although never reaching the level of healthy control performance. Early psychosis patients who did not progress to schizophrenia at follow-up had better relational memory than patients who did. CONCLUSIONS Relational memory impairments, some of which improve and are less severe in patients who do not progress to schizophrenia, are a target for intervention in early psychosis.
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Affiliation(s)
- Suzanne N Avery
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Kristan Armstrong
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Maureen McHugo
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Jennifer Urbano Blackford
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN,Department of Research and Development, Veterans Affairs Medical Center, Nashville, TN
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN,To whom correspondence should be addressed; Vanderbilt Psychiatric Hospital, 1601 23rd Avenue South, Room 3060, Nashville, TN 37212; tel: (615)-322-2665, fax: (615)-343-8400, e-mail:
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31
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Tronchin G, Akudjedu TN, Ahmed M, Holleran L, Hallahan B, Cannon DM, McDonald C. Progressive subcortical volume loss in treatment-resistant schizophrenia patients after commencing clozapine treatment. Neuropsychopharmacology 2020; 45:1353-1361. [PMID: 32268345 PMCID: PMC7298040 DOI: 10.1038/s41386-020-0665-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/20/2020] [Accepted: 03/24/2020] [Indexed: 02/07/2023]
Abstract
The association of antipsychotic medication with abnormal brain morphometry in schizophrenia remains uncertain. This study investigated subcortical morphometric changes 6 months after switching treatment to clozapine in patients with treatment-resistant schizophrenia compared with healthy volunteers, and the relationships between longitudinal volume changes and clinical variables. In total, 1.5T MRI images were acquired at baseline before commencing clozapine and again after 6 months of treatment for 33 patients with treatment-resistant schizophrenia and 31 controls, and processed using the longitudinal pipeline of Freesurfer v.5.3.0. Two-way repeated MANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. Whereas no significant subcortical volume differences were found between patients and controls at baseline (F(8,52) = 1.79; p = 0.101), there was a significant interaction between time, group and structure (F(7,143) = 52.54; p < 0.001). Corrected post-hoc analyses demonstrated that patients had significant enlargement of lateral ventricles (F(1,59) = 48.89; p < 0.001) and reduction of thalamus (F(1,59) = 34.85; p < 0.001), caudate (F(1,59) = 59.35; p < 0.001), putamen (F(1,59) = 87.20; p < 0.001) and hippocampus (F(1,59) = 14.49; p < 0.001) volumes. Thalamus and putamen volume reduction was associated with improvement in PANSS (r = 0.42; p = 0.021, r = 0.39; p = 0.033), SANS (r = 0.36; p = 0.049, r = 0.40; p = 0.027) and GAF (r = -0.39; p = 0.038, r = -0.42; p = 0.024) scores. Reduced thalamic volume over time was associated with increased serum clozapine level at follow-up (r = -0.44; p = 0.010). Patients with treatment-resistant schizophrenia display progressive subcortical volume deficits after switching to clozapine despite experiencing symptomatic improvement. Thalamo-striatal progressive volumetric deficit associated with symptomatic improvement after clozapine exposure may reflect an adaptive response related to improved outcome rather than a harmful process.
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Affiliation(s)
- Giulia Tronchin
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland.
| | - Theophilus N Akudjedu
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
- Institute of Medical Imaging & Visualisation, Faculty of Health & Social Science, Department of Medical Science & Public Science, Bournemouth University, Bournemouth, UK
| | - Mohamed Ahmed
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Laurena Holleran
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Brian Hallahan
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Dara M Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
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Palaniyappan L. Inefficient neural system stabilization: a theory of spontaneous resolutions and recurrent relapses in psychosis. J Psychiatry Neurosci 2019; 44:367-383. [PMID: 31245961 PMCID: PMC6821513 DOI: 10.1503/jpn.180038] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 02/07/2019] [Accepted: 03/05/2019] [Indexed: 12/21/2022] Open
Abstract
A striking feature of psychosis is its heterogeneity. Presentations of psychosis vary from transient symptoms with no functional consequence in the general population to a tenacious illness at the other extreme, with a wide range of variable trajectories in between. Even among patients with schizophrenia, who are diagnosed on the basis of persistent deterioration, marked variation is seen in response to treatment, frequency of relapses and degree of eventual recovery. Existing theoretical accounts of psychosis focus almost exclusively on how symptoms are initially formed, with much less emphasis on explaining their variable course. In this review, I present an account that links several existing notions of the biology of psychosis with the variant clinical trajectories. My aim is to incorporate perspectives of systems neuroscience in a staging framework to explain the individual variations in illness course that follow the onset of psychosis.
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Affiliation(s)
- Lena Palaniyappan
- From the Department of Psychiatry and Robarts Research Institute, University of Western Ontario and Lawson Health Research Institute, London, Ont., Canada
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33
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Davidson M. The debate regarding maintenance treatment with antipsychotic drugs in schizophrenia. DIALOGUES IN CLINICAL NEUROSCIENCE 2019. [PMID: 30581291 PMCID: PMC6296388 DOI: 10.31887/dcns.2018.20.3/mdavidson] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Several large meta-analyses of maintenance trials have confirmed that patients who suffer from chronic schizophrenia, randomized to placebo, are likely to experience earlier symptomatic worsening than patients randomized to a dopamine (DA)-blocking drug. These findings led expert groups to issue treatment guidelines, which recommend treatment with DA-blocking drugs for periods ranging from several years to indefinitely. The recommendations were accepted by the majority of, but not all, the experts, some of whom proposed a targeted or intermittent therapy approach by which DA-blocking drugs are discontinued upon symptomatic remission, to be renewed in case of symptom re-emergence. The debate between continued and targeted treatment approaches arises from disagreements regarding scientific and ethical questions. Scientifically, the discussion focuses on the quality and interpretation of the supporting or detracting evidence regarding each treatment option. For example, what is the percentage of individuals who can maintain stability off drugs? What is the rate of individuals who exacerbate despite maintenance treatment? What is the percentage of individuals who experience drug-related adverse effects? How can we interpret results of open-label, nonrandomized targeted trials? Regarding ethical questions, the debating sides disagree on how to weigh the impact of the decreased risk for exacerbation versus the certainty of adverse effects on the patients quality of life, and how to reach a patient-therapist shared decision within the constraints of mental illness.
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Affiliation(s)
- Michael Davidson
- UniSackler School of Medicine, Tel Aviv, Israel; Nicosia Medical School, Nicosia, Cyprus
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34
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Huhtaniska S, Korkala I, Heikka T, Björnholm L, Lehtiniemi H, Hulkko AP, Moilanen J, Tohka J, Manjón J, Coupé P, Kiviniemi V, Isohanni M, Koponen H, Murray GK, Miettunen J, Jääskeläinen E. Antipsychotic and benzodiazepine use and brain morphology in schizophrenia and affective psychoses - Systematic reviews and birth cohort study. Psychiatry Res Neuroimaging 2018; 281:43-52. [PMID: 30219591 DOI: 10.1016/j.pscychresns.2018.08.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Revised: 08/23/2018] [Accepted: 08/23/2018] [Indexed: 10/28/2022]
Abstract
The aim of this paper was to investigate differences in brain structure volumes between schizophrenia and affective psychoses, and whether cumulative lifetime antipsychotic or benzodiazepine doses relate to brain morphology in these groups. We conducted two systematic reviews on the topic and investigated 44 schizophrenia cases and 19 with affective psychoses from the Northern Finland Birth Cohort 1966. The association between lifetime antipsychotic and benzodiazepine dose and brain MRI scans at the age of 43 was investigated using linear regression. Intracranial volume, sex, illness severity, and antipsychotic/benzodiazepine doses were used as covariates. There were no differences between the groups in brain structure volumes. In schizophrenia, after adjusting for benzodiazepine dose and symptoms, a negative association between lifetime antipsychotic dose and the nucleus accumbens volume remained. In affective psychoses, higher lifetime benzodiazepine dose associated with larger volumes of total gray matter and hippocampal volume after controlling for antipsychotic use and symptoms. It seems that in addition to antipsychotics, the severity of symptoms and benzodiazepine dose are also associated with brain structure volumes. These results suggest, that benzodiazepine effects should also be investigated also independently and not only as a confounder.
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Affiliation(s)
- Sanna Huhtaniska
- Center for Life Course Health Research, University of Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Finland.
| | - Iikka Korkala
- Center for Life Course Health Research, University of Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Finland
| | - Tuomas Heikka
- Center for Life Course Health Research, University of Oulu, Finland
| | - Lassi Björnholm
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Finland
| | - Heli Lehtiniemi
- Center for Life Course Health Research, University of Oulu, Finland
| | - Anja P Hulkko
- Center for Life Course Health Research, University of Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Finland
| | - Jani Moilanen
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Finland
| | - Jussi Tohka
- AI Virtanen Institute for Molecular Sciences, University of Eastern Finland, Finland
| | - José Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Spain
| | - Pierrick Coupé
- Laboratoire Bordelais de Recherche en Informatique, Unité Mixte de Recherche CNRS (UMR 5800), PICTURA Research Group, France
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Oulu University Hospital, Finland
| | - Matti Isohanni
- Center for Life Course Health Research, University of Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Finland; Department of Psychiatry, Oulu University Hospital, Finland
| | - Hannu Koponen
- University of Helsinki, Helsinki University Hospital, Psychiatry, Helsinki, Finland
| | - Graham K Murray
- University of Cambridge, Department of Psychiatry, United Kingdom; University of Cambridge, Behavioural and Clinical Neuroscience Institute, United Kingdom
| | - Jouko Miettunen
- Center for Life Course Health Research, University of Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Finland
| | - Erika Jääskeläinen
- Center for Life Course Health Research, University of Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Finland; Department of Psychiatry, Oulu University Hospital, Finland
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Tarcijonas G, Sarpal DK. Neuroimaging markers of antipsychotic treatment response in schizophrenia: An overview of magnetic resonance imaging studies. Neurobiol Dis 2018; 131:104209. [PMID: 29953933 DOI: 10.1016/j.nbd.2018.06.021] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 05/16/2018] [Accepted: 06/23/2018] [Indexed: 12/18/2022] Open
Abstract
Antipsychotic drugs are the primary treatment for psychosis, yet individual response to their administration remains variable. At present, no biological predictors of response exist to guide clinicians as they select treatments for patients, and our understanding of the neurobiology underlying the heterogeneity of outcomes remains limited. Magnetic Resonance Imaging (MRI) has been applied by numerous studies to examine the response to antipsychotic treatment, though a large gap remains between their results and our clinical practice. To advance patient care with precision medicine approaches, prior work must be accounted for and built upon with future studies. This review provides an overview of studies that relate treatment outcome to various MRI-related measures, including structural, spectroscopic, diffusion tensor, and functional imaging. Knowledge derived from these studies will be discussed along with future directions for the field.
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Affiliation(s)
- Goda Tarcijonas
- University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Deepak K Sarpal
- University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.
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36
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Ostrow L, Jessell L, Hurd M, Darrow SM, Cohen D. Discontinuing Psychiatric Medications: A Survey of Long-Term Users. Psychiatr Serv 2017; 68:1232-1238. [PMID: 28712356 DOI: 10.1176/appi.ps.201700070] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Individuals undergoing long-term psychiatric treatment frequently choose to stop taking psychiatric medications. To enhance service user choice and prevent undesirable outcomes, this first U.S. survey of a large sample of longer-term users sought to increase knowledge about users' experience of medication discontinuation. METHODS A sample of 250 U.S. adults with a diagnosis of serious mental illness and a recent goal to stop up to two prescribed psychiatric medications, which they had taken for at least nine months, completed a web-based survey about experiences, strategies, and supports during discontinuation. RESULTS About half (54%) met their goal of completely discontinuing one or more medications; 46% reported another outcome (use was reduced, use increased, or use stayed the same). Concerns about medications' effects (for example, long-term effects and side effects) prompted the decision to discontinue for 74% of respondents. They used various strategies to cope with withdrawal symptoms, which 54% rated as severe. Self-education and contact with friends and with others who had discontinued or reduced medications were most frequently cited as helpful. Although more than half rated the initial medication decision with prescribers as largely collaborative, only 45% rated prescribers as helpful during discontinuation. Of respondents who completely discontinued, 82% were satisfied with their decision. CONCLUSIONS Discontinuing psychiatric medication appears to be a complicated and difficult process, although most respondents reported satisfaction with their decision. Future research should guide health care systems and providers to better support patient choice and self-determination regarding the use and discontinuation of psychiatric medication.
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Affiliation(s)
- Laysha Ostrow
- Dr. Ostrow is with Live & Learn, Inc., Morro Bay, California. Ms. Jessell is with the Silver School of Social Work, New York University, New York. Mr. Hurd is with Bonita House, Inc., Oakland, California. Dr. Darrow is with the Department of Psychiatry, University of California, San Francisco. Dr. Cohen is with the Department of Social Welfare, Luskin School of Public Affairs, University of California, Los Angeles
| | - Lauren Jessell
- Dr. Ostrow is with Live & Learn, Inc., Morro Bay, California. Ms. Jessell is with the Silver School of Social Work, New York University, New York. Mr. Hurd is with Bonita House, Inc., Oakland, California. Dr. Darrow is with the Department of Psychiatry, University of California, San Francisco. Dr. Cohen is with the Department of Social Welfare, Luskin School of Public Affairs, University of California, Los Angeles
| | - Manton Hurd
- Dr. Ostrow is with Live & Learn, Inc., Morro Bay, California. Ms. Jessell is with the Silver School of Social Work, New York University, New York. Mr. Hurd is with Bonita House, Inc., Oakland, California. Dr. Darrow is with the Department of Psychiatry, University of California, San Francisco. Dr. Cohen is with the Department of Social Welfare, Luskin School of Public Affairs, University of California, Los Angeles
| | - Sabrina M Darrow
- Dr. Ostrow is with Live & Learn, Inc., Morro Bay, California. Ms. Jessell is with the Silver School of Social Work, New York University, New York. Mr. Hurd is with Bonita House, Inc., Oakland, California. Dr. Darrow is with the Department of Psychiatry, University of California, San Francisco. Dr. Cohen is with the Department of Social Welfare, Luskin School of Public Affairs, University of California, Los Angeles
| | - David Cohen
- Dr. Ostrow is with Live & Learn, Inc., Morro Bay, California. Ms. Jessell is with the Silver School of Social Work, New York University, New York. Mr. Hurd is with Bonita House, Inc., Oakland, California. Dr. Darrow is with the Department of Psychiatry, University of California, San Francisco. Dr. Cohen is with the Department of Social Welfare, Luskin School of Public Affairs, University of California, Los Angeles
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Wojtalik JA, Smith MJ, Keshavan MS, Eack SM. A Systematic and Meta-analytic Review of Neural Correlates of Functional Outcome in Schizophrenia. Schizophr Bull 2017; 43:1329-1347. [PMID: 28204755 PMCID: PMC5737663 DOI: 10.1093/schbul/sbx008] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Individuals with schizophrenia are burdened with impairments in functional outcome, despite existing interventions. The lack of understanding of the neurobiological correlates supporting adaptive function in the disorder is a significant barrier to developing more effective treatments. This research conducted a systematic and meta-analytic review of all peer-reviewed studies examining brain-functional outcome relationships in schizophrenia. A total of 53 (37 structural and 16 functional) brain imaging studies examining the neural correlates of functional outcome across 1631 individuals with schizophrenia were identified from literature searches in relevant databases occurring between January, 1968 and December, 2016. Study characteristics and results representing brain-functional outcome relationships were systematically extracted, reviewed, and meta-analyzed. Results indicated that better functional outcome was associated with greater fronto-limbic and whole brain volumes, smaller ventricles, and greater activation, especially during social cognitive processing. Thematic observations revealed that the dorsolateral prefrontal cortex, anterior cingulate, posterior cingulate, parahippocampal gyrus, superior temporal sulcus, and cerebellum may have role in functioning. The neural basis of functional outcome and disability is infrequently studied in schizophrenia. While existing evidence is limited and heterogeneous, these findings suggest that the structural and functional integrity of fronto-limbic brain regions is consistently related to functional outcome in individuals with schizophrenia. Further research is needed to understand the mechanisms and directionality of these relationships, and the potential for identifying neural targets to support functional improvement.
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Affiliation(s)
- Jessica A Wojtalik
- School of Social Work, University of Pittsburgh, Pittsburgh, PA,To whom correspondence should be addressed; School of Social Work, University of Pittsburgh, 2117 Cathedral of Learning, Pittsburgh, PA 15260, US; tel: 412-624-6304, e-mail:
| | - Matthew J Smith
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL
| | | | - Shaun M Eack
- School of Social Work, University of Pittsburgh, Pittsburgh, PA,Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
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38
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Dieleman N, Koek HL, Hendrikse J. Short-term mechanisms influencing volumetric brain dynamics. NEUROIMAGE-CLINICAL 2017; 16:507-513. [PMID: 28971004 PMCID: PMC5609861 DOI: 10.1016/j.nicl.2017.09.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Revised: 07/28/2017] [Accepted: 09/04/2017] [Indexed: 12/14/2022]
Abstract
With the use of magnetic resonance imaging (MRI) and brain analysis tools, it has become possible to measure brain volume changes up to around 0.5%. Besides long-term brain changes caused by atrophy in aging or neurodegenerative disease, short-term mechanisms that influence brain volume may exist. When we focus on short-term changes of the brain, changes may be either physiological or pathological. As such determining the cause of volumetric dynamics of the brain is essential. Additionally for an accurate interpretation of longitudinal brain volume measures by means of neurodegeneration, knowledge about the short-term changes is needed. Therefore, in this review, we discuss the possible mechanisms influencing brain volumes on a short-term basis and set-out a framework of MRI techniques to be used for volumetric changes as well as the used analysis tools. 3D T1-weighted images are the images of choice when it comes to MRI of brain volume. These images are excellent to determine brain volume and can be used together with an analysis tool to determine the degree of volume change. Mechanisms that decrease global brain volume are: fluid restriction, evening MRI measurements, corticosteroids, antipsychotics and short-term effects of pathological processes like Alzheimer's disease, hypertension and Diabetes mellitus type II. Mechanisms increasing the brain volume include fluid intake, morning MRI measurements, surgical revascularization and probably medications like anti-inflammatory drugs and anti-hypertensive medication. Exercise was found to have no effect on brain volume on a short-term basis, which may imply that dehydration caused by exercise differs from dehydration by fluid restriction. In the upcoming years, attention should be directed towards studies investigating physiological short-term changes within the light of long-term pathological changes. Ultimately this may lead to a better understanding of the physiological short-term effects of pathological processes and may aid in early detection of these diseases. Fluid-restriction, evening MRI, corticosteroids, & antipsychotics decrease volume Fluid-intake, morning MRI, surgical revascularization & medications increase volume Short-term changes within the light of long-term pathological changes should be investigated Short-term changes may introduce bias in longitudinal data
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Affiliation(s)
- Nikki Dieleman
- Department of Radiology, University Medical Center Utrecht, The Netherlands
| | - Huiberdina L Koek
- Department of Geriatrics, University Medical Center Utrecht, The Netherlands
| | - Jeroen Hendrikse
- Department of Radiology, University Medical Center Utrecht, The Netherlands
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39
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Emsley R, Asmal L, du Plessis S, Chiliza B, Phahladira L, Kilian S. Brain volume changes over the first year of treatment in schizophrenia: relationships to antipsychotic treatment. Psychol Med 2017; 47:2187-2196. [PMID: 28347393 DOI: 10.1017/s0033291717000642] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
BACKGROUND Progressive brain volume reductions have been described in schizophrenia, and an association with antipsychotic exposure has been reported. METHODS We compared percentage changes in grey and white matter volume from baseline to month 12 in 23 previously antipsychotic-naïve patients with a first episode of schizophrenia or schizophreniform disorder who were treated with the lowest effective dose of flupenthixol decanoate depot formulation, with 53 matched healthy individuals. Total antipsychotic dose was precisely calculated and its relationship with brain volume changes investigated. Relationships between volumetric changes and treatment were further investigated in terms of treatment response (changes in psychopathology and functionality) and treatment-related adverse-events (extrapyramidal symptoms and weight gain). RESULTS Excessive cortical volume reductions were observed in patients [-4.6 (6.6)%] v. controls [-1.12 (4.0)%] (p = 0.009), with no significant group differences for changes in subcortical grey matter and white matter volumes. In a multiple regression model, the only significant predictor of cortical volume change was total antipsychotic dose received (p = 0.04). Cortical volume change was not significantly associated with the changes in psychopathology, functionality, extrapyramidal symptoms and body mass index or age, gender and duration of untreated psychosis. CONCLUSIONS Brain volume reductions associated with antipsychotic treatment are not restricted to poor outcome patients and occur even with the lowest effective dose of antipsychotic. The lack of an association with poor treatment response or treatment-related adverse effects counts against cortical volume reductions reflecting neurotoxicity, at least in the short term. On the other hand, the volume reductions were not linked to the therapeutic benefits of antipsychotics.
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Affiliation(s)
- R Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences,Stellenbosch University,Cape Town,South Africa
| | - L Asmal
- Department of Psychiatry, Faculty of Medicine and Health Sciences,Stellenbosch University,Cape Town,South Africa
| | - S du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences,Stellenbosch University,Cape Town,South Africa
| | - B Chiliza
- Department of Psychiatry, Faculty of Medicine and Health Sciences,Stellenbosch University,Cape Town,South Africa
| | - L Phahladira
- Department of Psychiatry, Faculty of Medicine and Health Sciences,Stellenbosch University,Cape Town,South Africa
| | - S Kilian
- Department of Psychiatry, Faculty of Medicine and Health Sciences,Stellenbosch University,Cape Town,South Africa
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40
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Huhtaniska S, Jääskeläinen E, Heikka T, Moilanen JS, Lehtiniemi H, Tohka J, Manjón JV, Coupé P, Björnholm L, Koponen H, Veijola J, Isohanni M, Kiviniemi V, Murray GK, Miettunen J. Long-term antipsychotic and benzodiazepine use and brain volume changes in schizophrenia: The Northern Finland Birth Cohort 1966 study. Psychiatry Res Neuroimaging 2017; 266:73-82. [PMID: 28618327 DOI: 10.1016/j.pscychresns.2017.05.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Revised: 05/12/2017] [Accepted: 05/19/2017] [Indexed: 11/22/2022]
Abstract
High doses of antipsychotics have been associated with loss in cortical and total gray matter in schizophrenia. However, previous imaging studies have not taken benzodiazepine use into account, in spite of evidence suggesting adverse effects such as cognitive impairment and increased mortality. In this Northern Finland Birth Cohort 1966 study, 69 controls and 38 individuals with schizophrenia underwent brain MRI at the ages of 34 and 43 years. At baseline, the average illness duration was over 10 years. Brain structures were delineated using an automated volumetry system, volBrain, and medication data on cumulative antipsychotic and benzodiazepine doses were collected using medical records and interviews. We used linear regression with intracranial volume and sex as covariates; illness severity was also taken into account. Though both medication doses associated to volumetric changes in subcortical structures, after adjusting for each other and the average PANSS total score, higher scan-interval antipsychotic dose associated only to volume increase in lateral ventricles and higher benzodiazepine dose associated with volume decrease in the caudate nucleus. To our knowledge, there are no previous studies reporting associations between benzodiazepine dose and brain structural changes. Further studies should focus on how these observations correspond to cognition and functioning.
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Affiliation(s)
- Sanna Huhtaniska
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland.
| | - Erika Jääskeläinen
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Oulu University Hospital, P.O. Box 26, FIN-90029 Oulu, Finland
| | - Tuomas Heikka
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland
| | - Jani S Moilanen
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Oulu University Hospital, P.O. Box 26, FIN-90029 Oulu, Finland
| | - Heli Lehtiniemi
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, FIN-70211 Kuopio, Finland
| | - José V Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Pierrick Coupé
- Laboratoire Bordelais de Recherche en Informatique, Unité Mixte de Recherche CNRS (UMR 5800), PICTURA Research Group, France
| | - Lassi Björnholm
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland
| | - Hannu Koponen
- Department of Psychiatry, University of Helsinki and Helsinki University Hospital, P.O. Box 22, University of Helsinki, Finland
| | - Juha Veijola
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Oulu University Hospital, P.O. Box 26, FIN-90029 Oulu, Finland
| | - Matti Isohanni
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Oulu University Hospital, P.O. Box 26, FIN-90029 Oulu, Finland
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Oulu University Hospital, P.O. Box 50, FIN-90029 Oulu, Finland
| | - Graham K Murray
- Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Box 189, Cambridge CB2 2QQ, UK; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Site, Cambridge CB2 3EB, UK
| | - Jouko Miettunen
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland; Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, P.O. Box 5000, FIN-90014 Oulu, Finland
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Progressive cortical reorganisation: A framework for investigating structural changes in schizophrenia. Neurosci Biobehav Rev 2017; 79:1-13. [DOI: 10.1016/j.neubiorev.2017.04.028] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Revised: 04/26/2017] [Accepted: 04/26/2017] [Indexed: 12/27/2022]
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Dietsche B, Kircher T, Falkenberg I. Structural brain changes in schizophrenia at different stages of the illness: A selective review of longitudinal magnetic resonance imaging studies. Aust N Z J Psychiatry 2017; 51:500-508. [PMID: 28415873 DOI: 10.1177/0004867417699473] [Citation(s) in RCA: 135] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Schizophrenia is a devastating mental disorder accompanied by aberrant structural brain connectivity. The question whether schizophrenia is a progressive brain disorder is yet to be resolved. Thus, it is not clear when these structural alterations occur and how they develop over time. METHODS In our selective review, we summarized recent findings from longitudinal magnetic resonance imaging studies investigating structural brain alterations and its impact on clinical outcome at different stages of the illness: (1) subjects at ultra-high risk of developing psychosis, (2) patients with a first episode psychosis, and (3) chronically ill patients. Moreover, we reviewed studies examining the longitudinal effects of medication on brain structure in patients with schizophrenia. RESULTS (1) Studies from pre-clinical stages to conversion showed a more pronounced cortical gray matter loss (i.e. superior temporal and inferior frontal regions) in those individuals who later made transition to psychosis. (2) Studies investigating patients with a first episode psychosis revealed a decline in multiple gray matter regions (i.e. frontal regions and thalamus) over time as well as progressive cortical thinning in the superior and inferior frontal cortex. (3) Studies focusing on patients with chronic schizophrenia showed that gray matter decreased to a greater extent (i.e. frontal and temporal areas, thalamus, and cingulate cortices)-especially in poor-outcome patients. Very few studies reported effects on white matter microstructure in the longitudinal course of the illness. CONCLUSION There is adequate evidence to suggest that schizophrenia is associated with progressive gray matter abnormalities particularly during the initial stages of illness. However, causal relationships between structural changes and illness course-especially in chronically ill patients-should be interpreted with caution. Findings might be confounded by longer periods of treatment and higher doses of antipsychotics or epiphenomena related to the illness.
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Affiliation(s)
- Bruno Dietsche
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Irina Falkenberg
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
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Neuroadaptations to antipsychotic drugs: Insights from pre-clinical and human post-mortem studies. Neurosci Biobehav Rev 2017; 76:317-335. [DOI: 10.1016/j.neubiorev.2016.10.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Revised: 07/07/2016] [Accepted: 10/06/2016] [Indexed: 12/21/2022]
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Huhtaniska S, Jääskeläinen E, Hirvonen N, Remes J, Murray GK, Veijola J, Isohanni M, Miettunen J. Long-term antipsychotic use and brain changes in schizophrenia - a systematic review and meta-analysis. Hum Psychopharmacol 2017; 32. [PMID: 28370309 DOI: 10.1002/hup.2574] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Revised: 01/13/2017] [Accepted: 01/28/2017] [Indexed: 01/03/2023]
Abstract
OBJECTIVE The association between long-term antipsychotic treatment and changes in brain structure in schizophrenia is unclear. Our aim was to conduct a systematic review and a meta-analysis on long-term antipsychotic effects on brain structures in schizophrenia focusing on studies with at least 2 years of follow-up between MRI scans. DESIGN Studies were systematically collected using 4 databases, and we also contacted authors for unpublished data. We calculated correlations between antipsychotic dose and/or type and brain volumetric changes and used random effect meta-analysis to study correlations by brain area. RESULTS Thirty-one publications from 16 samples fulfilled our inclusion criteria. In meta-analysis, higher antipsychotic exposure associated statistically significantly with parietal lobe decrease (studies, n = 4; r = -.14, p = .013) and with basal ganglia increase (n = 4; r = .10, p = .044). Most of the reported correlations in the original studies were statistically nonsignificant. There were no clear differences between typical and atypical exposure and brain volume change. The studies were often small and highly heterogeneous in their methods and seldom focused on antipsychotic medication and brain changes as the main subject. CONCLUSIONS Antipsychotic medication may associate with brain structure changes. More long-term follow-up studies taking into account illness severity measures are needed to make definitive conclusions.
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Affiliation(s)
- Sanna Huhtaniska
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.,Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland
| | - Erika Jääskeläinen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.,Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland.,Department of Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Noora Hirvonen
- Information Studies, Faculty of Humanities, University of Oulu, Oulu, Finland
| | - Jukka Remes
- Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Graham K Murray
- Department of Psychiatry, University of Cambridge, Cambridge, UK.,Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Juha Veijola
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.,Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland.,Department of Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Matti Isohanni
- Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland.,Department of Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Jouko Miettunen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.,Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland.,Department of Psychiatry, Oulu University Hospital, Oulu, Finland
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45
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Maric NP, Jovicic MJ, Mihaljevic M, Miljevic C. Improving Current Treatments for Schizophrenia. Drug Dev Res 2016; 77:357-367. [DOI: 10.1002/ddr.21337] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Nadja P. Maric
- School of Medicine; University of Belgrade; Belgrade Serbia
- Clinical Centre of Serbia; Clinic for Psychiatry; Belgrade Serbia
| | | | | | - Cedo Miljevic
- School of Medicine; University of Belgrade; Belgrade Serbia
- Institute of Mental Health; Belgrade Serbia
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46
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Torres US, Duran FLS, Schaufelberger MS, Crippa JAS, Louzã MR, Sallet PC, Kanegusuku CYO, Elkis H, Gattaz WF, Bassitt DP, Zuardi AW, Hallak JEC, Leite CC, Castro CC, Santos AC, Murray RM, Busatto GF. Patterns of regional gray matter loss at different stages of schizophrenia: A multisite, cross-sectional VBM study in first-episode and chronic illness. NEUROIMAGE-CLINICAL 2016; 12:1-15. [PMID: 27354958 PMCID: PMC4910144 DOI: 10.1016/j.nicl.2016.06.002] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 05/27/2016] [Accepted: 06/02/2016] [Indexed: 12/17/2022]
Abstract
Background: Structural brain abnormalities in schizophrenia have been repeatedly demonstrated in magnetic resonance imaging (MRI) studies, but it remains unclear whether these are static or progressive in nature. While longitudinal MRI studies have been traditionally used to assess the issue of progression of brain abnormalities in schizophrenia, information from cross-sectional neuroimaging studies directly comparing first-episode and chronic schizophrenia patients to healthy controls may also be useful to further clarify this issue. With the recent interest in multisite mega-analyses combining structural MRI data from multiple centers aiming at increased statistical power, the present multisite voxel-based morphometry (VBM) study was carried out to examine patterns of brain structural changes according to the different stages of illness and to ascertain which (if any) of such structural abnormalities would be specifically correlated to potential clinical moderators, including cumulative exposure to antipsychotics, age of onset, illness duration and overall illness severity. Methods: We gathered a large sample of schizophrenia patients (161, being 99 chronic and 62 first-episode) and controls (151) from four previous morphometric MRI studies (1.5 T) carried out in the same geographical region of Brazil. Image processing and analyses were conducted using Statistical Parametric Mapping (SPM8) software with the diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) algorithm. Group effects on regional gray matter (GM) volumes were investigated through whole-brain voxel-wise comparisons using General Linear Model Analysis of Co-variance (ANCOVA), always including total GM volume, scan protocol, age and gender as nuisance variables. Finally, correlation analyses were performed between the aforementioned clinical moderators and regional and global brain volumes. Results: First-episode schizophrenia subjects displayed subtle volumetric deficits relative to controls in a circumscribed brain regional network identified only in small volume-corrected (SVC) analyses (p < 0.05, FWE-corrected), including the insula, temporolimbic structures and striatum. Chronic schizophrenia patients, on the other hand, demonstrated an extensive pattern of regional GM volume decreases relative to controls, involving bilateral superior, inferior and orbital frontal cortices, right middle frontal cortex, bilateral anterior cingulate cortices, bilateral insulae and right superior and middle temporal cortices (p < 0.05, FWE-corrected over the whole brain). GM volumes in several of those brain regions were directly correlated with age of disease onset on SVC analyses for conjoined (first-episode and chronic) schizophrenia groups. There were also widespread foci of significant negative correlation between duration of illness and relative GM volumes, but such findings remained significant only for the right dorsolateral prefrontal cortex after accounting for the influence of age of disease onset. Finally, significant negative correlations were detected between life-time cumulative exposure to antipsychotics and total GM and white matter volumes in schizophrenia patients, but no significant relationship was found between indices of antipsychotic usage and relative GM volume in any specific brain region. Conclusion: The above data indicate that brain changes associated with the diagnosis of schizophrenia are more widespread in chronic schizophrenia compared to first-episode patients. Our findings also suggest that relative GM volume deficits may be greater in (presumably more severe) cases with earlier age of onset, as well as varying as a function of illness duration in specific frontal brain regions. Finally, our results highlight the potentially complex effects of the continued use of antipsychotic drugs on structural brain abnormalities in schizophrenia, as we found that cumulative doses of antipsychotics affected brain volumes globally rather than selectively on frontal-temporal regions. Structural brain changes are more widespread in chronic than first-episode schizophrenia. Regional GM deficits may be greater in cases with earlier age of onset. Illness duration seems to impact in some specific frontal structural brain changes. Antipsychotics seem to affect brain volumes globally rather than regionally.
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Affiliation(s)
- Ulysses S Torres
- Post-Graduation Program in Radiology, Institute of Radiology (INRAD), Faculty of Medicine, University of São Paulo, Brazil; Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil
| | - Fabio L S Duran
- Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil
| | - Maristela S Schaufelberger
- Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department of Neuroscience and Behaviour, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - José A S Crippa
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department of Neuroscience and Behaviour, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Mario R Louzã
- Department and Institute of Psychiatry, University of Sao Paulo Medical School, Brazil
| | - Paulo C Sallet
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department and Institute of Psychiatry, University of Sao Paulo Medical School, Brazil
| | | | - Helio Elkis
- Department and Institute of Psychiatry, University of Sao Paulo Medical School, Brazil
| | - Wagner F Gattaz
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department and Institute of Psychiatry, University of Sao Paulo Medical School, Brazil; Laboratory of Neuroscience (LIM 27), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, Brazil
| | - Débora P Bassitt
- Department and Institute of Psychiatry, University of Sao Paulo Medical School, Brazil
| | - Antonio W Zuardi
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department of Neuroscience and Behaviour, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Jaime Eduardo C Hallak
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department of Neuroscience and Behaviour, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Claudia C Leite
- Post-Graduation Program in Radiology, Institute of Radiology (INRAD), Faculty of Medicine, University of São Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil
| | - Claudio C Castro
- Post-Graduation Program in Radiology, Institute of Radiology (INRAD), Faculty of Medicine, University of São Paulo, Brazil; Department of Diagnostic Imaging, Heart Institute (InCor), Faculty of Medicine, University of São Paulo, Brazil
| | - Antonio Carlos Santos
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department of Internal Medicine - Radiology Division, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, King's College London, UK
| | - Geraldo F Busatto
- Post-Graduation Program in Radiology, Institute of Radiology (INRAD), Faculty of Medicine, University of São Paulo, Brazil; Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Brazil; Department and Institute of Psychiatry, University of Sao Paulo Medical School, Brazil
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