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Read J. What is helpful and unhelpful when people try to withdraw from antipsychotics: An international survey. Psychol Psychother 2024; 97:665-685. [PMID: 39445669 DOI: 10.1111/papt.12551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 09/26/2024] [Indexed: 10/25/2024]
Abstract
OBJECTIVE Antipsychotics remain the first-line treatment for people diagnosed with psychotic disorders despite adverse effects which lead many people to stop their medication. Many stop without the support of the prescriber, who may fear relapse. The objective of this study is to better understand the process of withdrawal from antipsychotics, from the perspective of people taking antipsychotics. DESIGN Online survey. METHODS An international online survey elicited quantitative responses about pre-withdrawal planning (560) and qualitative responses about what was helpful and unhelpful when withdrawing from antipsychotics (443). Responses came from users of antipsychotics in 29 countries. RESULTS Forty-seven per cent did not consult their psychiatrist before discontinuing. Only 40% made preparations, most commonly making a plan, gathering information and informing family. The most frequently reported helpful factors were focussing on the benefits of getting off the drugs (including ending adverse effects and feeling more alive), information about withdrawal symptoms and how to withdraw safely, withdrawing slowly, and support from psychologists, counsellors and psychotherapists. The most common unhelpful factor was the psychiatrist/doctor, largely because of their lack of knowledge, refusal to support the patient's wishes and the threat or use of coercion. CONCLUSIONS Evidence-based, respectful, collaborative responses to patients' concerns about adverse effects and desires to withdraw would probably reduce relapse rates and improve long-term outcomes. It would definitely help end pervasive breaching of the principle of informed consent and human rights legislation.
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Affiliation(s)
- John Read
- School of Psychology, University of East London, London, UK
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2
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Cho KIK, Zhang F, Penzel N, Seitz-Holland J, Tang Y, Zhang T, Xu L, Li H, Keshavan M, Whitfield-Gabrieli S, Niznikiewicz M, Stone WS, Wang J, Shenton ME, Pasternak O. Excessive interstitial free-water in cortical gray matter preceding accelerated volume changes in individuals at clinical high risk for psychosis. Mol Psychiatry 2024; 29:3623-3634. [PMID: 38830974 DOI: 10.1038/s41380-024-02597-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 05/01/2024] [Accepted: 05/03/2024] [Indexed: 06/05/2024]
Abstract
Recent studies show that accelerated cortical gray matter (GM) volume reduction seen in anatomical MRI can help distinguish between individuals at clinical high risk (CHR) for psychosis who will develop psychosis and those who will not. This reduction is suggested to represent atypical developmental or degenerative changes accompanying an accumulation of microstructural changes, such as decreased spine density and dendritic arborization. Detecting the microstructural sources of these changes before they accumulate into volume loss is crucial. Our study aimed to detect these microstructural GM alterations using diffusion MRI (dMRI). We tested for baseline and longitudinal group differences in anatomical and dMRI data from 160 individuals at CHR and 96 healthy controls (HC) acquired in a single imaging site. Of the CHR individuals, 33 developed psychosis (CHR-P), while 127 did not (CHR-NP). Among all participants, longitudinal data was available for 45 HCs, 17 CHR-P, and 66 CHR-NP. Eight cortical lobes were examined for GM volume and GM microstructure. A novel dMRI measure, interstitial free water (iFW), was used to quantify GM microstructure by eliminating cerebrospinal fluid contribution. Additionally, we assessed whether these measures differentiated the CHR-P from the CHR-NP. In addition, for completeness, we also investigated changes in cortical thickness and in white matter (WM) microstructure. At baseline the CHR group had significantly higher iFW than HC in the prefrontal, temporal, parietal, and occipital lobes, while volume was reduced only in the temporal lobe. Neither iFW nor volume differentiated between the CHR-P and CHR-NP groups at baseline. However, in many brain areas, the CHR-P group demonstrated significantly accelerated changes (iFW increase and volume reduction) with time than the CHR-NP group. Cortical thickness provided similar results as volume, and there were no significant changes in WM microstructure. Our results demonstrate that microstructural GM changes in individuals at CHR have a wider extent than volumetric changes or microstructural WM changes, and they predate the acceleration of brain changes that occur around psychosis onset. Microstructural GM changes, as reflected by the increased iFW, are thus an early pathology at the prodromal stage of psychosis that may be useful for a better mechanistic understanding of psychosis development.
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Affiliation(s)
- Kang Ik K Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nora Penzel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
| | - Huijun Li
- Department of Psychology, Florida A&M University, Tallahassee, FL, USA
| | - Matcheri Keshavan
- The Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Harvard Medical School, Boston, MA, USA
| | - Susan Whitfield-Gabrieli
- Department of Psychology, Northeastern University, Boston, MA, USA
- The McGovern Institute for Brain Research and the Poitras Center for Affective Disorders Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Margaret Niznikiewicz
- The Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - William S Stone
- The Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Harvard Medical School, Boston, MA, USA
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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3
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Leucht S, Priller J, Davis JM. Antipsychotic Drugs: A Concise Review of History, Classification, Indications, Mechanism, Efficacy, Side Effects, Dosing, and Clinical Application. Am J Psychiatry 2024; 181:865-878. [PMID: 39350614 DOI: 10.1176/appi.ajp.20240738] [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: 10/23/2024]
Abstract
The introduction of the first antipsychotic drug, chlorpromazine, was a milestone for psychiatry. The authors review the history, classification, indications, mechanism, efficacy, side effects, dosing, drug initiation, switching, and other practical issues and questions related to antipsychotics. Classifications such as first-generation/typical versus second-generation/atypical antipsychotics are neither valid nor useful; these agents should be described according to the Neuroscience-based Nomenclature (NbN). Antipsychotic drugs are not specific for treating schizophrenia. They reduce psychosis regardless of the underlying diagnosis, and they go beyond nonspecific sedation. All currently available antipsychotic drugs are dopamine blockers or dopamine partial agonists. In schizophrenia, effect sizes for relapse prevention are larger than for acute treatment. A major unresolved problem is the implausible increase in placebo response in antipsychotic drug trials over the decades. Differences in side effects, which can be objectively measured, such as weight gain, are less equivocal than differences in rating-scale-measured (subjective) efficacy. The criteria for choosing among antipsychotics are mainly pragmatic and include factors such as available formulations, metabolism, half-life, efficacy, and side effects in previous illness episodes. Plasma levels help to detect nonadherence, and once-daily dosing at night (which is possible with many antipsychotics) and long-acting injectable formulations are useful when adherence is a problem. Dose-response curves for both acute treatment and relapse prevention follow a hyperbolic pattern, with maximally efficacious average dosages for schizophrenia of around 5 mg/day risperidone equivalents. Computer apps facilitating the choice between drugs are available. Future drug development should include pharmacogenetics and focus on drugs for specific aspects of psychosis.
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Affiliation(s)
- Stefan Leucht
- Technical University of Munich, TUM School of Medicine and Health, Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Munich (Leucht, Priller); German Center for Mental Health, Munich (Leucht, Priller); Neuropsychiatry, Charité-Universitätsmedizin Berlin, and German Center for Neurodegenerative Disorders, Berlin (Priller); University of Edinburgh and UK Dementia Research Institute, Edinburgh (Priller); Department of Psychiatry, University of Illinois at Chicago (Davis)
| | - Josef Priller
- Technical University of Munich, TUM School of Medicine and Health, Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Munich (Leucht, Priller); German Center for Mental Health, Munich (Leucht, Priller); Neuropsychiatry, Charité-Universitätsmedizin Berlin, and German Center for Neurodegenerative Disorders, Berlin (Priller); University of Edinburgh and UK Dementia Research Institute, Edinburgh (Priller); Department of Psychiatry, University of Illinois at Chicago (Davis)
| | - John M Davis
- Technical University of Munich, TUM School of Medicine and Health, Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Munich (Leucht, Priller); German Center for Mental Health, Munich (Leucht, Priller); Neuropsychiatry, Charité-Universitätsmedizin Berlin, and German Center for Neurodegenerative Disorders, Berlin (Priller); University of Edinburgh and UK Dementia Research Institute, Edinburgh (Priller); Department of Psychiatry, University of Illinois at Chicago (Davis)
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4
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Di Camillo F, Grimaldi DA, Cattarinussi G, Di Giorgio A, Locatelli C, Khuntia A, Enrico P, Brambilla P, Koutsouleris N, Sambataro F. Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis. Psychiatry Clin Neurosci 2024. [PMID: 39290174 DOI: 10.1111/pcn.13736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 07/31/2024] [Accepted: 08/19/2024] [Indexed: 09/19/2024]
Abstract
BACKGROUND Recent advances in multivariate pattern recognition have fostered the search for reliable neuroimaging-based biomarkers in psychiatric conditions, including schizophrenia. These approaches consider the complex pattern of alterations in brain function and structure, overcoming the limitations of traditional univariate methods. To assess the reliability of neuroimaging-based biomarkers and the contribution of study characteristics in distinguishing individuals with schizophrenia spectrum disorder (SSD) from healthy controls (HCs), we conducted a systematic review of the studies that used multivariate pattern recognition for this objective. METHODS We systematically searched PubMed, Scopus, and Web of Science for studies on SSD classification using multivariate pattern analysis on magnetic resonance imaging data. We employed a bivariate random-effects meta-analytic model to explore the classification of sensitivity (SE) and specificity (SP) across studies while also evaluating the moderator effects of clinical and non-clinical variables. RESULTS A total of 119 studies (with 12,723 patients with SSD and 13,196 HCs) were identified. The meta-analysis estimated a SE of 79.1% (95% confidence interval [CI], 77.1%-81.0%) and a SP of 80.0% (95% CI, 77.8%-82.0%). In particular, the Positive and Negative Syndrome Scale and the Global Assessment of Functioning scores, age, age of onset, duration of untreated psychosis, deep learning, algorithm type, features selection, and validation methods had significant effects on classification performance. CONCLUSIONS Multivariate pattern analysis reliably identifies neuroimaging-based biomarkers of SSD, achieving ∼80% SE and SP. Despite clinical heterogeneity, discernible brain modifications effectively differentiate SSD from HCs. Classification performance depends on patient-related and methodological factors crucial for the development, validation, and application of prospective models in clinical settings.
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Affiliation(s)
- Fabio Di Camillo
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | | | - Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Annabella Di Giorgio
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Clara Locatelli
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Adyasha Khuntia
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
- Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Paolo Enrico
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Department of Neurosciences and Mental Health, Fondazione IRCSS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Department of Neurosciences and Mental Health, Fondazione IRCSS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Nikolaos Koutsouleris
- Max-Planck-Institute of Psychiatry, Munich, Germany
- Department of Psychiatry, Munich University Hospital, Munich, Germany
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
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5
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Tang B, Yao L, Strawn JR, Zhang W, Lui S. Neurostructural, Neurofunctional, and Clinical Features of Chronic, Untreated Schizophrenia: A Narrative Review. Schizophr Bull 2024:sbae152. [PMID: 39212651 DOI: 10.1093/schbul/sbae152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Studies of individuals with chronic, untreated schizophrenia (CUS) can provide important insights into the natural course of schizophrenia and how antipsychotic pharmacotherapy affects neurobiological aspects of illness course and progression. We systematically review 17 studies on the neuroimaging, cognitive, and epidemiological aspects of CUS individuals. These studies were conducted at the Shanghai Mental Health Center, Institute of Mental Health at Peking University, and Huaxi MR Research Center between 2013 and 2021. CUS is associated with cognitive impairment, severe symptoms, and specific demographic characteristics and is different significantly from those observed in antipsychotic-treated individuals. Furthermore, CUS individuals have neurostructural and neurofunctional alterations in frontal and temporal regions, corpus callosum, subcortical, and visual processing areas, as well as default-mode and somatomotor networks. As the disease progresses, significant structural deteriorations occur, such as accelerated cortical thinning in frontal and temporal lobes, greater reduction in fractional anisotropy in the genu of corpus callosum, and decline in nodal metrics of gray mater network in thalamus, correlating with worsening cognitive deficits and clinical outcomes. In addition, striatal hypertrophy also occurs, independent of antipsychotic treatment. Contrasting with the negative neurostructural and neurofunctional effects of short-term antipsychotic treatment, long-term therapy frequently results in significant improvements. It notably enhances white matter integrity and the functions of key subcortical regions such as the amygdala, hippocampus, and striatum, potentially improving cognitive functions. This narrative review highlights the progressive neurobiological sequelae of CUS, the importance of early detection, and long-term treatment of schizophrenia, particularly because treatment may attenuate neurobiological deterioration and improve clinical outcomes.
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Affiliation(s)
- Biqiu Tang
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | - Li Yao
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jeffrey R Strawn
- Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | - Wenjing Zhang
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Su Lui
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
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Male AG, Goudzwaard E, Nakahara S, Turner JA, Calhoun VD, Mueller BA, Lim KO, Bustillo JR, Belger A, Voyvodic J, O'Leary D, Mathalon DH, Ford JM, Potkin SG, Preda A, van Erp TGM. Structural white matter abnormalities in Schizophrenia and associations with neurocognitive performance and symptom severity. Psychiatry Res Neuroimaging 2024; 342:111843. [PMID: 38896909 DOI: 10.1016/j.pscychresns.2024.111843] [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: 03/12/2024] [Revised: 05/25/2024] [Accepted: 06/04/2024] [Indexed: 06/21/2024]
Abstract
Schizophrenia is associated with robust white matter (WM) abnormalities but influences of potentially confounding variables and relationships with cognitive performance and symptom severity remain to be fully determined. This study was designed to evaluate WM abnormalities based on diffusion tensor imaging (DTI) in individuals with schizophrenia, and their relationships with cognitive performance and symptom severity. Data from individuals with schizophrenia (SZ; n=138, mean age±SD=39.02±11.82; 105 males) and healthy controls (HC; n=143, mean age±SD=37.07±10.84; 102 males) were collected as part of the Function Biomedical Informatics Research Network Phase 3 study. Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were compared between individuals with schizophrenia and healthy controls, and their relationships with neurocognitive performance and symptomatology assessed. Individuals with SZ had significantly lower FA in forceps minor and the left inferior fronto-occipital fasciculus compared to HC. FA in several tracts were associated with speed of processing and attention/vigilance and the severity of the negative symptom alogia. This study suggests that regional WM abnormalities are fundamentally involved in the pathophysiology of schizophrenia and may contribute to cognitive performance deficits and symptom expression observed in schizophrenia.
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Affiliation(s)
- Alie G Male
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617, USA
| | - Esther Goudzwaard
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617, USA; University of Amsterdam, Amsterdam 1000 GG, The Netherlands
| | - Soichiro Nakahara
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617, USA; Discovery Accelerator Venture Unit Direct Reprogramming, Astellas Pharma Inc., 21 Miyukigaoka, Tsukuba, Ibaraki 305-8585, Japan
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Vince D Calhoun
- Departments of Psychology and Neuroscience, Georgia State University, Atlanta, GA 30302, USA; Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA 30303, USA
| | - Bryon A Mueller
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN 55454, USA
| | - Kelvin O Lim
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN 55454, USA
| | - Juan R Bustillo
- Departments of Psychiatry & Neuroscience, University of New Mexico, Albuquerque, NM 87131, USA
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - James Voyvodic
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, USA
| | - Daniel O'Leary
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA
| | - Daniel H Mathalon
- Department of Psychiatry, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA; Veterans Affairs San Francisco Healthcare System, San Francisco, CA 94121, USA
| | - Judith M Ford
- Department of Psychiatry, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA; Veterans Affairs San Francisco Healthcare System, San Francisco, CA 94121, USA
| | - Steven G Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617, USA; Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA 92697, USA.
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7
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Kim WS, Heo DW, Maeng J, Shen J, Tsogt U, Odkhuu S, Zhang X, Cheraghi S, Kim SW, Ham BJ, Rami FZ, Sui J, Kang CY, Suk HI, Chung YC. Deep Learning-based Brain Age Prediction in Patients With Schizophrenia Spectrum Disorders. Schizophr Bull 2024; 50:804-814. [PMID: 38085061 PMCID: PMC11283195 DOI: 10.1093/schbul/sbad167] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/29/2024]
Abstract
BACKGROUND AND HYPOTHESIS The brain-predicted age difference (brain-PAD) may serve as a biomarker for neurodegeneration. We investigated the brain-PAD in patients with schizophrenia (SCZ), first-episode schizophrenia spectrum disorders (FE-SSDs), and treatment-resistant schizophrenia (TRS) using structural magnetic resonance imaging (sMRI). STUDY DESIGN We employed a convolutional network-based regression (SFCNR), and compared its performance with models based on three machine learning (ML) algorithms. We pretrained the SFCNR with sMRI data of 7590 healthy controls (HCs) selected from the UK Biobank. The parameters of the pretrained model were transferred to the next training phase with a new set of HCs (n = 541). The brain-PAD was analyzed in independent HCs (n = 209) and patients (n = 233). Correlations between the brain-PAD and clinical measures were investigated. STUDY RESULTS The SFCNR model outperformed three commonly used ML models. Advanced brain aging was observed in patients with SCZ, FE-SSDs, and TRS compared to HCs. A significant difference in brain-PAD was observed between FE-SSDs and TRS with ridge regression but not with the SFCNR model. Chlorpromazine equivalent dose and cognitive function were correlated with the brain-PAD in SCZ and FE-SSDs. CONCLUSIONS Our findings indicate that there is advanced brain aging in patients with SCZ and higher brain-PAD in SCZ can be used as a surrogate marker for cognitive dysfunction. These findings warrant further investigations on the causes of advanced brain age in SCZ. In addition, possible psychosocial and pharmacological interventions targeting brain health should be considered in early-stage SCZ patients with advanced brain age.
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Affiliation(s)
- Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Da-Woon Heo
- Department of Artificial Intelligence, Korea University, Seoul, Korea
| | - Junyeong Maeng
- Department of Artificial Intelligence, Korea University, Seoul, Korea
| | - Jie Shen
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Yanbian University, Medical School, Yanji, China
| | - Uyanga Tsogt
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Soyolsaikhan Odkhuu
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Xuefeng Zhang
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Sahar Cheraghi
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Sung-Wan Kim
- Department of Psychiatry, Chonnam National University Medical School, Gwangju, Korea
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Fatima Zahra Rami
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Chae Yeong Kang
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Heung-Il Suk
- Department of Artificial Intelligence, Korea University, Seoul, Korea
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
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8
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Uyar Demir A, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Van Rheenen TE, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos SI, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TGM, Cheng W, Feng J. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm. Nat Commun 2024; 15:5996. [PMID: 39013848 PMCID: PMC11252381 DOI: 10.1038/s41467-024-50267-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 07/03/2024] [Indexed: 07/18/2024] Open
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Magdeburg, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, SYD, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, SYD, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Min Tae M Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, TO, Canada
- Centre for Addiction and Mental Health, TO, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, MEL, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- School of Data Science, Fudan University, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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9
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Torres-Carmona E, Ueno F, Iwata Y, Nakajima S, Song J, Mar W, Abdolizadeh A, Agarwal SM, de Luca V, Remington G, Gerretsen P, Graff-Guerrero A. Elevated intrinsic cortical curvature in treatment-resistant schizophrenia: Evidence of structural deformation in functional connectivity areas and comparison with alternate indices of structure. Schizophr Res 2024; 269:103-113. [PMID: 38761434 DOI: 10.1016/j.schres.2024.05.002] [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: 11/17/2023] [Revised: 04/14/2024] [Accepted: 05/02/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Research suggests structural and connectivity abnormalities in patients with treatment-resistant schizophrenia (TRS) compared to first-line responders and healthy-controls. However, measures of these abnormalities are often influenced by external factors like nicotine and antipsychotics, limiting their clinical utility. Intrinsic-cortical-curvature (ICC) presents a millimetre-scale measure of brain gyrification, highly sensitive to schizophrenia differences, and associated with TRS-like traits in early stages of the disorder. Despite this evidence, ICC in TRS remains unexplored. This study investigates ICC as a marker for treatment resistance in TRS, alongside structural indices for comparison. METHODS We assessed ICC in anterior cingulate, dorsolateral prefrontal, temporal, and parietal cortices of 38 first-line responders, 30 clozapine-resistant TRS, 37 clozapine-responsive TRS, and 52 healthy-controls. For comparative purposes, Fold and Curvature indices were also analyzed. RESULTS Adjusting for age, sex, nicotine-use, and chlorpromazine equivalence, principal findings indicate ICC elevations in the left hemisphere dorsolateral prefrontal (p < 0.001, η2partial = 0.142) and temporal cortices (LH p = 0.007, η2partial = 0.060; RH p = 0.011, η2partial = 0.076) of both TRS groups, and left anterior cingulate cortex of clozapine-resistant TRS (p = 0.026, η2partial = 0.065), compared to healthy-controls. Elevations that correlated with reduced cognition (p = 0.001) and negative symptomology (p < 0.034) in clozapine-resistant TRS. Fold and Curvature indices only detected group differences in the right parietal cortex, showing interactions with age, sex, and nicotine use. ICC showed interactions with age. CONCLUSION ICC elevations were found among patients with TRS, and correlated with symptom severity. ICCs relative independence from sex, nicotine-use, and antipsychotics, may support ICC's potential as a viable marker for TRS, though age interactions should be considered.
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Affiliation(s)
- Edgardo Torres-Carmona
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
| | - Fumihiko Ueno
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Yusuke Iwata
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Neuropsychiatry, Keio University, Minato, Tokyo, Japan
| | - Shinichiro Nakajima
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Neuropsychiatry, Keio University, Minato, Tokyo, Japan
| | - Jianmeng Song
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
| | - Wanna Mar
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Ali Abdolizadeh
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Sri Mahavir Agarwal
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Vincenzo de Luca
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Gary Remington
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Philip Gerretsen
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada
| | - Ariel Graff-Guerrero
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Campbell Institute Research Program, CAMH, Toronto, ON, Canada.
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10
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Jezsó B, Kálmán S, Farkas KG, Hathy E, Vincze K, Kovács-Schoblocher D, Lilienberg J, Tordai C, Nemoda Z, Homolya L, Apáti Á, Réthelyi JM. Haloperidol, Olanzapine, and Risperidone Induce Morphological Changes in an In Vitro Model of Human Hippocampal Neurogenesis. Biomolecules 2024; 14:688. [PMID: 38927091 PMCID: PMC11201986 DOI: 10.3390/biom14060688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/04/2024] [Accepted: 06/09/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND Induced pluripotent stem cell (iPSC) based neuronal differentiation is valuable for studying neuropsychiatric disorders and pharmacological mechanisms at the cellular level. We aimed to examine the effects of typical and atypical antipsychotics on human iPSC-derived neural progenitor cells (NPCs). METHODS Proliferation and neurite outgrowth were measured by live cell imaging, and gene expression levels related to neuronal identity were analyzed by RT-QPCR and immunocytochemistry during differentiation into hippocampal dentate gyrus granule cells following treatment of low- and high-dose antipsychotics (haloperidol, olanzapine, and risperidone). RESULTS Antipsychotics did not modify the growth properties of NPCs after 3 days of treatment. However, the characteristics of neurite outgrowth changed significantly in response to haloperidol and olanzapine. After three weeks of differentiation, mRNA expression levels of the selected neuronal markers increased (except for MAP2), while antipsychotics caused only subtle changes. Additionally, we found no changes in MAP2 or GFAP protein expression levels as a result of antipsychotic treatment. CONCLUSIONS Altogether, antipsychotic medications promoted neurogenesis in vitro by influencing neurite outgrowth rather than changing cell survival or gene expression. This study provides insights into the effects of antipsychotics on neuronal differentiation and highlights the importance of considering neurite outgrowth as a potential target of action.
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Affiliation(s)
- Bálint Jezsó
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
- Doctoral School of Biology, Institute of Biology, Eötvös Loránd University, Pázmány Péter sétány 1/c., H-1117 Budapest, Hungary
- ELTE-MTA “Momentum” Motor Enzymology Research Group, Department of Biochemistry, Eötvös Loránd University, Pázmány Péter sétány 1/c., H-1117 Budapest, Hungary
| | - Sára Kálmán
- Albert Szent-Györgyi Health Centre, Department of Psychiatry, University of Szeged, Szentháromság utca 5., H-6722 Szeged, Hungary;
| | - Kiara Gitta Farkas
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
| | - Edit Hathy
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
- Department of Psychiatry and Psychotherapy, Semmelweis University, Balassa utca 6., H-1083 Budapest, Hungary
| | - Katalin Vincze
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
- Department of Psychiatry and Psychotherapy, Semmelweis University, Balassa utca 6., H-1083 Budapest, Hungary
| | | | - Julianna Lilienberg
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
| | - Csongor Tordai
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
- Department of Psychiatry and Psychotherapy, Semmelweis University, Balassa utca 6., H-1083 Budapest, Hungary
| | - Zsófia Nemoda
- Department of Psychiatry and Psychotherapy, Semmelweis University, Balassa utca 6., H-1083 Budapest, Hungary
| | - László Homolya
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
| | - Ágota Apáti
- Institute of Molecular Life Sciences, HUN-REN RCNS, Magyar tudósok körútja 2., H-1117 Budapest, Hungary; (B.J.)
| | - János M. Réthelyi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Balassa utca 6., H-1083 Budapest, Hungary
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11
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Sfera A, Imran H, Sfera DO, Anton JJ, Kozlakidis Z, Hazan S. Novel Insights into Psychosis and Antipsychotic Interventions: From Managing Symptoms to Improving Outcomes. Int J Mol Sci 2024; 25:5904. [PMID: 38892092 PMCID: PMC11173215 DOI: 10.3390/ijms25115904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 05/20/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024] Open
Abstract
For the past 70 years, the dopamine hypothesis has been the key working model in schizophrenia. This has contributed to the development of numerous inhibitors of dopaminergic signaling and antipsychotic drugs, which led to rapid symptom resolution but only marginal outcome improvement. Over the past decades, there has been limited research on the quantifiable pathological changes in schizophrenia, including premature cellular/neuronal senescence, brain volume loss, the attenuation of gamma oscillations in electroencephalograms, and the oxidation of lipids in the plasma and mitochondrial membranes. We surmise that the aberrant activation of the aryl hydrocarbon receptor by toxins derived from gut microbes or the environment drives premature cellular and neuronal senescence, a hallmark of schizophrenia. Early brain aging promotes secondary changes, including the impairment and loss of mitochondria, gray matter depletion, decreased gamma oscillations, and a compensatory metabolic shift to lactate and lactylation. The aim of this narrative review is twofold: (1) to summarize what is known about premature cellular/neuronal senescence in schizophrenia or schizophrenia-like disorders, and (2) to discuss novel strategies for improving long-term outcomes in severe mental illness with natural senotherapeutics, membrane lipid replacement, mitochondrial transplantation, microbial phenazines, novel antioxidant phenothiazines, inhibitors of glycogen synthase kinase-3 beta, and aryl hydrocarbon receptor antagonists.
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Affiliation(s)
- Adonis Sfera
- Patton State Hospital, 3102 Highland Ave., Patton, CA 92369, USA; (H.I.)
- University of California Riverside, Riverside 900 University Ave., Riverside, CA 92521, USA
- Loma Linda University, 11139 Anderson St., Loma Linda, CA 92350, USA
| | - Hassan Imran
- Patton State Hospital, 3102 Highland Ave., Patton, CA 92369, USA; (H.I.)
- University of California Riverside, Riverside 900 University Ave., Riverside, CA 92521, USA
- Loma Linda University, 11139 Anderson St., Loma Linda, CA 92350, USA
| | - Dan O. Sfera
- Patton State Hospital, 3102 Highland Ave., Patton, CA 92369, USA; (H.I.)
- University of California Riverside, Riverside 900 University Ave., Riverside, CA 92521, USA
- Loma Linda University, 11139 Anderson St., Loma Linda, CA 92350, USA
| | | | - Zisis Kozlakidis
- International Agency for Research on Cancer, 69372 Lyon, France;
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12
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Zhang T, Wei Y, Tang X, Cui H, Xu L, Hu Y, Tang Y, Hu Q, Liu H, Wang Z, Chen T, Li C, Wang J. Cognitive functions following initiation of antipsychotic medication in adolescents and adults at clinical high risk for psychosis: a naturalistic sub group analysis using the MATRICS consensus cognitive battery. Child Adolesc Psychiatry Ment Health 2024; 18:53. [PMID: 38704567 PMCID: PMC11070077 DOI: 10.1186/s13034-024-00743-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 04/24/2024] [Indexed: 05/06/2024] Open
Abstract
BACKGROUND The effects of antipsychotic (AP) medications on cognitive functions in individuals at clinical high-risk (CHR) of psychosis are poorly understood. This study compared the effects of AP treatment on cognitive improvement in CHR adolescents and adults. METHODS A total of 327 CHR participants, with an age range of 13 to 45 years, who underwent baseline neuropsychological assessments and a 1-year clinical follow-up were included. Participants with CHR were categorized into four groups based on their age: adolescents (aged < 18) and adults (aged ≥ 18), as well as their antipsychotic medication status (AP+ or AP-). Therefore, the four groups were defined as Adolescent-AP-, Adolescent-AP+, Adult-AP-, and Adult-AP+. RESULTS During the follow-up, 231 CHR patients received AP treatment, 94 converted to psychosis, and 161 completed the 1-year follow-up. The Adolescent-AP+ group had more positive symptoms, lower general functions, and cognitive impairments than the Adolescent-AP- group at baseline, but no significant differences were observed among adults. The Adolescent-AP+ group showed a significant increase in the risk of conversion to psychosis (p < 0.001) compared to the Adolescent-AP- group. The Adult-AP+ group showed a decreasing trend in the risk of conversion (p = 0.088) compared to the Adult-AP- group. The Adolescent-AP- group had greater improvement in general functions (p < 0.001), neuropsychological assessment battery mazes (p = 0.025), and brief visuospatial memory test-revised (p = 0.020), as well as a greater decrease in positive symptoms (p < 0.001) at follow-up compared to the Adolescent-AP+ group. No significant differences were observed among adults. CONCLUSIONS Early use of AP was not associated with a positive effect on cognitive function in CHR adolescents. Instead, the absence of AP treatment was associated with better cognitive recovery, suggesting that AP exposure might not be the preferred choice for cognitive recovery in CHR adolescents, but may be more reasonable for use in adults.
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Affiliation(s)
- TianHong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China.
| | - YanYan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China
| | - XiaoChen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China
| | - HuiRu Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China
| | - LiHua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China
| | - YeGang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China
| | - YingYing Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China
| | - Qiang Hu
- Department of Psychiatry, ZhenJiang Mental Health Center, Zhenjiang, People's Republic of China
| | - HaiChun Liu
- Department of Automation, Shanghai Jiao Tong University, 200240, Shanghai, China
| | - ZiXuan Wang
- Shanghai Xinlianxin Psychological Counseling Center, Shanghai, China
| | - Tao Chen
- Big Data Research Lab, University of Waterloo, Waterloo, ON, Canada
- Labor and Worklife Program, Harvard University, Cambridge, MA, USA
| | - ChunBo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China
| | - JiJun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Jiaotong University School of Medicine, 600 Wanping Nan Road, 200030, Shanghai, China.
- Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, People's Republic of China.
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
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13
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Gan L, Wang L, Liu H, Wang G. Based on neural network cascade abnormal texture information dissemination of classification of patients with schizophrenia and depression. Brain Res 2024; 1830:148819. [PMID: 38403037 DOI: 10.1016/j.brainres.2024.148819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 02/11/2024] [Accepted: 02/20/2024] [Indexed: 02/27/2024]
Abstract
This study used MRI brain image segmentation to identify novel magnetic resonance imaging (MRI) biomarkers to distinguish patients with schizophrenia (SCZ), major depressive disorder (MD), and healthy control (HC). Brain texture measurements, including entropy and contrast, were calculated to capture variability in adjacent MRI voxel intensity. These measures are then applied to group classification in deep learning techniques and combined with hierarchical correlations to locate results. Texture feature maps were extracted from segmented brain MRI scans of 141 patients with schizophrenia (SCZ), 103 patients with major depressive disorder (MD) and 238 healthy controls (HC). Gray scale coassociation matrix (GLCM) is a monomer matrix calculated in a voxel cube. Deep learning methods were evaluated to determine the application capability of texture feature mapping in binary classification (SCZ vs. HC, MD vs. HC, SCZ vs. MD). The method is implemented by repeated nesting and cross-validation for feature selection. Regions that show the highest correlation (positive or negative). In this study, the authors successfully classified SCZ, MD and HC. This suggests that texture analysis can be used as an effective feature extraction method to distinguish different disease states. Compared with other methods, texture analysis can capture richer image information and improve classification accuracy in some cases. The classification accuracy of SCZ and HC, MD and HC, SCZ and MD reached 84.6%, 86.4% and 76.21%, respectively. Among them, SCZ and HC are the most significant features with high sensitivity and specificity.
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Affiliation(s)
- Linfeng Gan
- School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
| | - Linfeng Wang
- School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
| | - Hu Liu
- Peking University Health Science Center, Institute of Medical Technology, Beijing 100069, China.
| | - Gang Wang
- School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
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14
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Jensen KM, Calhoun VD, Fu Z, Yang K, Faria AV, Ishizuka K, Sawa A, Andrés-Camazón P, Coffman BA, Seebold D, Turner JA, Salisbury DF, Iraji A. A whole-brain neuromark resting-state fMRI analysis of first-episode and early psychosis: Evidence of aberrant cortical-subcortical-cerebellar functional circuitry. Neuroimage Clin 2024; 41:103584. [PMID: 38422833 PMCID: PMC10944191 DOI: 10.1016/j.nicl.2024.103584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/31/2024] [Accepted: 02/25/2024] [Indexed: 03/02/2024]
Abstract
Psychosis (including symptoms of delusions, hallucinations, and disorganized conduct/speech) is a main feature of schizophrenia and is frequently present in other major psychiatric illnesses. Studies in individuals with first-episode (FEP) and early psychosis (EP) have the potential to interpret aberrant connectivity associated with psychosis during a period with minimal influence from medication and other confounds. The current study uses a data-driven whole-brain approach to examine patterns of aberrant functional network connectivity (FNC) in a multi-site dataset comprising resting-state functional magnetic resonance images (rs-fMRI) from 117 individuals with FEP or EP and 130 individuals without a psychiatric disorder, as controls. Accounting for age, sex, race, head motion, and multiple imaging sites, differences in FNC were identified between psychosis and control participants in cortical (namely the inferior frontal gyrus, superior medial frontal gyrus, postcentral gyrus, supplementary motor area, posterior cingulate cortex, and superior and middle temporal gyri), subcortical (the caudate, thalamus, subthalamus, and hippocampus), and cerebellar regions. The prominent pattern of reduced cerebellar connectivity in psychosis is especially noteworthy, as most studies focus on cortical and subcortical regions, neglecting the cerebellum. The dysconnectivity reported here may indicate disruptions in cortical-subcortical-cerebellar circuitry involved in rudimentary cognitive functions which may serve as reliable correlates of psychosis.
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Affiliation(s)
- Kyle M Jensen
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA.
| | - Vince D Calhoun
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Zening Fu
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Kun Yang
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andreia V Faria
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Koko Ishizuka
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akira Sawa
- Johns Hopkins University School of Medicine, Baltimore, MD, USA; Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Pablo Andrés-Camazón
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA; Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - Brian A Coffman
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dylan Seebold
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jessica A Turner
- Wexner Medical Center, The Ohio State University, Columbus, OH, USA
| | - Dean F Salisbury
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Armin Iraji
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
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15
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Chaves C, Dursun SM, Tusconi M, Hallak JEC. Neuroinflammation and schizophrenia - is there a link? Front Psychiatry 2024; 15:1356975. [PMID: 38389990 PMCID: PMC10881867 DOI: 10.3389/fpsyt.2024.1356975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 01/30/2024] [Indexed: 02/24/2024] Open
Affiliation(s)
- Cristiano Chaves
- NeuroMood Lab, School of Medicine and Kingston Health Sciences Center (KHSC), Department of Psychiatry, Queen's University, Kingston, ON, Canada
- Department of Neuroscience and Behavior, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
- National Institute for Translational Medicine (INCT-TM), CNPq, São Paulo, Brazil
| | - Serdar M Dursun
- National Institute for Translational Medicine (INCT-TM), CNPq, São Paulo, Brazil
- Department of Psychiatry (Neurochemical Research Unit) and Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Massimo Tusconi
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Jaime E C Hallak
- Department of Neuroscience and Behavior, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
- National Institute for Translational Medicine (INCT-TM), CNPq, São Paulo, Brazil
- Department of Psychiatry (Neurochemical Research Unit) and Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
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16
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Si S, Bi A, Yu Z, See C, Kelly S, Ambrogi S, Arango C, Baeza I, Banaj N, Berk M, Castro-Fornieles J, Crespo-Facorro B, Crouse JJ, Díaz-Caneja CM, Fett AK, Fortea A, Frangou S, Goldstein BI, Hickie IB, Janssen J, Kennedy KG, Krabbendam L, Kyriakopoulos M, MacIntosh BJ, Morgado P, Nerland S, Pascual-Diaz S, Picó-Pérez M, Piras F, Rund BR, de la Serna E, Spalletta G, Sugranyes G, Suo C, Tordesillas-Gutiérrez D, Vecchio D, Radua J, McGuire P, Thomopoulos SI, Jahanshad N, Thompson PM, Barth C, Agartz I, James A, Kempton MJ. Mapping gray and white matter volume abnormalities in early-onset psychosis: an ENIGMA multicenter voxel-based morphometry study. Mol Psychiatry 2024; 29:496-504. [PMID: 38195979 PMCID: PMC11116097 DOI: 10.1038/s41380-023-02343-1] [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: 06/13/2023] [Revised: 11/07/2023] [Accepted: 11/27/2023] [Indexed: 01/11/2024]
Abstract
INTRODUCTION Regional gray matter (GM) alterations have been reported in early-onset psychosis (EOP, onset before age 18), but previous studies have yielded conflicting results, likely due to small sample sizes and the different brain regions examined. In this study, we conducted a whole brain voxel-based morphometry (VBM) analysis in a large sample of individuals with EOP, using the newly developed ENIGMA-VBM tool. METHODS 15 independent cohorts from the ENIGMA-EOP working group participated in the study. The overall sample comprised T1-weighted MRI data from 482 individuals with EOP and 469 healthy controls. Each site performed the VBM analysis locally using the standardized ENIGMA-VBM tool. Statistical parametric T-maps were generated from each cohort and meta-analyzed to reveal voxel-wise differences between EOP and healthy controls as well as the individual-based association between GM volume and age of onset, chlorpromazine (CPZ) equivalent dose, and other clinical variables. RESULTS Compared with healthy controls, individuals with EOP showed widespread lower GM volume encompassing most of the cortex, with the most marked effect in the left median cingulate (Hedges' g = 0.55, p = 0.001 corrected), as well as small clusters of lower white matter (WM), whereas no regional GM or WM volumes were higher in EOP. Lower GM volume in the cerebellum, thalamus and left inferior parietal gyrus was associated with older age of onset. Deficits in GM in the left inferior frontal gyrus, right insula, right precentral gyrus and right superior frontal gyrus were also associated with higher CPZ equivalent doses. CONCLUSION EOP is associated with widespread reductions in cortical GM volume, while WM is affected to a smaller extent. GM volume alterations are associated with age of onset and CPZ equivalent dose but these effects are small compared to case-control differences. Mapping anatomical abnormalities in EOP may lead to a better understanding of the role of psychosis in brain development during childhood and adolescence.
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Grants
- P41 EB015922 NIBIB NIH HHS
- R01 MH116147 NIMH NIH HHS
- R01 MH121246 NIMH NIH HHS
- R01 MH134004 NIMH NIH HHS
- P50 MH115846 NIMH NIH HHS
- U01 MH124639 NIMH NIH HHS
- R01 AG059874 NIA NIH HHS
- Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (ISCIII), co-financed by the European Union, ERDF Funds from the European Commission, “A way of making Europe”, financed by the European Union - NextGenerationEU (PMP21/00051), PI19/01024, PI20/00721, JR19/00024. CIBERSAM, Madrid Regional Government (S2022/BMD-7216 (AGES 3-CM)), European Union Structural Funds, European Union Seventh Framework Program, European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking: Project PRISM-2 (Grant agreement No.101034377), Project AIMS-2-TRIALS (Grant agreement No 777394), Horizon Europe, the National Institute of Mental Health of the National Institutes of Health under Award Number 1U01MH124639-01 (Project ProNET) and Award Number 5P50MH115846-03 (project FEP-CAUSAL), Fundación Familia Alonso, and Fundación Alicia Koplowitz. YTOP cohort is suppoprted by The Research Council of Norway (223273, 213700, 250358, 288083); South-Eastern Norway Regional Health Authority (2017112); KG Jebsen Stiftelsen (SKGJ-MED-008).
- the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (ISCIII), co-financed by the European Union, (PI18/00976, PI20/00654, PI02100330), Ajut a la Recerca Pons Bartran, the Alicia Koplowitz Foundation, Brain and Behaviour Research Foundation (NARSAD Young Investigator Award 2017) and Strategic Research and Innovation Plan in Health (PERIS), Department of Health, Government of Catalonia.
- NHMRC Senior Principal Research Fellowship and Leadership 3 Investigator grant (1156072 and 2017131)
- Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (ISCIII), co-financed by the European Union, ERDF Funds from the European Commission, “A way of making Europe”, financed by the European Union - NextGenerationEU (PMP21/00051), PI19/01024, PI20/00721, JR19/00024,. CIBERSAM, Madrid Regional Government (S2022/BMD-7216 (AGES 3-CM)), European Union Structural Funds, European Union Seventh Framework Program, European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking: Project PRISM-2 (Grant agreement No.101034377), Project AIMS-2-TRIALS (Grant agreement No 777394), Horizon Europe, the National Institute of Mental Health of the National Institutes of Health under Award Number 1U01MH124639-01 (Project ProNET) and Award Number 5P50MH115846-03 (project FEP-CAUSAL), Fundación Familia Alonso, and Fundación Alicia Koplowitz.
- the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (ISCIII), co-financed by the European Union, ERDF Funds from the European Commission, “A way of making Europe”, financed by the European Union - NextGenerationEU (PMP21/00051), PI19/01024, PI20/00721, JR19/00024,. CIBERSAM, Madrid Regional Government (S2022/BMD-7216 (AGES 3-CM)), European Union Structural Funds, European Union Seventh Framework Program, European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking: Project PRISM-2 (Grant agreement No.101034377), Project AIMS-2-TRIALS (Grant agreement No 777394), Horizon Europe, the National Institute of Mental Health of the National Institutes of Health under Award Number 1U01MH124639-01 (Project ProNET) and Award Number 5P50MH115846-03 (project FEP-CAUSAL), Fundación Familia Alonso, and Fundación Alicia Koplowitz.
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Affiliation(s)
- Shuqing Si
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
| | - Anbreen Bi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Zhaoying Yu
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Cheryl See
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Sinead Kelly
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Hospital Clinic Barcelona. CIBERSAM-ISCIII. Fundació de Recerca Clínic Barcelona - August Pi i Sunyer Biomedical Research Institute (FCRB-IDIBAPS). Institute of Neuroscience, Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Michael Berk
- Deakin University, Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Australia
| | - Josefina Castro-Fornieles
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Hospital Clinic Barcelona. CIBERSAM-ISCIII. Fundació de Recerca Clínic Barcelona - August Pi i Sunyer Biomedical Research Institute (FCRB-IDIBAPS). Institute of Neuroscience, Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Benedicto Crespo-Facorro
- Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Department of Psychiatry, CIBERSAM, IBiS-CSIC, Sevilla, Spain
| | - Jacob J Crouse
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, Madrid, Spain
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Anne-Kathrin Fett
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
- Department of Psychology, City, University of London, London, UK
| | - Adriana Fortea
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Hospital Clinic Barcelona. CIBERSAM-ISCIII. Fundació de Recerca Clínic Barcelona - August Pi i Sunyer Biomedical Research Institute (FCRB-IDIBAPS). Institute of Neuroscience, Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Sophia Frangou
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, Madrid, Spain
| | - Kody G Kennedy
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Lydia Krabbendam
- Department of Clinical, Neuro and Developmental Psychology, Faculty of Behavioural and Movement Sciences, Institute for Brain and Behaviour (IBBA) Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Marinos Kyriakopoulos
- 1st Department of Psychiatry, National and Kapodistrian University of Athens, Athens, Greece
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Pedro Morgado
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, Braga/Guimarães, Portugal
- 2CA-Braga Cinical Academic Center, Hospital de Braga, 4710-243, Braga, Portugal
| | - Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Saül Pascual-Diaz
- Laboratory of Surgical Neuroanatomy, Universitat de Barcelona, Barcelona, Spain
| | - Maria Picó-Pérez
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, Braga/Guimarães, Portugal
- Departamento de Psicología Básica, Clínica y Psicobiología, Universitat Jaume I, Castelló de la Plana, Spain
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Bjørn Rishovd Rund
- Research Department, Vestre Viken Hospital Trust, 3004, Drammen, Norway
- Department of Psychology, University of Oslo, P. O. box 1094, Blindern, 0317, Oslo, Norway
| | - Elena de la Serna
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Hospital Clinic Barcelona. CIBERSAM-ISCIII. Fundació de Recerca Clínic Barcelona - August Pi i Sunyer Biomedical Research Institute (FCRB-IDIBAPS). Institute of Neuroscience, Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Hospital Clinic Barcelona. CIBERSAM-ISCIII. Fundació de Recerca Clínic Barcelona - August Pi i Sunyer Biomedical Research Institute (FCRB-IDIBAPS). Institute of Neuroscience, Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Chao Suo
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Diana Tordesillas-Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander (Cantabria), Spain
- Advanced Computing and e-Science, Instituto de Física de Cantabria (UC-CSIC), Santander (Cantabria), Spain
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, University of Barcelona, Barcelona, Spain
| | - Philip McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institute & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Anthony James
- Department of Psychiatry, University of Oxford, Oxford, UK
- Highfield Unit, Warneford Hospital, Oxford, UK
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
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17
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Tandon R, Nasrallah H, Akbarian S, Carpenter WT, DeLisi LE, Gaebel W, Green MF, Gur RE, Heckers S, Kane JM, Malaspina D, Meyer-Lindenberg A, Murray R, Owen M, Smoller JW, Yassin W, Keshavan M. The schizophrenia syndrome, circa 2024: What we know and how that informs its nature. Schizophr Res 2024; 264:1-28. [PMID: 38086109 DOI: 10.1016/j.schres.2023.11.015] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 03/01/2024]
Abstract
With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.
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Affiliation(s)
- Rajiv Tandon
- Department of Psychiatry, WMU Homer Stryker School of Medicine, Kalamazoo, MI 49008, United States of America.
| | - Henry Nasrallah
- Department of Psychiatry, University of Cincinnati College of Medicine Cincinnati, OH 45267, United States of America
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21201, United States of America
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance and Harvard Medical School, Cambridge, MA 02139, United States of America
| | - Wolfgang Gaebel
- Department of Psychiatry and Psychotherapy, LVR-Klinikum Dusseldorf, Heinrich-Heine University, Dusseldorf, Germany
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute of Neuroscience and Human Behavior, UCLA, Los Angeles, CA 90024, United States of America; Greater Los Angeles Veterans' Administration Healthcare System, United States of America
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States of America
| | - Stephan Heckers
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37232, United States of America
| | - John M Kane
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Glen Oaks, NY 11004, United States of America
| | - Dolores Malaspina
- Department of Psychiatry, Neuroscience, Genetics, and Genomics, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannhein/Heidelberg University, Mannheim, Germany
| | - Robin Murray
- Institute of Psychiatry, Psychology, and Neuroscience, Kings College, London, UK
| | - Michael Owen
- Centre for Neuropsychiatric Genetics and Genomics, and Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Jordan W Smoller
- Center for Precision Psychiatry, Department of Psychiatry, Psychiatric and Neurodevelopmental Unit, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States of America
| | - Walid Yassin
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
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18
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Liang L, Heinrichs RW, Liddle PF, Jeon P, Théberge J, Palaniyappan L. Cortical impoverishment in a stable subgroup of schizophrenia: Validation across various stages of psychosis. Schizophr Res 2024; 264:567-577. [PMID: 35644706 DOI: 10.1016/j.schres.2022.05.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 05/09/2022] [Accepted: 05/16/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Cortical thinning is a well-known feature in schizophrenia. The considerable variation in the spatial distribution of thickness changes has been used to parse heterogeneity. A 'cortical impoverishment' subgroup with a generalized reduction in thickness has been reported. However, it is unclear if this subgroup is recoverable irrespective of illness stage, and if it relates to the glutamate hypothesis of schizophrenia. METHODS We applied hierarchical cluster analysis to cortical thickness data from magnetic resonance imaging scans of three datasets in different stages of psychosis (n = 288; 160 patients; 128 healthy controls) and studied the cognitive and symptom profiles of the observed subgroups. In one of the samples, we also studied the subgroup differences in 7-Tesla magnetic resonance spectroscopy glutamate concentration in the dorsal anterior cingulate cortex. RESULTS Our consensus-based clustering procedure consistently produced 2 subgroups of participants. Patients accounted for 75%-100% of participants in one subgroup that was characterized by significantly lower cortical thickness. Both subgroups were equally symptomatic in clinically unstable stages, but cortical impoverishment indicated a higher symptom burden in a clinically stable sample and higher glutamate levels in the first-episode sample. There were no subgroup differences in cognitive and functional outcome profiles or antipsychotic exposure across all stages. CONCLUSIONS Cortical thinning does not vary with functioning or cognitive impairment, but it is more prevalent among patients, especially those with glutamate excess in early stages and higher residual symptom burden at later stages, providing an important mechanistic clue to one of the several possible pathways to the illness.
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Affiliation(s)
- Liangbing Liang
- Graduate Program in Neuroscience, Western University, London, Ontario, Canada; Robarts Research Institute, Western University, London, Ontario, Canada
| | | | - Peter F Liddle
- Institute of Mental Health, Division of Mental Health and Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Peter Jeon
- Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Jean Théberge
- Department of Medical Biophysics, Western University, London, Ontario, Canada; Department of Psychiatry, Western University, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, Western University, London, Ontario, Canada; Department of Medical Biophysics, Western University, London, Ontario, Canada; Department of Psychiatry, Western University, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
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19
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Kang N, Chung S, Lee SH, Bang M. Cerebro-cerebellar gray matter abnormalities associated with cognitive impairment in patients with recent-onset and chronic schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:11. [PMID: 38280893 PMCID: PMC10851702 DOI: 10.1038/s41537-024-00434-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/12/2024] [Indexed: 01/29/2024]
Abstract
Although the role of the cerebellum in schizophrenia has gained attention, its contribution to cognitive impairment remains unclear. We aimed to investigate volumetric alterations in the cerebro-cerebellar gray matter (GM) in patients with recent-onset schizophrenia (ROS) and chronic schizophrenia (CS) compared with healthy controls (HCs). Seventy-two ROS, 43 CS, and 127 HC participants were recruited, and high-resolution T1-weighted structural magnetic resonance images of the brain were acquired. We compared cerebellar GM volumes among the groups using voxel-based morphometry and examined the cerebro-cerebellar GM volumetric correlations in participants with schizophrenia. Exploratory correlation analysis investigated the functional relevance of cerebro-cerebellar GM volume alterations to cognitive function in the schizophrenia group. The ROS and CS participants demonstrated smaller cerebellar GM volumes, particularly in Crus I and II, than HCs. Extracted cerebellar GM volumes demonstrated significant positive correlations with the cerebral GM volume in the fronto-temporo-parietal association areas engaged in higher-order association. The exploratory analysis showed that smaller cerebellar GM in the posterior lobe regions was associated with poorer cognitive performance in participants with schizophrenia. Our study suggests that cerebellar pathogenesis is present in the early stages of schizophrenia and interconnected with structural abnormalities in the cerebral cortex. Integrating the cerebellum into the pathogenesis of schizophrenia will help advance our understanding of the disease and identify novel treatment targets concerning dysfunctional cerebro-cerebellar interactions.
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Affiliation(s)
- Naok Kang
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea
| | - Subin Chung
- CHA University School of Medicine, Pocheon, Republic of Korea
| | - Sang-Hyuk Lee
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea
| | - Minji Bang
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea.
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20
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Rasser PE, Ehlkes T, Schall U. Fronto-temporal cortical grey matter thickness and surface area in the at-risk mental state and recent-onset schizophrenia: a magnetic resonance imaging study. BMC Psychiatry 2024; 24:33. [PMID: 38191320 PMCID: PMC10775434 DOI: 10.1186/s12888-024-05494-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 01/02/2024] [Indexed: 01/10/2024] Open
Abstract
BACKGROUND Studies to date examining cortical thickness and surface area in young individuals At Risk Mental State (ARMS) of developing psychosis have revealed inconsistent findings, either reporting increased, decreased or no differences compared to mentally healthy individuals. The inconsistencies may be attributed to small sample sizes, varying age ranges, different ARMS identification criteria, lack of control for recreational substance use and antipsychotic pharmacotherapy, as well as different methods for deriving morphological brain measures. METHODS A surfaced-based approach was employed to calculate fronto-temporal cortical grey matter thickness and surface area derived from magnetic resonance imaging (MRI) data collected from 44 young antipsychotic-naïve ARMS individuals, 19 young people with recent onset schizophrenia, and 36 age-matched healthy volunteers. We conducted group comparisons of the morphological measures and explored their association with symptom severity, global and socio-occupational function levels, and the degree of alcohol and cannabis use in the ARMS group. RESULTS Grey matter thickness and surface areas in ARMS individuals did not significantly differ from their age-matched healthy counterparts. However, reduced left-frontal grey matter thickness was correlated with greater symptom severity and lower function levels; the latter being also correlated with smaller left-frontal surface areas. ARMS individuals with more severe symptoms showed greater similarities to the recent onset schizophrenia group. The morphological measures in ARMS did not correlate with the lifetime level of alcohol or cannabis use. CONCLUSIONS Our findings suggest that a decline in function levels and worsening mental state are associated with morphological changes in the left frontal cortex in ARMS but to a lesser extent than those seen in recent onset schizophrenia. Alcohol and cannabis use did not confound these findings. However, the cross-sectional nature of our study limits our ability to draw conclusions about the potential progressive nature of these morphological changes in ARMS.
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Affiliation(s)
- Paul E Rasser
- Centre for Brain & Mental Health Research, The University of Newcastle, Waratah, NSW, 2298, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, 2305, Australia
| | - Tim Ehlkes
- Centre for Brain & Mental Health Research, The University of Newcastle, Waratah, NSW, 2298, Australia
| | - Ulrich Schall
- Centre for Brain & Mental Health Research, The University of Newcastle, Waratah, NSW, 2298, Australia.
- Hunter Medical Research Institute, New Lambton Heights, NSW, 2305, Australia.
- Centre for Brain & Mental Health Research, McAuley Centre, Mater Hospital, Waratah, NSW, 2298, Australia.
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21
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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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22
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Belkacem A, Lavigne KM, Makowski C, Chakravarty M, Joober R, Malla A, Shah J, Lepage M. Effects of Anticholinergic Burden on Verbal Memory Performance in First-Episode Psychosis. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2023; 68:894-903. [PMID: 37254533 PMCID: PMC10657580 DOI: 10.1177/07067437231179161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVES Antipsychotics are widely used to treat first-episode psychosis but may have an anticholinergic burden, that is, a cumulative effect of medications that block the cholinergic system. Studies suggest that a high anticholinergic burden negatively affects memory in psychosis, where cognitive deficits, particularly those in verbal memory, are a core feature of the disease. The present study sought to replicate this in a large cohort of well-characterized first-episode psychosis patients. We expected that patients in the highest anticholinergic burden group would exhibit the poorest verbal memory compared to those with low anticholinergic burden and healthy controls at baseline (3 months following admission). We further hypothesized that over time, at month 12, patients' verbal memory performance would improve but would remain inferior to controls. METHODS Patients (n = 311; low anticholinergic burden [n = 241] and high anticholinergic burden [n = 70], defined by a Drug Burden Index cut-off of 1) and healthy controls (n = 128) completed a clinical and neurocognitive battery including parts of the Wechsler Memory Scale at months 3 and 12. RESULTS Cross-sectionally, using an analysis of variance, patients in the highest anticholinergic burden group had the poorest performance in verbal memory when compared to the other groups at month 3, F(2,430) = 52.33, P < 0.001. Longitudinally, using a Generalized Estimating Equation model, the verbal memory performance of all groups improved over time. However, patients' performance overall remained poorer than the controls. CONCLUSION These findings highlight the importance of considering the anticholinergic burden when prescribing medications in the early stages of the disease.
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Affiliation(s)
- Agnès Belkacem
- Douglas Research Centre, McGill University, Montreal, Canada
| | - Katie M. Lavigne
- Douglas Research Centre, McGill University, Montreal, Canada
- Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
| | - Carolina Makowski
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | | | - Ridha Joober
- Douglas Research Centre, McGill University, Montreal, Canada
| | - Ashok Malla
- Douglas Research Centre, McGill University, Montreal, Canada
| | - Jai Shah
- Douglas Research Centre, McGill University, Montreal, Canada
| | - Martin Lepage
- Douglas Research Centre, McGill University, Montreal, Canada
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Ehlen F, Montag C, Leopold K, Heinz A. Linguistic findings in persons with schizophrenia-a review of the current literature. Front Psychol 2023; 14:1287706. [PMID: 38078276 PMCID: PMC10710163 DOI: 10.3389/fpsyg.2023.1287706] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 10/31/2023] [Indexed: 10/24/2024] Open
Abstract
INTRODUCTION Alterations of verbalized thought occur frequently in psychotic disorders. We characterize linguistic findings in individuals with schizophrenia based on the current literature, including findings relevant for differential and early diagnosis. METHODS Review of literature published via PubMed search between January 2010 and May 2022. RESULTS A total of 143 articles were included. In persons with schizophrenia, language-related alterations can occur at all linguistic levels. Differentiating from findings in persons with affective disorders, typical symptoms in those with schizophrenia mainly include so-called "poverty of speech," reduced word and sentence production, impaired processing of complex syntax, pragmatic language deficits as well as reduced semantic verbal fluency. At the at-risk state, "poverty of content," pragmatic difficulties and reduced verbal fluency could be of predictive value. DISCUSSION The current results support multilevel alterations of the language system in persons with schizophrenia. Creative expressions of psychotic experiences are frequently found but are not in the focus of this review. Clinical examinations of linguistic alterations can support differential diagnostics and early detection. Computational methods (Natural Language Processing) may improve the precision of corresponding diagnostics. The relations between language-related and other symptoms can improve diagnostics.
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Affiliation(s)
- Felicitas Ehlen
- Department of Neurology, Motor and Cognition Group, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Vivantes Klinikum am Urban und Vivantes Klinikum im Friedrichshain, Kliniken für Psychiatrie, Psychotherapie und Psychosomatik, Akademische Lehrkrankenhäuser Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Christiane Montag
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte (Psychiatric University Clinic at St. Hedwig Hospital, Große Hamburger Berlin) – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Karolina Leopold
- Vivantes Klinikum am Urban und Vivantes Klinikum im Friedrichshain, Kliniken für Psychiatrie, Psychotherapie und Psychosomatik, Akademische Lehrkrankenhäuser Charité - Universitätsmedizin Berlin, Berlin, Germany
- Klinik und Poliklinik für Psychiatrie und Psychotherapie, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Andreas Heinz
- Department of Psychiatry and Neurosciences, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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24
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Liu CC, Hsieh MH, Chien YL, Liu CM, Lin YT, Hwang TJ, Hwu HG. Guided antipsychotic reduction to reach minimum effective dose (GARMED) in patients with remitted psychosis: a 2-year randomized controlled trial with a naturalistic cohort. Psychol Med 2023; 53:7078-7086. [PMID: 36896797 PMCID: PMC10719630 DOI: 10.1017/s0033291723000429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 01/30/2023] [Accepted: 02/06/2023] [Indexed: 03/11/2023]
Abstract
BACKGROUND Patients with remitted psychosis face a dilemma between the wish to discontinue antipsychotics and the risk of relapse. We test if an operationalized guided-dose-reduction algorithm can help reach a lower effective dose without increased risks of relapse. METHODS A 2-year open-label randomized prospective comparative cohort trial from Aug 2017 to Sep 2022. Patients with a history of schizophrenia-related psychotic disorders under stable medications and symptoms were eligible, randomized 2:1 into guided dose reduction group (GDR) v. maintenance treatment group (MT1), together with a group of naturalistic maintenance controls (MT2). We observed if the relapse rates would be different between 3 groups, to what extent the dose could be reduced, and if GDR patients could have improved functioning and quality of life. RESULTS A total of 96 patients, comprised 51, 24, and 21 patients in GDR, MT1, and MT2 groups, respectively. During follow-up, 14 patients (14.6%) relapsed, including 6, 4, and 4 from GDR, MT1, and MT2, statistically no difference between groups. In total, 74.5% of GDR patients could stay well under a lower dose, including 18 patients (35.3%) conducting 4 consecutive dose-tapering and staying well after reducing 58.5% of their baseline dose. The GDR group exhibited improved clinical outcomes and endorsed better quality of life. CONCLUSIONS GDR is a feasible approach as the majority of patients had a chance to taper antipsychotics to certain extents. Still, 25.5% of GDR patients could not successfully decrease any dose, including 11.8% experienced relapse, a risk comparable to their maintenance counterparts.
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Affiliation(s)
- Chen-Chung Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 10002, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ming H. Hsieh
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 10002, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yi-Ling Chien
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 10002, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chih-Min Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 10002, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yi-Ting Lin
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 10002, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Tzung-Jeng Hwang
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 10002, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Hai-Gwo Hwu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, 10002, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
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25
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Sfera A, Andronescu L, Britt WG, Himsl K, Klein C, Rahman L, Kozlakidis Z. Receptor-Independent Therapies for Forensic Detainees with Schizophrenia-Dementia Comorbidity. Int J Mol Sci 2023; 24:15797. [PMID: 37958780 PMCID: PMC10647468 DOI: 10.3390/ijms242115797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/23/2023] [Accepted: 10/28/2023] [Indexed: 11/15/2023] Open
Abstract
Forensic institutions throughout the world house patients with severe psychiatric illness and history of criminal violations. Improved medical care, hygiene, psychiatric treatment, and nutrition led to an unmatched longevity in this population, which previously lived, on average, 15 to 20 years shorter than the public at large. On the other hand, longevity has contributed to increased prevalence of age-related diseases, including neurodegenerative disorders, which complicate clinical management, increasing healthcare expenditures. Forensic institutions, originally intended for the treatment of younger individuals, are ill-equipped for the growing number of older offenders. Moreover, as antipsychotic drugs became available in 1950s and 1960s, we are observing the first generation of forensic detainees who have aged on dopamine-blocking agents. Although the consequences of long-term treatment with these agents are unclear, schizophrenia-associated gray matter loss may contribute to the development of early dementia. Taken together, increased lifespan and the subsequent cognitive deficit observed in long-term forensic institutions raise questions and dilemmas unencountered by the previous generations of clinicians. These include: does the presence of neurocognitive dysfunction justify antipsychotic dose reduction or discontinuation despite a lifelong history of schizophrenia and violent behavior? Should neurolipidomic interventions become the standard of care in elderly individuals with lifelong schizophrenia and dementia? Can patients with schizophrenia and dementia meet the Dusky standard to stand trial? Should neurocognitive disorders in the elderly with lifelong schizophrenia be treated differently than age-related neurodegeneration? In this article, we hypothesize that gray matter loss is the core symptom of schizophrenia which leads to dementia. We hypothesize further that strategies to delay or stop gray matter depletion would not only improve the schizophrenia sustained recovery, but also avert the development of major neurocognitive disorders in people living with schizophrenia. Based on this hypothesis, we suggest utilization of both receptor-dependent and independent therapeutics for chronic psychosis.
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Affiliation(s)
- Adonis Sfera
- Paton State Hospital, 3102 Highland Ave, Patton, CA 92369, USA; (L.A.); (K.H.)
- School of Behavioral Health, Loma Linda University, 11139 Anderson St., Loma Linda, CA 92350, USA
- Department of Psychiatry, University of California, Riverside 900 University Ave, Riverside, CA 92521, USA
| | - Luminita Andronescu
- Paton State Hospital, 3102 Highland Ave, Patton, CA 92369, USA; (L.A.); (K.H.)
| | - William G. Britt
- Department of Psychiatry, School of Medicine, Loma Linda University, Loma Linda, CA 92350, USA;
| | - Kiera Himsl
- Paton State Hospital, 3102 Highland Ave, Patton, CA 92369, USA; (L.A.); (K.H.)
| | - Carolina Klein
- California Department of State Hospitals, Sacramento, CA 95814, USA;
| | - Leah Rahman
- Department of Neuroscience, University of Oregon, 1585 E 13th Ave, Eugene, OR 97403, USA;
| | - Zisis Kozlakidis
- International Agency for Research on Cancer, 69366 Lyon Cedex, France;
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26
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Demir AU, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Rheenen TEV, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos S, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TG, Cheng W, Feng J. Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.11.23296862. [PMID: 37873296 PMCID: PMC10593004 DOI: 10.1101/2023.10.11.23296862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, 305-8575, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, 187-8553, Japan
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L. Rodrigue
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona 08035, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Spain
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R. Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S. Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience - University “Federico II”, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences - University “Federico II”, Naples, Italy
| | - Min Tae M. Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Centre for Addiction and Mental Health, Toronto, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, California, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Sophia Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi’an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, 92697-3950, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | | | | | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- School of Data Science, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
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27
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Kang IC, Pasternak O, Zhang F, Penzel N, Seitz-Holland J, Tang Y, Zhang T, Xu L, Li H, Keshavan M, Whitfield-Gabrielli S, Niznikiewicz M, Stone W, Wang J, Shenton M. Microstructural Cortical Gray Matter Changes Preceding Accelerated Volume Changes in Individuals at Clinical High Risk for Psychosis. RESEARCH SQUARE 2023:rs.3.rs-3179575. [PMID: 37841868 PMCID: PMC10571628 DOI: 10.21203/rs.3.rs-3179575/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Recent studies show that accelerated cortical gray matter (GM) volume reduction seen in anatomical MRI can help distinguish between individuals at clinical high risk (CHR) for psychosis who will develop psychosis and those who will not. This reduction is thought to result from an accumulation of microstructural changes, such as decreased spine density and dendritic arborization. Detecting the microstructural sources of these changes before they accumulate is crucial, as volume reduction likely indicates an underlying neurodegenerative process. Our study aimed to detect these microstructural GM alterations using diffusion MRI (dMRI). We tested for baseline and longitudinal group differences in anatomical and dMRI data from 160 individuals at CHR and 96 healthy controls (HC) acquired in a single imaging site. Eight cortical lobes were examined for GM volume and GM microstructure. A novel dMRI measure, interstitial free water (iFW), was used to quantify GM microstructure by eliminating cerebrospinal fluid contribution. Additionally, we assessed whether these measures differentiated the 33 individuals at CHR who developed psychosis (CHR-P) from the 127 individuals at CHR who did not (CHR-NP). At baseline the CHR group had significantly higher iFW than HC in the prefrontal, temporal, parietal, and occipital lobes, while volume was reduced only in the temporal lobe. Neither iFW nor volume differentiated between the CHR-P and CHR-NP groups at baseline. However, in most brain areas, the CHR-P group demonstrated significantly accelerated iFW increase and volume reduction with time than the CHR-NP group. Our results demonstrate that microstructural GM changes in individuals at CHR have a wider extent than volumetric changes and they predate the acceleration of brain changes that occur around psychosis onset. Microstructural GM changes are thus an early pathology at the prodromal stage of psychosis that may be useful for early detection and a better mechanistic understanding of psychosis development.
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Affiliation(s)
| | | | | | | | - Johanna Seitz-Holland
- Brigham and Women's Hospital and Massachusetts General Hospital, Harvard Medical School
| | - Yingying Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine
| | - Tianhong Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | | | | | | | | | | | | | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine
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28
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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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Kocakaya H, Bayar Muluk N, Bekin Sarikaya PZ. Peripheric and central olfactory measurements in patients with bipolar disorder. Acta Radiol 2023; 64:2594-2602. [PMID: 37312533 DOI: 10.1177/02841851231179174] [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] [Indexed: 06/15/2023]
Abstract
BACKGROUND Bipolar disorder (BD) is a mental health disorder. PURPOSE To investigate the peripheric and central olfactory measurements in patients with BD using magnetic resonance imaging (MRI). MATERIAL AND METHODS This study was conducted retrospectively. Group 1 consisted of 27 euthymic patients with BD (14 men, 13 women) and Group 2 consisted of 27 healthy controls (14 men, 13 women). Olfactory bulb (OB) volume and olfactory sulcus (OS) depth (peripheric), and corpus amygdala and insular gyrus area (central) measurements were performed using cranial MRI. RESULTS OB volume and OS depth value of the bipolar group were lower than the control group, but there were no significant differences between the groups (P > 0.05). The corpus amygdala and left insular gyrus area of the bipolar group were significantly lower than those in the control group (P < 0.05). There were positive correlations between OB volumes and OS depths, the insular gyrus areas, and the corpus amygdala areas (P < 0.05). As the number of depressive episodes and duration of illness increased in bipolar patients, the depth of the sulcus decreased (P < 0.05). CONCLUSION In the present study a correlation was detected between OB volumes and the structures, known as emotional processing (e.g. insular gyrus area, corpus amygdala), and clinical features. Accordingly, new treatment techniques, such as olfactory training, may be considered an option in the treatment of such patients with BD.
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Affiliation(s)
- Hanife Kocakaya
- Psychiatry Department, Faculty of Medicine, Doctor Faculty Member in Kırıkkale University, Kırıkkale, Turkey
| | - Nuray Bayar Muluk
- ENT Department, Faculty of Medicine, Professor in Kırıkkale University, Kırıkkale, Turkey
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Samamé C, Durante P, Cattaneo B, Aprahamian I, Strejilevich S. Efficacy of cognitive remediation in bipolar disorder: systematic review and meta-analysis of randomized controlled trials. Psychol Med 2023; 53:5361-5373. [PMID: 37485698 DOI: 10.1017/s0033291723001897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
A significant percentage of people with bipolar disorder (BD) exhibit suboptimal functional adjustment, even when appropriately treated and after symptomatic recovery is achieved. Given that cognitive impairment is one of the strongest correlates of socio-occupational outcomes and quality of life in BD, cognitive remediation (CR) is currently acknowledged as a promising treatment that could help bridge the gap between symptomatic and full functional recovery. The aim of this review was to explore the efficacy of CR approaches in improving cognitive and functional outcomes in BD patients. PubMed, PsycINFO, and CENTRAL were searched from inception to November 2022. Randomized controlled trials exploring the effects of CR on cognition and/or functional adjustment in adult BD patients were eligible. Ten studies based on seven independent trials (n = 586) were included. Change-score effect sizes (Hedges' g) were obtained for efficacy outcome measures and combined by means of meta-analytic procedures. Small but significant overall effects were observed for working memory (g = 0.32, 95% CI 0.11-0.52), planning (g = 0.30, 95% CI 0.03-0.56), and verbal learning (g = 0.40, 95% CI 0.15-0.66). However, CR was not found to exert any significant effects on functional outcomes at treatment completion or at follow-up assessment. Although CR may modestly enhance the cognitive performance of BD patients, this effect does not translate into an improvement at the functional level. The current data do not support the inclusion of CR as a treatment recommendation in clinical practice guidelines for the management of BD.
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Affiliation(s)
- Cecilia Samamé
- Universidad Católica del Uruguay, Montevideo, Uruguay
- Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina
| | | | | | - Ivan Aprahamian
- Faculdade de Medicina de Jundiaí, Departamento de Medicina Interna, Divisão de Geriatria, Grupo de Investigação sobre Multimorbidade e Saúde Mental no Envelhecimento, Jundiaí SP, Brasil
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sergio Strejilevich
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
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Liu CC, Hsieh MH, Chien YL, Liu CM, Lin YT, Hwang TJ, Hwu HG. Dose-tapering trajectories in patients with remitted psychosis undergoing guided antipsychotic reduction to reach minimum effective dose. Eur Psychiatry 2023; 66:e66. [PMID: 37578111 PMCID: PMC10594210 DOI: 10.1192/j.eurpsy.2023.2440] [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: 04/11/2023] [Revised: 08/01/2023] [Accepted: 08/08/2023] [Indexed: 08/15/2023] Open
Abstract
BACKGROUND Patients with remitted psychosis wish to reduce antipsychotic doses yet facing increased risks of relapse. Examining dose-tapering processes may provide insights to re-evaluate the risk-to-benefit balance. We aimed to depict and subgroup tapering trajectories, and explore factors associated with different dose-reduction patterns. METHODS A 2-year open-label randomized prospective comparative trial from August 2017 to September 2022 in Taiwan. Patients with a history of schizophrenia-related psychotic disorders under stable medications and symptoms were eligible, randomizing a proportion to conduct guided dose reduction. We depicted the trajectories of individual patients and named subgroups based on dose-tapering patterns. Predictors of baseline characteristics for designated subgroups were examined by logistic regression analysis; changes in outcomes were compared by paired t-test. RESULTS Fifty-one patients undergoing guided dose reduction, 18 (35.3%) reduced 4 steps consecutively (sequential reducers, SR), 14 (27.5%) reduced 1 to 3 steps (modest reducers, MR), 3 (5.9%) re-escalated to previous level (alert reducers, AR), 7 (13.7%) returned to baseline level (baseline returners, BR), 6 (11.7%) relapsed (failed reducers, FR) and 3 (5.9%) withdrew without relapse (early exits, EE). Patients with a history of relapse assumed a conservative dose-tapering pace; only the SR subgroup exhibited significant improvements in functioning and quality of life while failing to identify variables for predicting who would become SR or FR. CONCLUSIONS Guided dose reduction comprises dynamic processes with differences between individual trajectories. The proposed naming of dose-tapering patterns/subgroups provides a framework depicting patients undergoing dose-tapering. Longer-term observation and more flexible tapering approaches are anticipated to reveal favorable outcomes.
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Affiliation(s)
- Chen-Chung Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ming H. Hsieh
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yi-Ling Chien
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chih-Min Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yi-Ting Lin
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Tzung-Jeng Hwang
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Hai-Gwo Hwu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Department of Psychiatry, College of Medicine, National Taiwan University, Taipei, Taiwan
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Neufeld NH, Oliver LD, Mulsant BH, Alexopoulos GS, Hoptman MJ, Tani H, Marino P, Meyers BS, Rothschild AJ, Whyte EM, Bingham KS, Flint AJ, Voineskos AN. Effects of antipsychotic medication on functional connectivity in major depressive disorder with psychotic features. Mol Psychiatry 2023; 28:3305-3313. [PMID: 37258617 DOI: 10.1038/s41380-023-02118-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 05/02/2023] [Accepted: 05/11/2023] [Indexed: 06/02/2023]
Abstract
The effect of antipsychotic medication on resting state functional connectivity in major depressive disorder (MDD) is currently unknown. To address this gap, we examined patients with MDD with psychotic features (MDDPsy) participating in the Study of the Pharmacotherapy of Psychotic Depression II. All participants were treated with sertraline plus olanzapine and were subsequently randomized to continue sertraline plus olanzapine or be switched to sertraline plus placebo. Participants completed an MRI at randomization and at study endpoint (study completion at Week 36, relapse, or early termination). The primary outcome was change in functional connectivity measured within and between specified networks and the rest of the brain. The secondary outcome was change in network topology measured by graph metrics. Eighty-eight participants completed a baseline scan; 73 completed a follow-up scan, of which 58 were usable for analyses. There was a significant treatment X time interaction for functional connectivity between the secondary visual network and rest of the brain (t = -3.684; p = 0.0004; pFDR = 0.0111). There was no significant treatment X time interaction for graph metrics. Overall, functional connectivity between the secondary visual network and the rest of the brain did not change in participants who stayed on olanzapine but decreased in those switched to placebo. There were no differences in changes in network topology measures when patients stayed on olanzapine or switched to placebo. This suggests that olanzapine may stabilize functional connectivity, particularly between the secondary visual network and the rest of the brain.
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Affiliation(s)
- Nicholas H Neufeld
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | | | - Benoit H Mulsant
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - George S Alexopoulos
- Department of Psychiatry, Weill Cornell Medicine, Weill Cornell Medical College, Westchester Behavioral Health Center, White Plains, NY, USA
| | - Matthew J Hoptman
- Division of Clinical Research, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Hideaki Tani
- Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Patricia Marino
- Department of Psychiatry, Weill Cornell Medicine, Weill Cornell Medical College, Westchester Behavioral Health Center, White Plains, NY, USA
| | - Barnett S Meyers
- Department of Psychiatry, Weill Cornell Medicine, Weill Cornell Medical College, Westchester Behavioral Health Center, White Plains, NY, USA
| | - Anthony J Rothschild
- Department of Psychiatry, University of Massachusetts Chan Medical School and UMass Memorial Health Care, Worcester, MA, USA
| | - Ellen M Whyte
- Department of Psychiatry, University of Pittsburgh School of Medicine and UPMC Western Psychiatric Hospital, Pittsburgh, PA, USA
| | - Kathleen S Bingham
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Centre for Mental Health, University Health Network, Toronto, ON, Canada
| | - Alastair J Flint
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Centre for Mental Health, University Health Network, Toronto, ON, Canada
| | - Aristotle N Voineskos
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
- Centre for Addiction and Mental Health, Toronto, ON, Canada.
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Cui LB, Wang XY, Fu YF, Liu XF, Wei Y, Zhao SW, Gu YW, Fan JW, Wu WJ, Gong H, Lin BD, Yin H, Guan F, Chang X. Transcriptional level of inflammation markers associates with short-term brain structural changes in first-episode schizophrenia. BMC Med 2023; 21:250. [PMID: 37424013 PMCID: PMC10332052 DOI: 10.1186/s12916-023-02963-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023] Open
Abstract
BACKGROUND Inflammation has been implicated in the pathology of schizophrenia and may cause neuronal cell death and dendrite loss. Neuroimaging studies have highlighted longitudinal brain structural changes in patients with schizophrenia, yet it is unclear whether this is related to inflammation. We aim to address this question, by relating brain structural changes with the transcriptional profile of inflammation markers in the early stage of schizophrenia. METHODS Thirty-eight patients with first-episode schizophrenia and 51 healthy controls were included. High-resolution T1-weighted magnetic resonance imaging (MRI) and clinical assessments were performed at baseline and 2 ~ 6 months follow-up for all subjects. Changes in the brain structure were analyzed using surface-based morphological analysis and correlated with the expression of immune cells-related gene sets of interest reported by previous reviews. Transcriptional data were retrieved from the Allen Human Brain Atlas. Furthermore, we examined the brain structural changes and peripheral inflammation markers in association with behavioral symptoms and cognitive functioning in patients. RESULTS Patients exhibited accelerated cortical thickness decrease in the left frontal cortices, less decrease or an increase in the superior parietal lobule and right lateral occipital lobe, and increased volume in the bilateral pallidum, compared with controls. Changes in cortical thickness correlated with the transcriptional level of monocyte across cortical regions in patients (r = 0.54, p < 0.01), but not in controls (r = - 0.05, p = 0.76). In addition, cortical thickness change in the left superior parietal lobule positively correlated with changes in digital span-backward test scores in patients. CONCLUSIONS Patients with schizophrenia exhibit regional-specific cortical thickness changes in the prefrontal and parietooccipital cortices, which is related to their cognitive impairment. Inflammation may be an important factor contributing to cortical thinning in first-episode schizophrenia. Our findings suggest that the immunity-brain-behavior association may play a crucial role in the pathogenesis of schizophrenia.
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Affiliation(s)
- Long-Biao Cui
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China.
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China.
| | - Xian-Yang Wang
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Shu-Wan Zhao
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yue-Wen Gu
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jing-Wen Fan
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hengfen Gong
- School of Medicine, Shanghai Pudong New Area Mental Health Center, Tongji University, Shanghai, China
| | - Bochao Danae Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Fanglin Guan
- Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, China.
| | - Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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Perez-Rando M, Penades-Gomiz C, Martinez-Marin P, García-Martí G, Aguilar EJ, Escarti MJ, Grasa E, Corripio I, Sanjuan J, Nacher J. Volume alterations of the hippocampus and amygdala in patients with schizophrenia and persistent auditory hallucinations. REVISTA DE PSIQUIATRIA Y SALUD MENTAL 2023:S1888-9891(23)00014-9. [PMID: 37495479 DOI: 10.1016/j.rpsm.2023.05.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 12/05/2022] [Accepted: 05/24/2023] [Indexed: 07/28/2023]
Abstract
INTRODUCTION Auditory hallucinations (AH) are one of the most prevalent symptoms of schizophrenia. They might cause several brain alterations, especially changes in the volumes of hippocampus and amygdala, regions related to the relay and processing of auditory cues and emotional memories. MATERIAL AND METHODS We have recruited 41 patients with schizophrenia and persistent AH, 35 patients without AH, and 55 healthy controls. Using their MRIs, we have performed semiautomatic segmentations of the hippocampus and amygdala using Freesurfer. We have also performed bilateral correlations between the total PSYRATS score and the volumes of affected subregions and nuclei. RESULTS In the hippocampus, we found bilateral increases in the volume of its hippocampal fissure and decreases in the right fimbria in patients with and without AH. The volume of the right hippocampal tail and left head of the granule cell layer from the dentate gyrus were decreased in patients with AH. In the amygdala, we found its left total volume was shrunk, and there was a decrease of its left accessory basal nucleus in patients with AH. CONCLUSIONS We have detected volume alterations of different limbic structures likely due to the presence of AH. The volumes of the right hippocampal tail and left head of the granule cell layer from the dentate gyrus, and total volume of the amygdala and its accessory basal nucleus, were only affected in patients with AH. Bilateral volume alterations in the hippocampal fissure and right fimbria seem inherent of schizophrenia and due to traits not contemplated in our research.
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Affiliation(s)
- Marta Perez-Rando
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain; Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Institute of Research of the Clinic Hospital from Valencia (INCLIVA), Valencia, Spain.
| | - Carlota Penades-Gomiz
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain
| | - Pablo Martinez-Marin
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain
| | - Gracián García-Martí
- Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Quironsalud Hospital, Valencia, Spain
| | - Eduardo J Aguilar
- Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Psychiatry Unit, Faculty of Medicine, Universitat de València, Valencia, Spain
| | - Maria J Escarti
- Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Institute of Research of the Clinic Hospital from Valencia (INCLIVA), Valencia, Spain; Psychiatry Unit, Faculty of Medicine, Universitat de València, Valencia, Spain
| | - Eva Grasa
- Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Mental Health, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
| | - Iluminada Corripio
- Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Mental Health, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain; Mental Health and Psychiatry Department, Vic Hospital Consortium, Catalonia, Spain
| | - Julio Sanjuan
- Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Psychiatry Unit, Faculty of Medicine, Universitat de València, Valencia, Spain
| | - Juan Nacher
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain; Spanish National Network for Research in Mental Health (CIBERSAM), Madrid, Spain; Institute of Research of the Clinic Hospital from Valencia (INCLIVA), Valencia, Spain.
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Jiang S, Huang H, Zhou J, Li H, Duan M, Yao D, Luo C. Progressive trajectories of schizophrenia across symptoms, genes, and the brain. BMC Med 2023; 21:237. [PMID: 37400838 PMCID: PMC10318676 DOI: 10.1186/s12916-023-02935-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 06/12/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND Schizophrenia is characterized by complex psychiatric symptoms and unclear pathological mechanisms. Most previous studies have focused on the morphological changes that occur over the development of the disease; however, the corresponding functional trajectories remain unclear. In the present study, we aimed to explore the progressive trajectories of patterns of dysfunction after diagnosis. METHODS Eighty-six patients with schizophrenia and 120 healthy controls were recruited as the discovery dataset. Based on multiple functional indicators of resting-state brain functional magnetic resonance imaging, we conducted a duration-sliding dynamic analysis framework to investigate trajectories in association with disease progression. Neuroimaging findings were associated with clinical symptoms and gene expression data from the Allen Human Brain Atlas database. A replication cohort of patients with schizophrenia from the University of California, Los Angeles, was used as the replication dataset for the validation analysis. RESULTS Five stage-specific phenotypes were identified. A symptom trajectory was characterized by positive-dominated, negative ascendant, negative-dominated, positive ascendant, and negative surpassed stages. Dysfunctional trajectories from primary and subcortical regions to higher-order cortices were recognized; these are associated with abnormal external sensory gating and a disrupted internal excitation-inhibition equilibrium. From stage 1 to stage 5, the importance of neuroimaging features associated with behaviors gradually shifted from primary to higher-order cortices and subcortical regions. Genetic enrichment analysis identified that neurodevelopmental and neurodegenerative factors may be relevant as schizophrenia progresses and highlighted multiple synaptic systems. CONCLUSIONS Our convergent results indicate that progressive symptoms and functional neuroimaging phenotypes are associated with genetic factors in schizophrenia. Furthermore, the identification of functional trajectories complements previous findings of structural abnormalities and provides potential targets for drug and non-drug interventions in different stages of schizophrenia.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Mingjun Duan
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China.
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China.
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China.
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Hua JPY, Loewy RL, Stuart B, Fryer SL, Niendam TA, Carter CS, Vinogradov S, Mathalon DH. Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia. Psychiatry Res Neuroimaging 2023; 332:111653. [PMID: 37121090 PMCID: PMC10362971 DOI: 10.1016/j.pscychresns.2023.111653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/27/2023] [Accepted: 04/18/2023] [Indexed: 05/02/2023]
Abstract
Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.
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Affiliation(s)
- Jessica P Y Hua
- Sierra Pacific Mental Illness Research Education and Clinical Centers, San Francisco VA Medical Center, and the University of California, San Francisco, CA, United States; Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States; Department of Psychological Sciences, University of Missouri, Columbia, 65211, MO, United States
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States
| | - Barbara Stuart
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States
| | - Susanna L Fryer
- Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States
| | - Tara A Niendam
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, 95616, CA, United States
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, 95616, CA, United States
| | - Sophia Vinogradov
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, 55455, MN, United States
| | - Daniel H Mathalon
- Mental Health Service, San Francisco VA Medical Center, San Francisco, 94121, CA, United States; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, 94143, CA, United States.
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Abé C, Liberg B, Klahn AL, Petrovic P, Landén M. Mania-related effects on structural brain changes in bipolar disorder - a narrative review of the evidence. Mol Psychiatry 2023; 28:2674-2682. [PMID: 37147390 PMCID: PMC10615759 DOI: 10.1038/s41380-023-02073-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 04/12/2023] [Accepted: 04/14/2023] [Indexed: 05/07/2023]
Abstract
Cross-sectional neuroimaging studies show that bipolar disorder is associated with structural brain abnormalities, predominantly observed in prefrontal and temporal cortex, cingulate gyrus, and subcortical regions. However, longitudinal studies are needed to elucidate whether these abnormalities presage disease onset or are consequences of disease processes, and to identify potential contributing factors. Here, we narratively review and summarize longitudinal structural magnetic resonance imaging studies that relate imaging outcomes to manic episodes. First, we conclude that longitudinal brain imaging studies suggest an association of bipolar disorder with aberrant brain changes, including both deviant decreases and increases in morphometric measures. Second, we conclude that manic episodes have been related to accelerated cortical volume and thickness decreases, with the most consistent findings occurring in prefrontal brain areas. Importantly, evidence also suggests that in contrast to healthy controls, who in general show age-related cortical decline, brain metrics remain stable or increase during euthymic periods in bipolar disorder patients, potentially reflecting structural recovering mechanisms. The findings stress the importance of preventing manic episodes. We further propose a model of prefrontal cortical trajectories in relation to the occurrence of manic episodes. Finally, we discuss potential mechanisms at play, remaining limitations, and future directions.
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Affiliation(s)
- Christoph Abé
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Quantify Research, Stockholm, Sweden
| | - Benny Liberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Anna Luisa Klahn
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Predrag Petrovic
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Cognitive and Computational Neuropsychiatry, Karolinska Institutet, Stockholm, Sweden
- Center for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Landén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
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Liu H, Li W, Liu N, Tang J, Sun L, Xu J, Ji Y, Xie Y, Ding H, Ye Z, Yu C, Qin W. Structural covariances of prefrontal subregions selectively associate with dopamine-related gene coexpression and schizophrenia. Cereb Cortex 2023; 33:8035-8045. [PMID: 36935097 DOI: 10.1093/cercor/bhad096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/24/2023] [Accepted: 02/25/2023] [Indexed: 03/20/2023] Open
Abstract
Evidence highlights that dopamine (DA) system dysregulation and prefrontal cortex (PFC) dysfunction may underlie the pathophysiology of schizophrenia. However, the associations among DA genes, PFC morphometry, and schizophrenia have not yet been fully clarified. Based on the brain gene expression dataset from Allen Human Brain Atlas and structural magnetic resonance imaging data (NDIS = 1727, NREP = 408), we first identified 10 out of 22 PFC subregions whose gray matter volume (GMV) covariance profiles were reliably associated with their DA genes coexpression profiles, then four out of the identified 10 PFC subregions demonstrated abnormally increased GMV covariance with the hippocampus, insula, and medial frontal areas in schizophrenia patients (NCASE = 100; NCONTROL = 102). Moreover, based on a schizophrenia postmortem expression dataset, we found that the DA genes coexpression of schizophrenia was significantly reduced between the middle frontal gyrus and hippocampus, in which 21 DA genes showed significantly unsynchronized expression changes, and the 21 genes' brain expression were enriched in brain activity invoked by working memory, reward, speech production, and episodic memory. Our findings indicate the DA genes selectively regulate the structural covariance of PFC subregions by their coexpression profiles, which may underlie the disrupted GMV covariance and impaired cognitive functions in schizophrenia.
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Affiliation(s)
- Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Wei Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jie Tang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Lixin Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yuan Ji
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Hao Ding
- School of Medical Imaging, Tianjin Medical University, Tianjin 300070, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
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Demjaha A, Galderisi S, Glenthøj B, Arango C, Mucci A, Lawrence A, O'Daly O, Kempton M, Ciufolini S, Baandrup L, Ebdrup BH, Rodriguez-Jimenez R, Diaz-Marsa M, Díaz-Caneja CM, Winter van Rossum I, Kahn R, Dazzan P, McGuire P. Negative symptoms in First-Episode Schizophrenia related to morphometric alterations in orbitofrontal and superior temporal cortex: the OPTiMiSE study. Psychol Med 2023; 53:3471-3479. [PMID: 35197142 PMCID: PMC10277764 DOI: 10.1017/s0033291722000010] [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: 03/10/2021] [Revised: 12/20/2021] [Accepted: 01/04/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Negative symptoms are one of the most incapacitating features of Schizophrenia but their pathophysiology remains unclear. They have been linked to alterations in grey matter in several brain regions, but findings have been inconsistent. This may reflect the investigation of relatively small patient samples, and the confounding effects of chronic illness and exposure to antipsychotic medication. We sought to address these issues by investigating concurrently grey matter volumes (GMV) and cortical thickness (CTh) in a large sample of antipsychotic-naïve or minimally treated patients with First-Episode Schizophrenia (FES). METHODS T1-weighted structural MRI brain scans were acquired from 180 antipsychotic-naïve or minimally treated patients recruited as part of the OPTiMiSE study. The sample was stratified into subgroups with (N = 88) or without (N = 92) Prominent Negative Symptoms (PMN), based on PANSS ratings at presentation. Regional GMV and CTh in the two groups were compared using Voxel-Based Morphometry (VBM) and FreeSurfer (FS). Between-group differences were corrected for multiple comparisons via Family-Wise Error (FWE) and Monte Carlo z-field simulation respectively at p < 0.05 (2-tailed). RESULTS The presence of PMN symptoms was associated with larger left inferior orbitofrontal volume (p = 0.03) and greater CTh in the left lateral orbitofrontal gyrus (p = 0.007), but reduced CTh in the left superior temporal gyrus (p = 0.009). CONCLUSIONS The findings highlight the role of orbitofrontal and temporal cortices in the pathogenesis of negative symptoms of Schizophrenia. As they were evident in generally untreated FEP patients, the results are unlikely to be related to effects of previous treatment or illness chronicity.
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Affiliation(s)
- Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania Luigi Vanvitelli, Caserta, Italy
| | - Birthe Glenthøj
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Center Glostrup, University of Copenhagen, Copenhagen, Denmark
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health. Hospital General Universitario Gregorio Marañón. IiSGM, CIBERSAM. School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Armida Mucci
- Department of Psychiatry, University of Campania Luigi Vanvitelli, Caserta, Italy
| | - Andrew Lawrence
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Matthew Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Simone Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Lone Baandrup
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Center Glostrup, University of Copenhagen, Copenhagen, Denmark
| | - Bjørn H. Ebdrup
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Center Glostrup, University of Copenhagen, Copenhagen, Denmark
| | - Roberto Rodriguez-Jimenez
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health. Hospital General Universitario Gregorio Marañón. IiSGM, CIBERSAM. School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Maria Diaz-Marsa
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health. Hospital General Universitario Gregorio Marañón. IiSGM, CIBERSAM. School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Covadonga Martinez Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health. Hospital General Universitario Gregorio Marañón. IiSGM, CIBERSAM. School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | | | - Rene Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, Utrecht, Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paola Dazzan
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
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Li M, Deng W, Li Y, Zhao L, Ma X, Yu H, Li X, Meng Y, Wang Q, Du X, Sham PC, Palaniyappan L, Li T. Ameliorative patterns of grey matter in patients with first-episode and treatment-naïve schizophrenia. Psychol Med 2023; 53:3500-3510. [PMID: 35164887 PMCID: PMC10277763 DOI: 10.1017/s0033291722000058] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 12/30/2021] [Accepted: 01/05/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Grey matter (GM) reduction is a consistent observation in established late stages of schizophrenia, but patients in the untreated early stages of illness display an increase as well as a decrease in GM distribution relative to healthy controls (HC). The relative excess of GM may indicate putative compensatory responses, though to date its relevance is unclear. METHODS 343 first-episode treatment-naïve patients with schizophrenia (FES) and 342 HC were recruited. Multivariate source-based morphometry was performed to identify covarying 'networks' of grey matter concentration (GMC). Neurocognitive scores using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and symptom burden using the Positive and Negative Symptoms Scale (PANSS) were obtained. Bivariate linear relationships between GMC and cognition/symptoms were studied. RESULTS Compared to healthy subjects, FES had prominently lower GMC in two components; the first consists of the anterior insula, inferior frontal gyrus, anterior cingulate and the second component with the superior temporal gyrus, precuneus, inferior/superior parietal lobule, cuneus, and lingual gyrus. Higher GMC was seen in adjacent areas of the middle and superior temporal gyrus, middle frontal gyrus, inferior parietal cortex and putamen. Greater GMC of this component was associated with lower duration of untreated psychosis, less severe positive symptoms and better performance on cognitive tests. CONCLUSIONS In untreated stages of schizophrenia, both a distributed lower and higher GMC is observable. While the higher GMC is relatively modest, it occurs across frontoparietal, temporal and subcortical regions in association with reduced illness burden suggesting a compensatory role for higher GMC in the early stages of schizophrenia.
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Affiliation(s)
- Mingli Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Wei Deng
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yinfei Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Hua Yu
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaojing Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Yajing Meng
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xiangdong Du
- Suzhou Psychiatry Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu, China
| | - Pak Chung Sham
- Centre for Genomic Sciences and State Key Laboratory in Cognitive and Brain Sciences, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China
| | - Lena Palaniyappan
- Robarts Research Institute & The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada
- Lawson Health Research Institute, London, Ontario, Canada
| | - Tao Li
- Mental Health Center and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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Mısır E, Akay GG. Synaptic dysfunction in schizophrenia. Synapse 2023:e22276. [PMID: 37210696 DOI: 10.1002/syn.22276] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 04/25/2023] [Accepted: 05/07/2023] [Indexed: 05/22/2023]
Abstract
Schizophrenia is a chronic disease presented with psychotic symptoms, negative symptoms, impairment in the reward system, and widespread neurocognitive deterioration. Disruption of synaptic connections in neural circuits is responsible for the disease's development and progression. Because deterioration in synaptic connections results in the impaired effective processing of information. Although structural impairments of the synapse, such as a decrease in dendritic spine density, have been shown in previous studies, functional impairments have also been revealed with the development of genetic and molecular analysis methods. In addition to abnormalities in protein complexes regulating exocytosis in the presynaptic region and impaired vesicle release, especially, changes in proteins related to postsynaptic signaling have been reported. In particular, impairments in postsynaptic density elements, glutamate receptors, and ion channels have been shown. At the same time, effects on cellular adhesion molecular structures such as neurexin, neuroligin, and cadherin family proteins were detected. Of course, the confusing effect of antipsychotic use in schizophrenia research should also be considered. Although antipsychotics have positive and negative effects on synapses, studies indicate synaptic deterioration in schizophrenia independent of drug use. In this review, the deterioration in synapse structure and function and the effects of antipsychotics on the synapse in schizophrenia will be discussed.
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Affiliation(s)
- Emre Mısır
- Department of Psychiatry, Baskent University Faculty of Medicine, Ankara, Turkey
- Department of Interdisciplinary Neuroscience, Ankara University, Ankara, Turkey
| | - Güvem Gümüş Akay
- Department of Interdisciplinary Neuroscience, Ankara University, Ankara, Turkey
- Faculty of Medicine, Department of Physiology, Ankara University, Ankara, Turkey
- Brain Research Center (AÜBAUM), Ankara University, Ankara, Turkey
- Department of Cellular Neuroscience and Advanced Microscopic Neuroimaging, Neuroscience and Neurotechnology Center of Excellence (NÖROM), Ankara, Turkey
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Heidari Z, Mahmoudzadeh-Sagheb H, Shakiba M, Gorgich EAC. Brain Structural Changes in Schizophrenia Patients Compared to the Control: An MRI-based Cavalieri's Method. Basic Clin Neurosci 2023; 14:355-363. [PMID: 38077177 PMCID: PMC10700815 DOI: 10.32598/bcn.2021.3481.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 05/01/2021] [Accepted: 08/07/2021] [Indexed: 04/01/2024] Open
Abstract
INTRODUCTION Schizophrenia is a severe psychotic brain disorder. One of the potential mechanisms underlying this disease may be volumetric changes in some brain regions. The present study aimed to employ magnetic resonance imaging (MRI) to estimate and quantitatively analyze the brain of patients with schizophrenia compared to the controls. METHODS This case-control study was conducted on MRI scans of 20 patients with schizophrenia and 20 healthy controls in Zahedan City, Southeastern Iran. MRIs with 4 mm slice thickness and 5 mm intervals in coronal and sagittal planes were captured. Then, quantitative parameters, including volume and volume density of various brain regions, were estimated in both groups using Cavalieri's point counting method. Data analyses were performed using the Mann-Whitney U test. RESULTS The findings of this investigation revealed that volumes of gray matter, hippocampus, and gray/white matter in patients with schizophrenia were significantly lower than the controls (P<0.05). The volumes of lateral ventricles in patients with schizophrenia (36.60±4.32 mm3) were significantly higher than the healthy individuals (30.10±7.98 mm3). However, there were no statistically significant differences between the two groups regarding the changes in the brain's total volume, cerebral hemispheres, white matter, brain stem, cerebellum, and corpus callosum (P>0.05). CONCLUSION Volumetric estimations on brain MRI-based stereological technique can be helpful for elucidation of structural changes, following up the treatment trends, and evaluating the therapeutic situations in schizophrenia patients. Volumetric alternations in specific brain areas might be linked to cognitive impairments and the severity of symptoms in patients with schizophrenia. Further research is needed in this regard. HIGHLIGHTS Volumetric changes occur in certain regions of the brain of schizophrenia patients.Structural changes in the brain of schizophrenia patients are associated with the severity of clinical manifestations.A brain MRI-based stereological technique can clarify neuropathology and assess therapeutic efficiency in patients with schizophrenia. PLAIN LANGUAGE SUMMARY Schizophrenia is a severe neuropsychiatric disorder with worldwide prevalence that disrupts a person's social life. It's characterized by progressive neuroanatomical alterations in both gray and white matter in different brain regions and associated with changes in the structural and functioning of some critical brain circuits. Several factors have been suggested to be involved in the development and progression of the disease including alternations and disconnection in myelin, genetic factors, neurodegenerative process, neuroinflammation, neurodevelopmental deficiencies, the number of dopaminergic neurons and volumetric changes in different areas of the brain. It has shown that quantitative volumetric brain measurements on magnetic resonance imaging (MRI) scans in patients with neurodegenerative disease owing to selective regional atrophy are beneficial for clinicians to ascertain disease progression and to evaluate volume alternations and response to treatment. Thus, we investigated structural changes of the brain in schizophrenia patients on MR images using accurate Cavalieri's estimation and compared to healthy controls. The findings demonstrated that some structural changes occurs in various brain areas which involved in many critical roles in normal brain's functionality and connectivity. On the other hand, these changes are associated with cognitive impairments and the severity of clinical symptoms in patients with schizophrenia. It's appears that elucidation of the different pathways of various structural abnormalities related to schizophrenia is required to recognize and determine the role of discrete pathophysiological phenomena in mental illness development and progress.
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Affiliation(s)
- Zahra Heidari
- Infectious Diseases and Tropical Medicine Research Center, Research Institute of Cellular and Molecular Sciences in Infectious Diseases, Zahedan University of Medical Sciences, Zahedan, Iran
- Department of Histology, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran
| | - Hamidreza Mahmoudzadeh-Sagheb
- Infectious Diseases and Tropical Medicine Research Center, Research Institute of Cellular and Molecular Sciences in Infectious Diseases, Zahedan University of Medical Sciences, Zahedan, Iran
- Department of Histology, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran
| | - Mansour Shakiba
- Department of Neurology, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran
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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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Tasch G, Gøtzsche PC. Systematic violations of patients’ rights and safety: forced medication of a cohort of 30 patients in Alaska. PSYCHOSIS 2023. [DOI: 10.1080/17522439.2023.2183428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
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Masumo Y, Kanahara N, Kogure M, Yamasaki F, Nakata Y, Iyo M. Dopamine supersensitivity psychosis and delay of clozapine treatment in patients with treatment-resistant schizophrenia. Int Clin Psychopharmacol 2023; 38:102-109. [PMID: 36719338 DOI: 10.1097/yic.0000000000000442] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Both the underutilization of clozapine and treatment resistance of patients to clozapine are serious problems worldwide. Identifying clinical markers predicting response to clozapine would help clinicians more effectively utilize clozapine treatment. The present study retrospectively assessed dopamine supersensitivity psychosis (DSP) in addition to other measures such as age at disease onset and delay of clozapine introduction for a total of 47 treatment-resistant schizophrenia (TRS) patients. The response to clozapine was judged with CGI-C at 1 and 2 years from clozapine introduction. Results revealed that the DSP group tended to have a longer delay between designation of TRS and introduction of clozapine and continued to have slightly more severe psychopathology after treatment with clozapine, showing only slight improvement. The logistic regression analysis showed that the age at disease onset was the only significant indicator, predicting responsiveness to clozapine: patients with an onset age <20 years had a significantly better response to clozapine than patients with an onset age ≥20 years. The present study suggests that DSP might be related to a longer delay in clozapine introduction and the persistence of refractory symptoms despite clozapine treatment, whereas early age of disease onset might be related to a better response to clozapine.
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Affiliation(s)
- Yuto Masumo
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba
- Department of Psychiatry, Naoki-kai Isogaya Hospital, Ichihara
| | - Nobuhisa Kanahara
- Division of Medical Treatment and Rehabilitation, Center for Forensic Mental Health, Chiba University, Chiba
- Shirayuri-kai Ichihara Tsuruoka Hospital, Ichihara, Japan
| | - Masanobu Kogure
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba
| | - Fumiaki Yamasaki
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba
| | - Yusuke Nakata
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba
| | - Masaomi Iyo
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba
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46
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Chatterjee I, Chatterjee S. Investigating the symptomatic and morphological changes in the brain based on pre and post-treatment: A critical review from clinical to neuroimaging studies on schizophrenia. IBRO Neurosci Rep 2023. [DOI: 10.1016/j.ibneur.2023.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023] Open
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Howes OD, Cummings C, Chapman GE, Shatalina E. Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes. Neuropsychopharmacology 2023; 48:151-167. [PMID: 36056106 PMCID: PMC9700830 DOI: 10.1038/s41386-022-01426-x] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 08/03/2022] [Accepted: 08/05/2022] [Indexed: 11/09/2022]
Abstract
Over the last five decades, a large body of evidence has accrued for structural and metabolic brain alterations in schizophrenia. Here we provide an overview of these findings, focusing on measures that have traditionally been thought to reflect synaptic spine density or synaptic activity and that are relevant for understanding if there is lower synaptic density in the disorder. We conducted literature searches to identify meta-analyses or other relevant studies in patients with chronic or first-episode schizophrenia, or in people at high genetic or clinical risk for psychosis. We identified 18 meta-analyses including over 50,000 subjects in total, covering: structural MRI measures of gyrification index, grey matter volume, grey matter density and cortical thickness, neurite orientation dispersion and density imaging, PET imaging of regional glucose metabolism and magnetic resonance spectroscopy measures of N-acetylaspartate. We also review preclinical evidence on the relationship between ex vivo synaptic measures and structural MRI imaging, and PET imaging of synaptic protein 2A (SV2A). These studies show that schizophrenia is associated with lower grey matter volumes and cortical thickness, accelerated grey matter loss over time, abnormal gyrification patterns, and lower regional SV2A levels and metabolic markers in comparison to controls (effect sizes from ~ -0.11 to -1.0). Key regions affected include frontal, anterior cingulate and temporal cortices and the hippocampi. We identify several limitations for the interpretation of these findings in terms of understanding synaptic alterations. Nevertheless, taken with post-mortem findings, they suggest that schizophrenia is associated with lower synaptic density in some brain regions. However, there are several gaps in evidence, in particular whether SV2A findings generalise to other cohorts.
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Affiliation(s)
- Oliver D Howes
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- South London and Maudsley NHS Foundation Trust, London, UK.
| | - Connor Cummings
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- Clare Hall (College), University of Cambridge, Cambridge, UK
| | - George E Chapman
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Ekaterina Shatalina
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
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48
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Zoghbi AW, Lieberman JA, Girgis RR. The neurobiology of duration of untreated psychosis: a comprehensive review. Mol Psychiatry 2023; 28:168-190. [PMID: 35931757 PMCID: PMC10979514 DOI: 10.1038/s41380-022-01718-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 07/14/2022] [Accepted: 07/21/2022] [Indexed: 01/11/2023]
Abstract
Duration of untreated psychosis (DUP) is defined as the time from the onset of psychotic symptoms until the first treatment. Studies have shown that longer DUP is associated with poorer response rates to antipsychotic medications and impaired cognition, yet the neurobiologic correlates of DUP are poorly understood. Moreover, it has been hypothesized that untreated psychosis may be neurotoxic. Here, we conducted a comprehensive review of studies that have examined the neurobiology of DUP. Specifically, we included studies that evaluated DUP using a range of neurobiologic and imaging techniques and identified 83 articles that met inclusion and exclusion criteria. Overall, 27 out of the total 83 studies (32.5%) reported a significant neurobiological correlate with DUP. These results provide evidence against the notion of psychosis as structurally or functionally neurotoxic on a global scale and suggest that specific regions of the brain, such as temporal regions, may be more vulnerable to the effects of DUP. It is also possible that current methodologies lack the resolution needed to more accurately examine the effects of DUP on the brain, such as effects on synaptic density. Newer methodologies, such as MR scanners with stronger magnets, PET imaging with newer ligands capable of measuring subcellular structures (e.g., the PET ligand [11C]UCB-J) may be better able to capture these limited neuropathologic processes. Lastly, to ensure robust and replicable results, future studies of DUP should be adequately powered and specifically designed to test for the effects of DUP on localized brain structure and function with careful attention paid to potential confounds and methodological issues.
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Affiliation(s)
- Anthony W Zoghbi
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
- Institute of Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, 10032, USA.
- Office of Mental Health, New York State Psychiatric Institute, New York, NY, 10032, USA.
| | - Jeffrey A Lieberman
- Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Ragy R Girgis
- Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, 10032, USA.
- Office of Mental Health, New York State Psychiatric Institute, New York, NY, 10032, USA.
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49
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Sabe M, Chen C, Perez N, Solmi M, Mucci A, Galderisi S, Strauss GP, Kaiser S. Thirty years of research on negative symptoms of schizophrenia: A scientometric analysis of hotspots, bursts, and research trends. Neurosci Biobehav Rev 2023; 144:104979. [PMID: 36463972 DOI: 10.1016/j.neubiorev.2022.104979] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 11/19/2022] [Accepted: 11/28/2022] [Indexed: 12/02/2022]
Abstract
Research on negative symptoms of schizophrenia has received renewed interest since the 1980s. A scientometric analysis that objectively maps scientific knowledge, with changes in recent trends, is currently lacking. We searched the Web of Science Core Collection (WOSCC) on December 17, 2021 using relevant keywords. R-bibliometrix and CiteSpace were used to perform the analysis. We retrieved 27,568 references published between 1966 and 2022. An exponential rise in scientific interest was observed, with an average annual growth rate in publications of 16.56% from 1990 to 2010. The co-cited reference network that was retrieved presented 24 different clusters with a well-structured network (Q=0.7921; S=0.9016). Two distinct major research trends were identified: research on the conceptualization and treatment of negative symptoms. The latest trends in research on negative symptoms include evidence synthesis, nonpharmacological treatments, and computational psychiatry. Scientometric analyses provide a useful summary of changes in negative symptom research across time by identifying intellectual turning point papers and emerging trends. These results will be informative for systematic reviews, meta-analyses, and generating novel hypotheses.
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Affiliation(s)
- Michel Sabe
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Switzerland.
| | - Chaomei Chen
- College of Computing & Informatics, Drexel University, Philadelphia, PA, USA
| | - Natacha Perez
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Switzerland
| | - Marco Solmi
- Department of Psychiatry, University of Ottawa, Ontario, Canada; Department of Mental Health, The Ottawa Hospital, Ontario, Canada; Ottawa Hospital Research Institute (OHRI) Clinical Epidemiology Program University of Ottawa, Ontario, Ottawa; School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada; Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Armida Mucci
- Department of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy
| | | | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Switzerland
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50
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Kolomeets NS, Uranova NA. [Reduced numerical density of oligodendrocytes and oligodendrocyte clusters in the head of the caudate nucleus in schizophrenia]. Zh Nevrol Psikhiatr Im S S Korsakova 2023; 123:103-110. [PMID: 36719125 DOI: 10.17116/jnevro2023123011103] [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: 02/01/2023]
Abstract
OBJECTIVE Morphometric estimation of the numerical density of oligodendrocytes (NcOl) and numerical density of oligodendrocyte clusters (NvOlC) in the rostral part of the caudate head nucleus associated with the cortical regions of the default network in the norm and in schizophrenia. MATERIAL AND METHODS NcOl and NvOlC were determined in the gray matter of the rostral part of the head of the caudate nucleus in Nissl-stained sections using optical dissector in postmortem brains in 18 schizophrenia and 18 healthy control cases. RESULTS The NvOl (-20%, p<0.001) and NvOlC (-28%, p<0.001) were decreased in the schizophrenia group as compared to the control groups. The NvOl correlated with the NvOlC (R≥0.88, p<0.001) in both groups while a lack of correlations was previously found in the central part of the caudate head. CONCLUSION The detected deficits of the NcOl and NvOlC is an agreement with prominent suppressing of cortico-striatal connections and reduced density of gray matter in this part of the caudate in schizophrenia. The differences in the pattern of correlations as compared to the central part of this structure might be associated with the specific features of functional activity of default-mode and fronto-parietal networks associated with these parts of caudate nucleus.
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Affiliation(s)
- N S Kolomeets
- Federal State Budgetary Scientific Institution Mental Health Research Center, Moscow, Russia
| | - N A Uranova
- Federal State Budgetary Scientific Institution Mental Health Research Center, Moscow, Russia
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