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Weidenauer A, Sauerzopf U, Bauer M, Bum C, Diendorfer C, Dajic I, Bartova L, Kastner A, Bamminger K, Nics L, Philippe C, Hacker M, Rujescu D, Wadsak W, Praschak-Rieder N, Willeit M. Amphetamine-Induced Dopamine Release Predicts 1-Year Outcome in First-Episode Psychosis: A Naturalistic Observation. Schizophr Bull 2024:sbae111. [PMID: 39137162 DOI: 10.1093/schbul/sbae111] [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: 08/15/2024]
Abstract
BACKGROUND AND HYPOTHESIS The dopamine theory of schizophrenia suggests that antipsychotics alleviate symptoms by blocking dopamine D2/3 receptors, yet a significant subset of patients does not respond adequately to treatment. To investigate potential predictors, we evaluated d-amphetamine-induced dopamine release and 1-year clinical outcomes in 21 antipsychotic-naive patients with first-episode schizophrenia. STUDY DESIGN Twenty-one antipsychotic-naive patients (6 female) underwent dopamine D2/3 receptor radioligand [11C]-(+)-PHNO positron emission tomography. For estimating dopamine release, scans were performed with and without d-amphetamine pretreatment. The Positive and Negative Syndrome Scale was performed at regular intervals over 1 year while receiving treatment in a naturalistic setting (Clinical Trial Registry: EUDRACT 2010-019586-29). STUDY RESULTS A group analysis revealed no significant differences in d-amphetamine-induced dopamine release between patients with or without clinically significant improvement. However, d-amphetamine-induced dopamine release in ventral striatum was significantly associated with reductions in positive symptoms (r = 0.54, P = .04; uncorrected P-values); release in globus pallidus correlated with a decrease in PANSS negative (r = 0.58, P = .02), general (r = 0.53, P = .04), and total symptom scores (r = 0.063, P = .01). Higher dopamine release in substantia nigra/ventral tegmental area predicted larger reductions in general symptoms (r = 0.51, P = .05). Post-amphetamine binding in putamen correlated positively with negative symptom scores at baseline (r = 0.66, P = .005) and throughout all follow-up visits. CONCLUSIONS These exploratory results support a relationship between d-amphetamine-induced dopamine release and the severity and persistence of symptoms during the first year of psychosis.
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Affiliation(s)
- Ana Weidenauer
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
- Douglas Research Centre, Clinical and Translational Sciences Lab, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Ulrich Sauerzopf
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Martin Bauer
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
- Department of Clinical Pharmacology, Medical University of Vienna, Austria
- Psychosocial Services in Vienna, Vienna, Austria
| | - Carina Bum
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Cornelia Diendorfer
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Irena Dajic
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Lucie Bartova
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Alina Kastner
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Karsten Bamminger
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Austria
| | - Lukas Nics
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Austria
| | - Cecile Philippe
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Austria
| | - Dan Rujescu
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Wadsak
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Austria
- Center for Biomarker Research in Medicine CBmed, Graz, Austria
| | - Nicole Praschak-Rieder
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Matthäus Willeit
- Department of Psychiatry and Psychotherapy, Division of General Psychiatry, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
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2
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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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3
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Wang M, Barker PB, Cascella NG, Coughlin JM, Nestadt G, Nucifora FC, Sedlak TW, Kelly A, Younes L, Geman D, Palaniyappan L, Sawa A, Yang K. Longitudinal changes in brain metabolites in healthy controls and patients with first episode psychosis: a 7-Tesla MRS study. Mol Psychiatry 2023; 28:2018-2029. [PMID: 36732587 PMCID: PMC10394114 DOI: 10.1038/s41380-023-01969-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 01/13/2023] [Accepted: 01/17/2023] [Indexed: 02/04/2023]
Abstract
Seven Tesla magnetic resonance spectroscopy (7T MRS) offers a precise measurement of metabolic levels in the human brain via a non-invasive approach. Studying longitudinal changes in brain metabolites could help evaluate the characteristics of disease over time. This approach may also shed light on how the age of study participants and duration of illness may influence these metabolites. This study used 7T MRS to investigate longitudinal patterns of brain metabolites in young adulthood in both healthy controls and patients. A four-year longitudinal cohort with 38 patients with first episode psychosis (onset within 2 years) and 48 healthy controls was used to examine 10 brain metabolites in 5 brain regions associated with the pathophysiology of psychosis in a comprehensive manner. Both patients and controls were found to have significant longitudinal reductions in glutamate in the anterior cingulate cortex (ACC). Only patients were found to have a significant decrease over time in γ-aminobutyric acid, N-acetyl aspartate, myo-inositol, total choline, and total creatine in the ACC. Together we highlight the ACC with dynamic changes in several metabolites in early-stage psychosis, in contrast to the other 4 brain regions that also are known to play roles in psychosis. Meanwhile, glutathione was uniquely found to have a near zero annual percentage change in both patients and controls in all 5 brain regions during a four-year follow-up in young adulthood. Given that a reduction of the glutathione in the ACC has been reported as a feature of treatment-refractory psychosis, this observation further supports the potential of glutathione as a biomarker for this subset of patients with psychosis.
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Affiliation(s)
- Min Wang
- Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Peter B Barker
- Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Nicola G Cascella
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jennifer M Coughlin
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Gerald Nestadt
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Frederick C Nucifora
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas W Sedlak
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alexandra Kelly
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Laurent Younes
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Donald Geman
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Lena Palaniyappan
- Robarts Research Institution, University of Western Ontario, London, ON, Canada
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Akira Sawa
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Kun Yang
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Brandl F, Knolle F, Avram M, Leucht C, Yakushev I, Priller J, Leucht S, Ziegler S, Wunderlich K, Sorg C. Negative symptoms, striatal dopamine and model-free reward decision-making in schizophrenia. Brain 2023; 146:767-777. [PMID: 35875972 DOI: 10.1093/brain/awac268] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 06/13/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
Negative symptoms, such as lack of motivation or social withdrawal, are highly prevalent and debilitating in patients with schizophrenia. Underlying mechanisms of negative symptoms are incompletely understood, thereby preventing the development of targeted treatments. We hypothesized that in patients with schizophrenia during psychotic remission, impaired influences of both model-based and model-free reward predictions on decision-making ('reward prediction influence', RPI) underlie negative symptoms. We focused on psychotic remission, because psychotic symptoms might confound reward-based decision-making. Moreover, we hypothesized that impaired model-based/model-free RPIs depend on alterations of both associative striatum dopamine synthesis and storage (DSS) and executive functioning. Both factors influence RPI in healthy subjects and are typically impaired in schizophrenia. Twenty-five patients with schizophrenia with pronounced negative symptoms during psychotic remission and 24 healthy controls were included in the study. Negative symptom severity was measured by the Positive and Negative Syndrome Scale negative subscale, model-based/model-free RPI by the two-stage decision task, associative striatum DSS by 18F-DOPA positron emission tomography and executive functioning by the symbol coding task. Model-free RPI was selectively reduced in patients and associated with negative symptom severity as well as with reduced associative striatum DSS (in patients only) and executive functions (both in patients and controls). In contrast, model-based RPI was not altered in patients. Results provide evidence for impaired model-free reward prediction influence as a mechanism for negative symptoms in schizophrenia as well as for reduced associative striatum dopamine and executive dysfunction as relevant factors. Data suggest potential treatment targets for patients with schizophrenia and pronounced negative symptoms.
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Affiliation(s)
- Felix Brandl
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, 81675, Germany
| | - Franziska Knolle
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,Department of Psychiatry, University of Cambridge, Cambridge CB20SZ, UK
| | - Mihai Avram
- Translational Psychiatry, Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, 23538, Germany
| | - Claudia Leucht
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, 81675, Germany
| | - Igor Yakushev
- Department of Nuclear Medicine, School of Medicine, Technical University of Munich, Munich, 81675, Germany
| | - Josef Priller
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,Neuropsychiatry, Charité-Universitätsmedizin Berlin, and DZNE, Berlin, 10117, Germany.,UK DRI at University of Edinburgh, Edinburgh EH16 4SB, UK.,IoPPN, King's College London, London SE5 8AF, UK
| | - Stefan Leucht
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,Department of Psychosis studies, King's College London, London, UK
| | - Sibylle Ziegler
- Department of Nuclear Medicine, Ludwig-Maximilians University Munich, Munich, 81377, Germany
| | - Klaus Wunderlich
- Department of Psychology, Ludwig-Maximilians University Munich, Munich, 81377, Germany
| | - Christian Sorg
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, 81675, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, 81675, Germany
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5
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Wada M, Noda Y, Iwata Y, Tsugawa S, Yoshida K, Tani H, Hirano Y, Koike S, Sasabayashi D, Katayama H, Plitman E, Ohi K, Ueno F, Caravaggio F, Koizumi T, Gerretsen P, Suzuki T, Uchida H, Müller DJ, Mimura M, Remington G, Grace AA, Graff-Guerrero A, Nakajima S. Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment. Mol Psychiatry 2022; 27:2950-2967. [PMID: 35444257 DOI: 10.1038/s41380-022-01572-0] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/31/2022] [Accepted: 04/07/2022] [Indexed: 12/13/2022]
Abstract
Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.
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Affiliation(s)
- Masataka Wada
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yusuke Iwata
- Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Kazunari Yoshida
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Hideaki Tani
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan.,Neural Dynamics Laboratory, Research Service, VA Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Haruyuki Katayama
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Eric Plitman
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Fumihiko Ueno
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Fernando Caravaggio
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Teruki Koizumi
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Department of Psychiatry, National Hospital Organization Shimofusa Psychiatric Medical Center, Chiba, Japan
| | - Philip Gerretsen
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Takefumi Suzuki
- Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Daniel J Müller
- Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Gary Remington
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Anthony A Grace
- Departments of Neuroscience, Psychiatry and Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ariel Graff-Guerrero
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan. .,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
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6
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Rubio JM, Kane JM. The pharmacological treatment of schizophrenia: How far have we come? PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2022; 1:e13. [PMID: 38868633 PMCID: PMC11114354 DOI: 10.1002/pcn5.13] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 04/11/2022] [Accepted: 04/13/2022] [Indexed: 06/14/2024]
Abstract
Schizophrenia is a chronic and often severe mental disorder for which antipsychotic drugs are the cornerstone of treatment. Although the essential mechanism of action of these drugs has not changed much since they were first discovered in the 1950s, there have been numerous advances in the context in which these drugs are prescribed, as well as in the considerations for their optimal use. In this review, we summarize five selected issues in which the psychopharmacological treatment of schizophrenia has most evolved. Namely, these are the shift of outcomes of interest from symptoms to recovery, the development of stratified approaches to select the most appropriate treatment for each individual, the recognition of treatment nonadherence as a critical factor determining outcomes, the recommendations for maintenance treatment, and, finally, the promise of new antipsychotic compounds that innovate in their mechanisms of action, improving efficacy/safety profiles. Finally, we discuss how some of these advances have already delivered to improved outcomes in the real world, whereas others have demonstrated efficacy under optimal circumstances yet have not been translated into better outcomes in the community. Thus, the road ahead includes both identifying novel treatments that engage the psychopathology of the illness and improve the efficacy/tolerability profile of currently available agents, as well as developing interventions that mitigate the barriers for the use of novel interventions, some of them already existing, in the real world.
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Affiliation(s)
- Jose M. Rubio
- Donald and Barbara Zucker School of Medicine at Hofstra—Northwell, Feinstein Institutes of Medical Research—Institute of Behavioral ScienceZucker Hillside Hospital—Northwell HealthGlen OaksNYUnited States
| | - John M. Kane
- Donald and Barbara Zucker School of Medicine at Hofstra—Northwell, Feinstein Institutes of Medical Research—Institute of Behavioral ScienceZucker Hillside Hospital—Northwell HealthGlen OaksNYUnited States
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7
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Schoretsanitis G, Kane JM, Correll CU, Rubio JM. Predictors of Lack of Relapse After Random Discontinuation of Oral and Long-acting Injectable Antipsychotics in Clinically Stabilized Patients with Schizophrenia: A Re-analysis of Individual Participant Data. Schizophr Bull 2022; 48:296-306. [PMID: 34355232 PMCID: PMC8886604 DOI: 10.1093/schbul/sbab091] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
OBJECTIVE To quantify the risk and predictors of relapse among individuals with schizophrenia randomly withdrawn from antipsychotic maintenance treatment. METHODS We re-analyzed time-to-event and baseline predictors from placebo arms in five placebo-controlled randomized trials of antipsychotics (n = 688 individuals; 173 stabilized on oral antipsychotic [OAP] and 515 on long-acting injectables [LAI]) for relapse-prevention available in the Yale Open Data Access repository. Using a survival and Cox-proportional hazards regression analyses, we estimated survival rates of "relapse-free" individuals by the end of follow-up (median = 118 days, IQR = 52.0-208.0), the rate of study-confirmed relapse, and adjusted hazard ratios (aHR, 95% confidence intervals [CI]) associated with baseline predictors. We also estimated these parameters for individuals followed for >5 half-lives of the stabilizing antipsychotic, and studied predictors of "rebound psychosis" in OAP-stabilized participants, defined as occurring within 30 days of antipsychotic withdrawal. RESULTS 29.9% (95%CI = 23.2-38.5) remained relapse-free by the end of follow-up, 11.1% (95%CI = 5.65-21.9) among those OAP-stabilized, 36.4% (95%CI = 28.4-46.7) among those LAI-stabilized. The study-confirmed relapse rate was 45.2%, 62.4% among those OAP-stabilized and 39.4% among those LAI-stabilized. Predictors of relapse included smoking (aHR = 1.54, 95%CI = 1.19-2.00), female sex (aHR = 1.37, 95%CI = 1.08-1.79), and having been stabilized on OAPs vs LAIs (aHR = 3.56, 95%CI = 2.68-4.72). Greater risk of relapse on OAP persisted even after sufficient time had elapsed to clear antipsychotic plasma level among LAI-stabilized (aHR = 5.0, 95%CI = 3.5-7.1). "Rebound psychosis" did not show predictors. CONCLUSIONS AND RELEVANCE Our results corroborate the high relapse risk following antipsychotic withdrawal after symptom stabilization with limited patient-related predictors of safe treatment discontinuation. Stabilization with LAIs reduces the short-/medium-term relapse risk.
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Affiliation(s)
- Georgios Schoretsanitis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
- Department of Psychiatry, Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - John M Kane
- Department of Psychiatry, Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Christoph U Correll
- Department of Psychiatry, Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jose M Rubio
- Department of Psychiatry, Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
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8
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Yang K, Longo L, Narita Z, Cascella N, Nucifora FC, Coughlin JM, Nestadt G, Sedlak TW, Mihaljevic M, Wang M, Kenkare A, Nagpal A, Sethi M, Kelly A, Di Carlo P, Kamath V, Faria A, Barker P, Sawa A. A multimodal study of a first episode psychosis cohort: potential markers of antipsychotic treatment resistance. Mol Psychiatry 2022; 27:1184-1191. [PMID: 34642460 PMCID: PMC9001745 DOI: 10.1038/s41380-021-01331-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 09/17/2021] [Accepted: 09/29/2021] [Indexed: 11/13/2022]
Abstract
Treatment resistant (TR) psychosis is considered to be a significant cause of disability and functional impairment. Numerous efforts have been made to identify the clinical predictors of TR. However, the exploration of molecular and biological markers is still at an early stage. To understand the TR condition and identify potential molecular and biological markers, we analyzed demographic information, clinical data, structural brain imaging data, and molecular brain imaging data in 7 Tesla magnetic resonance spectroscopy from a first episode psychosis cohort that includes 136 patients. Age, gender, race, smoking status, duration of illness, and antipsychotic dosages were controlled in the analyses. We found that TR patients had a younger age at onset, more hospitalizations, more severe negative symptoms, a reduction in the volumes of the hippocampus (HP) and superior frontal gyrus (SFG), and a reduction in glutathione (GSH) levels in the anterior cingulate cortex (ACC), when compared to non-TR patients. The combination of multiple markers provided a better classification between TR and non-TR patients compared to any individual marker. Our study shows that ACC-GSH, HP and SFG volumes, and age at onset, could potentially be biomarkers for TR diagnosis, while hospitalization and negative symptoms could be used to evaluate the progression of the disease. Multimodal cohorts are essential in obtaining a comprehensive understanding of brain disorders.
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Affiliation(s)
- Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Luisa Longo
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Zui Narita
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Nicola Cascella
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Frederick C Nucifora
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Jennifer M Coughlin
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Gerald Nestadt
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Thomas W Sedlak
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Marina Mihaljevic
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Min Wang
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Anshel Kenkare
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Anisha Nagpal
- Department of Public Health Studies, Johns Hopkins University Zanvyl Krieger School of Arts and Sciences, Baltimore, MD, 21218, USA
| | - Mehk Sethi
- Department of Applied Math and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, 21218, USA
| | - Alexandra Kelly
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Pasquale Di Carlo
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Vidyulata Kamath
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Andreia Faria
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Peter Barker
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, 21205, USA
| | - Akira Sawa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
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9
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Sasabayashi D, Takayanagi Y, Takahashi T, Furuichi A, Kobayashi H, Noguchi K, Suzuki M. Increased brain gyrification and subsequent relapse in patients with first-episode schizophrenia. Front Psychiatry 2022; 13:937605. [PMID: 36032231 PMCID: PMC9406142 DOI: 10.3389/fpsyt.2022.937605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 06/30/2022] [Indexed: 11/13/2022] Open
Abstract
Most schizophrenia patients experience psychotic relapses, which may compromise long-term outcome. However, it is difficult to objectively assess the actual risk of relapse for each patient as the biological changes underlying relapse remain unknown. The present study used magnetic resonance imaging (MRI) to investigate the relationship between brain gyrification pattern and subsequent relapse in patients with first-episode schizophrenia. The subjects consisted of 19 patients with and 33 patients without relapse during a 3-year clinical follow-up after baseline MRI scanning. Using FreeSurfer software, we compared the local gyrification index (LGI) between the relapsed and non-relapsed groups. In the relapsed group, we also explored the relationship among LGI and the number of relapses and time to first relapse after MRI scanning. Relapsed patients exhibited a significantly higher LGI in the bilateral parietal and left occipital areas than non-relapsed patients. In addition, the time to first relapse was negatively correlated with LGI in the right inferior temporal cortex. These findings suggest that increased LGI in the temporo-parieto-occipital regions in first-episode schizophrenia patients may be a potential prognostic biomarker that reflects relapse susceptibility in the early course of the illness.
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Affiliation(s)
- Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Arisawabashi Hospital, Toyama, Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Haruko Kobayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Kyo Noguchi
- Department of Radiology, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
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10
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Effect of add-on alpha lipoic acid on psychopathology in patients with treatment-resistant schizophrenia: a pilot randomized double-blind placebo-controlled trial. Psychopharmacology (Berl) 2022; 239:3525-3535. [PMID: 36069950 PMCID: PMC9449282 DOI: 10.1007/s00213-022-06225-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 08/25/2022] [Indexed: 11/16/2022]
Abstract
RATIONALE Alpha lipoic acid is known to reverse NMDA receptor hypofunction in addition to dopamine receptor blockade activity. It also enhances neurotrophic factors and has antioxidant potential. These properties combined together may be beneficial for treatment-resistant schizophrenia (TRS). OBJECTIVES This study evaluates the effect of alpha lipoic acid (ALA) on psychopathological scores (positive, negative, cognitive), neurotrophic factors and oxidative stress in TRS. METHODS A pilot randomized double-blind placebo-controlled parallel design trial was conducted in 20 patients with TRS. After initial screening, participants were randomized into test (add-on ALA) and control (add-on placebo) groups. After recruitment, clinical evaluations with scale for assessment of positive symptoms and negative symptoms (SAPS and SANS), schizophrenia cognitive rating scale (SCoRS), UKU side effect rating scale were done. Serum levels of BDNF, MDA, and GSH were estimated. Patients were followed up for 8 weeks, and clinical and biochemical evaluations were repeated. Adherence to medication was evaluated at follow-up. RESULTS A significantly greater improvement was found in SANS score in the test group when compared to control (Mann-Whitney U = 17.0; p = 0.021), whereas there was no significant improvement in SAPS score (Mann-Whitney U = 41.5; p = 0.780). A significant increase in BDNF levels was observed in the control group when compared to ALA (U = 20.0; p = 0.041). No significant differences were found between the test and control groups in serum MDA (U = 30.0; p = 0.221), serum GSH (U = 40.0; p = 0.683), and medication adherence rating scale (MARS) scores (U = 44.0; p = 0.934). CONCLUSIONS ALA supplementation improved psychopathology and decreased oxidative stress in patients with TRS. This study thus shows the potential of adjunctive ALA in TRS. TRIAL REGISTRATION The study was prospectively registered in Clinical Trial Registry of India (CTRI/2020/03/023707 dated 02.03.2020).
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11
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Schulz J, Zimmermann J, Sorg C, Menegaux A, Brandl F. Magnetic resonance imaging of the dopamine system in schizophrenia - A scoping review. Front Psychiatry 2022; 13:925476. [PMID: 36203848 PMCID: PMC9530597 DOI: 10.3389/fpsyt.2022.925476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 07/08/2022] [Indexed: 11/30/2022] Open
Abstract
For decades, aberrant dopamine transmission has been proposed to play a central role in schizophrenia pathophysiology. These theories are supported by human in vivo molecular imaging studies of dopamine transmission, particularly positron emission tomography. However, there are several downsides to such approaches, for example limited spatial resolution or restriction of the measurement to synaptic processes of dopaminergic neurons. To overcome these limitations and to measure complementary aspects of dopamine transmission, magnetic resonance imaging (MRI)-based approaches investigating the macrostructure, metabolism, and connectivity of dopaminergic nuclei, i.e., substantia nigra pars compacta and ventral tegmental area, can be employed. In this scoping review, we focus on four dopamine MRI methods that have been employed in patients with schizophrenia so far: neuromelanin MRI, which is thought to measure long-term dopamine function in dopaminergic nuclei; morphometric MRI, which is assumed to measure the volume of dopaminergic nuclei; diffusion MRI, which is assumed to measure fiber-based structural connectivity of dopaminergic nuclei; and resting-state blood-oxygenation-level-dependent functional MRI, which is thought to measure functional connectivity of dopaminergic nuclei based on correlated blood oxygenation fluctuations. For each method, we describe the underlying signal, outcome measures, and downsides. We present the current state of research in schizophrenia and compare it to other disorders with either similar (psychotic) symptoms, i.e., bipolar disorder and major depressive disorder, or dopaminergic abnormalities, i.e., substance use disorder and Parkinson's disease. Finally, we discuss overarching issues and outline future research questions.
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Affiliation(s)
- Julia Schulz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Juliana Zimmermann
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Sorg
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
| | - Aurore Menegaux
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Felix Brandl
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
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12
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Rubio JM, Malhotra AK, Kane JM. Towards a framework to develop neuroimaging biomarkers of relapse in schizophrenia. Behav Brain Res 2021; 402:113099. [PMID: 33417996 DOI: 10.1016/j.bbr.2020.113099] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 12/16/2020] [Accepted: 12/27/2020] [Indexed: 12/31/2022]
Abstract
Schizophrenia is a chronic disorder that often requires long-term relapse-prevention treatment. This treatment is effective for most individuals, yet approximately 20-30 % of them may still relapse despite confirmed adherence. Alternatively, for about 15 % it may be safe to discontinue medications over the long term, but since there are no means to identify who those individuals will be, the recommendation is that all individuals receive long-term relapse-prevention treatment with antipsychotic maintenance. Thus, the current approach to prevent relapse in schizophrenia may be suboptimal for over one third of individuals, either by being insufficient to protect against relapse, or by unnecessarily exposing them to medication side effects. There is great need to identify biomarkers of relapse in schizophrenia to stratify treatment according to the risk and develop therapeutics targeting its pathophysiology. In order to develop a line of research that meets those needs, it is necessary to create a framework by identifying the challenges to this type of study as well as potential areas for biomarker identification and development. In this manuscript we review the literature to create such a framework.
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Affiliation(s)
- Jose M Rubio
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA; Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA; The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA.
| | - Anil K Malhotra
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA; Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA; The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
| | - John M Kane
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA; Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA; The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
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