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Li Y, Zhu M, Dong Y, Liu N, Wang X, Yang B, Li Z, Li S. Immunoinflammatory features and cognitive function in treatment-resistant schizophrenia: unraveling distinct patterns in clozapine-resistant patients. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01885-x. [PMID: 39196353 DOI: 10.1007/s00406-024-01885-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: 01/23/2024] [Accepted: 08/13/2024] [Indexed: 08/29/2024]
Abstract
Patients with treatment-resistant schizophrenia (TRS), particularly those resistant to clozapine (CTRS), pose a clinical challenge due to limited response to standard antipsychotic treatments. Inflammatory factors like tumor necrosis factor-alpha (TNF-α), interleukin 2 (IL-2), and interleukin 6 (IL-6) are implicated in schizophrenia's pathophysiology. Our study examines cognitive function, psychopathological symptoms and inflammatory factors in TRS patients, focusing on differences between CTRS and non-CTRS individuals, as well as healthy controls. A cohort of 115 TRS patients and 84 healthy controls were recruited, assessing IL-2, IL-6 and TNF-α. The Positive and Negative Syndrome Scale (PANSS) was applied to assess psychopathological symptoms, while the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was applied to assess cognitive functioning. CTRS patients showed lower visuospatial constructional score (p = 0.015), higher PANSS scores, higher levels of IL-2 and reduced TNF-α than non-CTRS patients (p < 0.05). Notably, IL-2 was independently associated with psychopathology symptoms in CTRS patients (Beta = 0.268, t = 2.075, p = 0.042), while IL-6 was associated with psychopathology symptoms in non-CTRS patients (Beta = - 0.327, t = - 2.109, p = 0.042). Sex-specific analysis in CTRS patients revealed IL-2 associations with PANSS total and positive symptoms in females, and TNF-α associations with PANSS positive symptoms in males. Furthermore, IL-2, IL-6, and TNF-α displayed potential diagnostic value in TRS patients and CTRS patients (p < 0.05). Clozapine‑resistant symptoms represent an independent endophenotype in schizophrenia with distinctive immunoinflammatory characteristics, potentially influenced by sex.
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Affiliation(s)
- Yanzhe Li
- Tianjin Anding Hospital, Institute of Mental Health, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
- Psychoneuromodulation Center, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
| | - Minghuan Zhu
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, 200124, China
| | - Yeqing Dong
- Tianjin Anding Hospital, Institute of Mental Health, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
- Psychoneuromodulation Center, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
| | - Nannan Liu
- Tianjin Anding Hospital, Institute of Mental Health, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
- Psychoneuromodulation Center, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
| | - Xinxu Wang
- Tianjin Anding Hospital, Institute of Mental Health, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
- Psychoneuromodulation Center, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China
| | - Bing Yang
- Department of Cell Biology, College of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Zezhi Li
- Department of Nutritional and Metabolic Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Mingxin Road #36, Liwan District, Guangzhou, 510370, China.
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China.
- Jiangsu Key Laboratory of Neurodegeneration, Nanjing Medical University, Nanjing, China.
| | - Shen Li
- Tianjin Anding Hospital, Institute of Mental Health, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China.
- Psychoneuromodulation Center, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, No. 13, Liulin Road, Hexi District, Tianjin, 300222, China.
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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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Cilia BJ, Eratne D, Wannan C, Malpas C, Janelidze S, Hansson O, Everall I, Bousman C, Thomas N, Santillo AF, Velakoulis D, Pantelis C. Associations between structural brain changes and blood neurofilament light chain protein in treatment-resistant schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.07.24305362. [PMID: 38645076 PMCID: PMC11030485 DOI: 10.1101/2024.04.07.24305362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background and Hypothesis Around 30% of people with schizophrenia are refractory to antipsychotic treatment (treatment-resistant schizophrenia; TRS). While abnormal structural neuroimaging findings, in particular volume and thickness reductions, are often observed in schizophrenia, it is anticipated that biomarkers of neuronal injury like neurofilament light chain protein (NfL) can improve our understanding of the pathological basis underlying schizophrenia. The current study aimed to determine whether people with TRS demonstrate different associations between plasma NfL levels and regional cortical thickness reductions compared with controls. Study Design Measurements of plasma NfL and cortical thickness were obtained from 39 individuals with TRS, and 43 healthy controls. T1-weighted magnetic resonance imaging sequences were obtained and processed via FreeSurfer. General linear mixed models adjusting for age and weight were estimated to determine whether the interaction between diagnostic group and plasma NfL level predicted lower cortical thickness across frontotemporal structures and the insula. Study Results Significant (false discovery rate corrected) cortical thinning of the left ( p = 0.001, η 2p = 0.104) and right ( p < 0.001, η 2 = 0.167) insula was associated with higher levels of plasma NfL in TRS, but not in healthy controls. Conclusions The association between regional thickness reduction of the insula bilaterally and plasma NfL may reflect a neurodegenerative process during the course of TRS. The findings of the present study suggest that some level of cortical degeneration localised to the bilateral insula may exist in people with TRS, which is not observed in the normal population.
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Porgalı Zayman E, Erbay MF. Neuroanatomical comparison of treatment-resistant and treatment-responsive schizophrenia patients using the cloud-based brain magnetic resonance image segmentation and parcellation system: An MRIcloud study. Psychiatry Res Neuroimaging 2024; 339:111789. [PMID: 38354479 DOI: 10.1016/j.pscychresns.2024.111789] [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: 07/05/2023] [Revised: 12/22/2023] [Accepted: 01/08/2024] [Indexed: 02/16/2024]
Abstract
Recent developments in neuroimaging have improved our understanding of the biological mechanisms underlying schizophrenia. However, neuroimaging findings in treatment-resistant schizophrenia (TRS) remain unclear. In the present study, we aimed to explore potential neuroanatomical regions that may be associated with treatment resistance in schizophrenia patients by comparing neuroanatomical regions of TRS and non-TRS patients using the MRICloud method. A total of 33 schizophrenia patients (meeting DSM 5 diagnostic criteria for schizophrenia) were included in the study. Patients were dichotomized into TRS (n = 18) and non-TRS (n = 15) groups, and all patients underwent MRI. Neuroanatomical regions of TRS and non-TRS patients were compared using the MRICloud method. Disease severity was measured using the Positive and Negative Syndrome Scale (PANSS). Interestingly, a statistically significant greater left Corpus Collosum (CC) thickness was found in TRS patients compared to non-TRS patients. It is clear that further studies comparing TRS patients with non-TRS patients are needed, and these studies should focus on the circuits in the corpus callosum that are thought to play a role in treatment resistance. Further longitudinal studies are also needed to complement the cross-sectional studies, using a multimodal imaging approach in the patients with clearly defined TRS criteria.
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Prohens L, Rodríguez N, Segura ÀG, Martínez-Pinteño A, Olivares-Berjaga D, Martínez I, González A, Mezquida G, Parellada M, Cuesta MJ, Bernardo M, Gassó P, Mas S. Gene expression imputation provides clinical and biological insights into treatment-resistant schizophrenia polygenic risk. Psychiatry Res 2024; 332:115722. [PMID: 38198858 DOI: 10.1016/j.psychres.2024.115722] [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: 10/23/2023] [Revised: 12/21/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
Genome-wide association studies (GWAS) have revealed the polygenic nature of treatment-resistant schizophrenia TRS. Gene expression imputation allowed the translation of GWAS results into regulatory mechanisms and the construction of gene expression (GReX) risk scores (GReX-RS). In the present study we computed GReX-RS from the largest GWAS of TRS to assess its association with clinical features. We perform transcriptome imputation in the largest GWAS of TRS to find GReX associated with TRS using brain tissues. Then, for each tissue, we constructed a GReX-RS of the identified genes in a sample of 254 genotyped first episode of psychosis (FEP) patients to test its association with clinical phenotypes, including clinical symptomatology, global functioning and cognitive performance. Our analysis provides evidence that the polygenic basis of TRS includes genetic variants that modulate the expression of certain genes in certain brain areas (substantia nigra, hippocampus, amygdala and frontal cortex), which at the same time are related to clinical features in FEP patients, mainly persistence of negative symptoms and cognitive alterations in sustained attention, which have also been suggested as clinical predictors of TRS. Our results provide a clinical explanation of the polygenic architecture of TRS and give more insight into the biological mechanisms underlying TRS.
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Affiliation(s)
- Llucia Prohens
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Natalia Rodríguez
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Àlex-Gonzàlez Segura
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Albert Martínez-Pinteño
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - David Olivares-Berjaga
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Irene Martínez
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Aitor González
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Gisela Mezquida
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), ISCIII, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Mara Parellada
- Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), ISCIII, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Manuel J Cuesta
- Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), ISCIII, Spain; Department of Psychiatry, Hospital Universitario de Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Miquel Bernardo
- Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), ISCIII, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Patricia Gassó
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), ISCIII, Spain
| | - Sergi Mas
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Institut d'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en red en salud Mental (CIBERSAM), ISCIII, Spain.
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Schulz J, Brandl F, Grothe MJ, Kirschner M, Kaiser S, Schmidt A, Borgwardt S, Priller J, Sorg C, Avram M. Basal-Forebrain Cholinergic Nuclei Alterations are Associated With Medication and Cognitive Deficits Across the Schizophrenia Spectrum. Schizophr Bull 2023; 49:1530-1541. [PMID: 37606273 PMCID: PMC10686329 DOI: 10.1093/schbul/sbad118] [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] [Indexed: 08/23/2023]
Abstract
BACKGROUND AND HYPOTHESIS The cholinergic system is altered in schizophrenia. Particularly, patients' volumes of basal-forebrain cholinergic nuclei (BFCN) are lower and correlated with attentional deficits. It is unclear, however, if and how BFCN changes and their link to cognitive symptoms extend across the schizophrenia spectrum, including individuals with at-risk mental state for psychosis (ARMS) or during first psychotic episode (FEP). STUDY DESIGN To address this question, we assessed voxel-based morphometry (VBM) of structural magnetic resonance imaging data of anterior and posterior BFCN subclusters as well as symptom ratings, including cognitive, positive, and negative symptoms, in a large multi-site dataset (n = 4) comprising 68 ARMS subjects, 98 FEP patients (27 unmedicated and 71 medicated), 140 patients with established schizophrenia (SCZ; medicated), and 169 healthy controls. RESULTS In SCZ, we found lower VBM measures for the anterior BFCN, which were associated with the anticholinergic burden of medication and correlated with patients' cognitive deficits. In contrast, we found larger VBM measures for the posterior BFCN in FEP, which were driven by unmedicated patients and correlated at-trend with cognitive deficits. We found no BFCN changes in ARMS. Altered VBM measures were not correlated with positive or negative symptoms. CONCLUSIONS Results demonstrate complex (posterior vs. anterior BFCN) and non-linear (larger vs. lower VBM) differences in BFCN across the schizophrenia spectrum, which are specifically associated both with medication, including its anticholinergic burden, and cognitive symptoms. Data suggest an altered trajectory of BFCN integrity in schizophrenia, influenced by medication and relevant for cognitive symptoms.
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Affiliation(s)
- Julia Schulz
- TUM-NIC Neuroimaging Center, Technical University of Munich, School of Medicine, Munich, Germany
- Department of Neuroradiology, Technical University of Munich, School of Medicine, Munich, Germany
| | - Felix Brandl
- TUM-NIC Neuroimaging Center, Technical University of Munich, School of Medicine, Munich, Germany
- Department of Neuroradiology, Technical University of Munich, School of Medicine, Munich, Germany
- Department of Psychiatry and Psychotherapy, Technical University of Munich, School of Medicine, Munich, Germany
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Spain
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland
| | - André Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Stefan Borgwardt
- Translational Psychiatry, Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Josef Priller
- Department of Psychiatry and Psychotherapy, Technical University of Munich, School of Medicine, Munich, Germany
| | - Christian Sorg
- TUM-NIC Neuroimaging Center, Technical University of Munich, School of Medicine, Munich, Germany
- Department of Neuroradiology, Technical University of Munich, School of Medicine, Munich, Germany
- Department of Psychiatry and Psychotherapy, Technical University of Munich, School of Medicine, Munich, Germany
| | - Mihai Avram
- Translational Psychiatry, Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
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Zhu T, Wang Z, Wu W, Ling Y, Wang Z, Zhou C, Fang X, Huang C, Xie C, Chen J, Zhang X. Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis. Front Hum Neurosci 2023; 17:1204632. [PMID: 37954938 PMCID: PMC10637389 DOI: 10.3389/fnhum.2023.1204632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 10/10/2023] [Indexed: 11/14/2023] Open
Abstract
Objective To investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients. Methods We performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls. Results Seventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear. Conclusion This meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).
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Affiliation(s)
- Tingting Zhu
- Department of Psychiatry, The Third People’s Hospital of Huai’an, Huaian, Jiangsu, China
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zengxiu Wang
- Department of Hepatology, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China
| | - Weifeng Wu
- Department of Hepatology, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China
| | - Yuru Ling
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zixu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Zhou
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xinyu Fang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chengbing Huang
- Department of Psychiatry, The Third People’s Hospital of Huai’an, Huaian, Jiangsu, China
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine Southeast University, Nanjing, China
| | - Jiu Chen
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
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Paunova R, Ramponi C, Kandilarova S, Todeva-Radneva A, Latypova A, Stoyanov D, Kherif F. Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes. Front Psychiatry 2023; 14:1272933. [PMID: 37908595 PMCID: PMC10614636 DOI: 10.3389/fpsyt.2023.1272933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/02/2023] [Indexed: 11/02/2023] Open
Abstract
Introduction In this study, we applied multivariate methods to identify brain regions that have a critical role in shaping the connectivity patterns of networks associated with major psychiatric diagnoses, including schizophrenia (SCH), major depressive disorder (MDD) and bipolar disorder (BD) and healthy controls (HC). We used T1w images from 164 subjects: Schizophrenia (n = 17), bipolar disorder (n = 25), major depressive disorder (n = 68) and a healthy control group (n = 54). Methods We extracted regions of interest (ROIs) using a method based on the SHOOT algorithm of the SPM12 toolbox. We then performed multivariate structural covariance between the groups. For the regions identified as significant in t term of their covariance value, we calculated their eigencentrality as a measure of the influence of brain regions within the network. We applied a significance threshold of p = 0.001. Finally, we performed a cluster analysis to determine groups of regions that had similar eigencentrality profiles in different pairwise comparison networks in the observed groups. Results As a result, we obtained 4 clusters with different brain regions that were diagnosis-specific. Cluster 1 showed the strongest discriminative values between SCH and HC and SCH and BD. Cluster 2 had the strongest discriminative value for the MDD patients, cluster 3 - for the BD patients. Cluster 4 seemed to contribute almost equally to the discrimination between the four groups. Discussion Our results suggest that we can use the multivariate structural covariance method to identify specific regions that have higher predictive value for specific psychiatric diagnoses. In our research, we have identified brain signatures that suggest that degeneracy shapes brain networks in different ways both within and across major psychiatric disorders.
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Affiliation(s)
- Rositsa Paunova
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Cristina Ramponi
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Anna Todeva-Radneva
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Adeliya Latypova
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Drozdstoy Stoyanov
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Pang TSW, Chun JSW, Wong TY, Chu ST, Ma CF, Honer WG, Chan SKW. A systematic review of neuroimaging studies of clozapine-resistant schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:65. [PMID: 37752161 PMCID: PMC10522657 DOI: 10.1038/s41537-023-00392-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 09/08/2023] [Indexed: 09/28/2023]
Abstract
This systematic review aimed to review neuroimaging studies comparing clozapine-resistant schizophrenia patients with clozapine-responding patients, and with first-line antipsychotic responding (FLR) patients. A total of 19 studies including 6 longitudinal studies were identified. Imaging techniques comprised computerized tomography (CT, n = 3), structural magnetic resonance imaging (MRI, n = 7), magnetic resonance spectroscopy (MRS, n = 5), functional MRI (n = 1), single-photon emission computerized tomography (SPECT, n = 3) and diffusion tensor imaging (DTI, n = 1). The most consistent finding was hypo-frontality in the clozapine-resistant group compared with the clozapine-responding group with possible differences in frontal-striatal-basal ganglia circuitry as well as the GABA level between the two treatment-resistant groups. Additional statistically significant findings were reported when comparing clozapine-resistant patients with the FLR group, including lower cortical thickness and brain volume of multiple brain regions as well as lower Glx/Cr level in the dorsolateral prefrontal cortex. Both treatment-resistant groups were found to have extensive differences in neurobiological features in comparison with the FLR group. Overall results suggested treatment-resistant schizophrenia is likely to be a neurobiological distinct type of the illness. Clozapine-resistant and clozapine-responding schizophrenia are likely to have both shared and distinct neurobiological features. However, conclusions from existing studies are limited, and future multi-center collaborative studies are required with a consensus clinical definition of patient samples, multimodal imaging tools, and longitudinal study designs.
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Affiliation(s)
- Tiffanie Sze Wing Pang
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Johnny Siu Wah Chun
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Ting Yat Wong
- Department of Psychology, The Education University of Hong Kong, Hong Kong SAR, China
| | - Sin Ting Chu
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Chak Fai Ma
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - William G Honer
- Department of Psychiatry, The University of British Columbia, Vancouver, Canada
| | - Sherry Kit Wa Chan
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, HKSAR, Hong Kong SAR, China.
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10
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Mohamed Saini S, Bousman CA, Mancuso SG, Cropley V, Van Rheenen TE, Lenroot RK, Bruggemann J, Weickert CS, Weickert TW, Sundram S, Everall IP, Pantelis C. Genetic variation in glutamatergic genes moderates the effects of childhood adversity on brain volume and IQ in treatment-resistant schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:59. [PMID: 37709784 PMCID: PMC10502098 DOI: 10.1038/s41537-023-00381-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/20/2023] [Indexed: 09/16/2023]
Affiliation(s)
- Suriati Mohamed Saini
- Department of Psychiatry, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Cheras, Kuala Lumpur, Malaysia.
- Department of Psychiatry, Hospital Canselor Tuanku Muhriz, Jalan Yaacob Latif, Cheras, Kuala Lumpur, Malaysia.
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Medical Genetics, Psychiatry, and Physiology and Pharmacology, The University of Calgary, Calgary, AB, Canada
| | - Serafino G Mancuso
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University, Melbourne, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University, Melbourne, VIC, Australia
| | - Rhoshel K Lenroot
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Psychiatry and Behavioural Science, University of New Mexico, Albuquerque, NM, USA
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Neuroscience Research Australia, Randwick, NSW, Australia
- Schizophrenia Research Institute, Sydney, NSW, Australia
| | - Cynthia S Weickert
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, NY, USA
- Schizophrenia Research Laboratory, Neuroscience Research Australia, NSW, Australia
| | - Thomas W Weickert
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, NY, USA
| | - Suresh Sundram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
- Monash Medical Centre, Monash Health, Clayton, VIC, Australia
| | - Ian P Everall
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Western Centre for Health Research & Education, Sunshine Hospital, Western Health, St Albans, VIC, 3021, Australia
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11
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Chen W, Gou M, Wang L, Li N, Li W, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Pan S, Luo X, Zhang P, Huang J, Tian L, Li CSR, Tan Y. Inflammatory disequilibrium and lateral ventricular enlargement in treatment-resistant schizophrenia. Eur Neuropsychopharmacol 2023; 72:18-29. [PMID: 37058967 DOI: 10.1016/j.euroneuro.2023.03.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/28/2023] [Accepted: 03/30/2023] [Indexed: 04/16/2023]
Abstract
Treatment-resistant schizophrenia (TRS) patient respond poorly to antipsychotics. Inflammatory imbalance involving pro- and anti-inflammatory cytokines may play an important role in the mechanism of antipsychotic-medication response. This study aimed to investigate immune imbalance and how the latter relates to clinical manifestations in patients with TRS. The level of net inflammation was estimated by evaluating the immune-inflammatory response system and compensatory immune-regulatory reflex system (IRS/CIRS) in 52 patients with TRS, 47 with non-TRS, and 56 sex and age matched healthy controls. The immune biomarkers mainly included macrophagic M1, T helper, Th-1, Th-2, Th-17, and T regulatory cytokines and receptors. Plasma cytokine levels were measured using enzyme-linked immunosorbent assay. Psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS). Subcortical volumes were quantified using a 3-T Prisma Magnetic Resonance Imaging scanner. The results showed that (1) patients with TRS were characterized by activated pro-inflammatory cytokines and relatively insufficient anti-inflammatory cytokines, with an elevated IRS/CIRS ratio indicating a new homeostatic immune setpoint; (2) IRS/CIRS ratio was positively correlated with larger lateral ventricle volume and higher PANSS score in patients with TRS. Our findings highlighted the inflammatory disequilibrium as a potential pathophysiological process of TRS.
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Affiliation(s)
- Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Leilei Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Na Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Xie
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shujuan Pan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China.
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12
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Kim J, Song J, Kambari Y, Plitman E, Shah P, Iwata Y, Caravaggio F, Brown EE, Nakajima S, Chakravarty MM, De Luca V, Remington G, Graff-Guerrero A, Gerretsen P. Cortical thinning in relation to impaired insight into illness in patients with treatment resistant schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:27. [PMID: 37120642 PMCID: PMC10148890 DOI: 10.1038/s41537-023-00347-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 03/12/2023] [Indexed: 05/01/2023]
Abstract
Impaired insight into illness is a common element of schizophrenia that contributes to treatment nonadherence and negative clinical outcomes. Previous studies suggest that impaired insight may arise from brain abnormalities. However, interpretations of these findings are limited due to small sample sizes and inclusion of patients with a narrow range of illness severity and insight deficits. In a large sample of patients with schizophrenia, the majority of which were designated as treatment-resistant, we investigated the associations between impaired insight and cortical thickness and subcortical volumes. A total of 94 adult participants with a schizophrenia spectrum disorder were included. Fifty-six patients (60%) had treatment-resistant schizophrenia. The core domains of insight were assessed with the VAGUS insight into psychosis scale. We obtained 3T MRI T1-weighted images, which were analysed using CIVET and MAGeT-Brain. Whole-brain vertex-wise analyses revealed impaired insight, as measured by VAGUS average scores, was related to cortical thinning in left frontotemporoparietal regions. The same analysis in treatment-resistant patients showed thinning in the same regions, even after controlling for age, sex, illness severity, and chlorpromazine antipsychotic dose equivalents. No association was found in non-treatment-resistant patients. Region-of-interest analyses revealed impaired general illness awareness was associated with cortical thinning in the left supramarginal gyrus when controlling for covariates. Reduced right and left thalamic volumes were associated with VAGUS symptom attribution and awareness of negative consequences subscale scores, respectively, but not after correction for multiple testing. Our results suggest impaired insight into illness is related to cortical thinning in left frontotemporoparietal regions in patients with schizophrenia, particularly those with treatment resistance where insight deficits may be more chronic.
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Affiliation(s)
- Julia Kim
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Jianmeng Song
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Yasaman Kambari
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Eric Plitman
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Parita Shah
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Yusuke Iwata
- University of Yamanashi, Faculty of Medicine, Department of Neuropsychiatry, Yamanashi, Japan
| | - Fernando Caravaggio
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Eric E Brown
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, CAMH, Toronto, ON, Canada
- Geriatric Mental Health Division, CAMH, Toronto, ON, Canada
| | - Shinichiro Nakajima
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Vincenzo De Luca
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Gary Remington
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, CAMH, Toronto, ON, Canada
- Schizophrenia Division, CAMH, Toronto, ON, Canada
| | - Ariel Graff-Guerrero
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Geriatric Mental Health Division, CAMH, Toronto, ON, Canada
- Schizophrenia Division, CAMH, Toronto, ON, Canada
| | - Philip Gerretsen
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Geriatric Mental Health Division, CAMH, Toronto, ON, Canada.
- Schizophrenia Division, CAMH, Toronto, ON, Canada.
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13
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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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14
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Facal F, Costas J. Polygenic risk scores for schizophrenia and treatment resistance: New data, systematic review and meta-analysis. Schizophr Res 2023; 252:189-197. [PMID: 36657363 DOI: 10.1016/j.schres.2023.01.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/14/2022] [Accepted: 01/05/2023] [Indexed: 01/18/2023]
Affiliation(s)
- Fernando Facal
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain; Servizo de Psiquiatría, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain; Universidade de Santiago de Compostela (USC), Galicia, Spain
| | - Javier Costas
- Instituto de Investigación Sanitaria (IDIS) de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain.
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15
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Kitajima K, Tamura S, Sasabayashi D, Nakajima S, Iwata Y, Ueno F, Takai Y, Takahashi J, Caravaggio F, Mar W, Torres-Carmona E, Noda Y, Gerretsen P, Luca VD, Mimura M, Hirano S, Nakao T, Onitsuka T, Remington G, Graff-Guerrero A, Hirano Y. Decreased cortical gyrification and surface area in the left medial parietal cortex in patients with treatment-resistant and ultratreatment-resistant schizophrenia. Psychiatry Clin Neurosci 2023; 77:2-11. [PMID: 36165228 PMCID: PMC10092309 DOI: 10.1111/pcn.13482] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/11/2022] [Accepted: 09/13/2022] [Indexed: 01/06/2023]
Abstract
AIM Validating the vulnerabilities and pathologies underlying treatment-resistant schizophrenia (TRS) is an important challenge in optimizing treatment. Gyrification and surface area (SA), reflecting neurodevelopmental features, have been linked to genetic vulnerability to schizophrenia. The aim of this study was to identify gyrification and SA abnormalities specific to TRS. METHODS We analyzed 3T magnetic resonance imaging findings of 24 healthy controls (HCs), 20 responders to first-line antipsychotics (FL-Resp), and 41 patients with TRS, including 19 clozapine responders (CLZ-Resp) and 22 FL- and clozapine-resistant patients (patients with ultratreatment-resistant schizophrenia [URS]). The local gyrification index (LGI) and associated SA were analyzed across groups. Diagnostic accuracy was verified by receiver operating characteristic curve analysis. RESULTS Both CLZ-Resp and URS had lower LGI values than HCs (P = 0.041, Hedges g [gH ] = 0.75; P = 0.013, gH = 0.96) and FL-Resp (P = 0.007, gH = 1.00; P = 0.002, gH = 1.31) in the left medial parietal cortex (Lt-MPC). In addition, both CLZ-Resp and URS had lower SA in the Lt-MPC than FL-Resp (P < 0.001, gH = 1.22; P < 0.001, gH = 1.75). LGI and SA were positively correlated in non-TRS (FL-Resp) (ρ = 0.64, P = 0.008) and TRS (CLZ-Resp + URS) (ρ = 0.60, P < 0.001). The areas under the receiver operating characteristic curve for non-TRS versus TRS with LGI and SA in the Lt-MPC were 0.79 and 0.85, respectively. SA in the Lt-MPC was inversely correlated with negative symptoms (ρ = -0.40, P = 0.018) and clozapine plasma levels (ρ = -0.35, P = 0.042) in TRS. CONCLUSION LGI and SA in the Lt-MPC, a functional hub in the default-mode network, were abnormally reduced in TRS compared with non-TRS. Thus, altered LGI and SA in the Lt-MPC might be structural features associated with genetic vulnerability to TRS.
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Affiliation(s)
- Kazutoshi Kitajima
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shunsuke Tamura
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, 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
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan.,Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Yusuke Iwata
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.,Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Fumihiko Ueno
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Yoshifumi Takai
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Junichi Takahashi
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of Neuropsychiatry, National Hospital Organization Kyushu Medical Center, Fukuoka, Japan
| | - Fernando Caravaggio
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Wanna Mar
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Edgardo Torres-Carmona
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Yoshihiro Noda
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Philip Gerretsen
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Vincenzo de Luca
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Shogo Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Tomohiro Nakao
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshiaki Onitsuka
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Gary Remington
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
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16
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Fan F, Huang J, Tan S, Wang Z, Li Y, Chen S, Li H, Hare S, Du X, Yang F, Tian B, Kochunov P, Tan Y, Hong LE. Association of cortical thickness and cognition with schizophrenia treatment resistance. Psychiatry Clin Neurosci 2023; 77:12-19. [PMID: 36184782 PMCID: PMC9812867 DOI: 10.1111/pcn.13486] [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: 09/01/2021] [Revised: 06/24/2022] [Accepted: 09/28/2022] [Indexed: 01/07/2023]
Abstract
AIM Approximately a third of patients with schizophrenia fail to adequately respond to antipsychotic medications, a condition known as treatment resistance (TR). We aimed to assess cognitive and cortical thickness deficits and their relationship to TR in schizophrenia. METHOD We recruited patients with schizophrenia (n = 127), including patients at treatment initiation (n = 45), treatment-responsive patients (n = 40) and TR patients (n = 42), and healthy controls (n = 83). Clinical symptoms, neurocognitive function, and structural images were assessed. We performed group comparisons, and explored association of cortical thickness and cognition with TR. RESULTS The TR patients showed significantly more severe clinical symptoms and cognitive impairment relative to the treatment-responsive group. Compared to healthy controls, 56 of 68 brain regions showed significantly reduced cortical thickness in patients with schizophrenia. Reductions in five regions were significantly associated with TR (reduction in TR relative to treatment-responsive patients), i.e. in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cognition deficits were also significantly correlated with cortical thickness in these five regions in patients with schizophrenia. Cortical thickness of the right caudal middle frontal gyrus, superior frontal cortex and pars opercularis of the inferior frontal cortex also significantly mediated effects of cognitive deficits on TR. CONCLUSION Treatment resistance in schizophrenia was associated with reduced thickness in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cortical abnormalities further mediate cognitive deficits known to be associated with TR.
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Affiliation(s)
- Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yanli Li
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Hui Li
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Stephanie Hare
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Baopeng Tian
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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17
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Zhu F, Xiao Y, Tao B, Gao Z, Gao X, Zhao Q, Zhang Q, Tang B, Zhang X, Zhao Y, Bishop JR, Sweeney JA, Lui S. Radiomic features of gray matter in never-treated first-episode schizophrenia. Cereb Cortex 2022; 33:5957-5967. [PMID: 36513368 DOI: 10.1093/cercor/bhac474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/09/2022] [Accepted: 11/10/2022] [Indexed: 12/15/2022] Open
Abstract
Alterations of radiomic features (RFs) in gray matter are observed in schizophrenia, of which the results may be limited by small study samples and confounding effects of drug therapies. We tested for RFs alterations of gray matter in never-treated first-episode schizophrenia (NT-FES) patients and examined their associations with known gene expression profiles. RFs were examined in the first sample with 197 NT-FES and 178 healthy controls (HCs) and validated in the second independent sample (90 NT-FES and 74 HCs). One-year follow-up data were available from 87 patients to determine whether RFs were associated with treatment outcomes. Associations between identified RFs in NT-FES and gene expression profiles were evaluated. NT-FES exhibited alterations of 30 RFs, with the greatest involvement of microstructural heterogeneity followed by measures of brain region shape. The identified RFs were mainly located in the central executive network, frontal-temporal network, and limbic system. Two baseline RFs with the involvement of microstructural heterogeneity predicted treatment response with moderate accuracy (78% for the first sample, 70% for the second sample). Exploratory analyses indicated that RF alterations were spatially related to the expression of schizophrenia risk genes. In summary, the present findings link brain abnormalities in schizophrenia with molecular features and treatment response.
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Affiliation(s)
- Fei Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ziyang Gao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xin Gao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qiannan Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qi Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Biqiu Tang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | | | - Yu Zhao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology and Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN 55455, USA
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH 45219, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
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18
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Network hub centrality and working memory performance in schizophrenia. SCHIZOPHRENIA 2022; 8:76. [PMID: 36151201 PMCID: PMC9508261 DOI: 10.1038/s41537-022-00288-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 09/12/2022] [Indexed: 11/08/2022]
Abstract
Cognitive impairment, and working memory deficits in particular, are debilitating, treatment-resistant aspects of schizophrenia. Dysfunction of brain network hubs, putatively related to altered neurodevelopment, is thought to underlie the cognitive symptoms associated with this illness. Here, we used weighted degree, a robust graph theory metric representing the number of weighted connections to a node, to quantify centrality in cortical hubs in 29 patients with schizophrenia and 29 age- and gender-matched healthy controls and identify the critical nodes that underlie working memory performance. In both patients and controls, elevated weighted degree in the default mode network (DMN) was generally associated with poorer performance (accuracy and reaction time). Higher degree in the ventral attention network (VAN) nodes in the right superior temporal cortex was associated with better performance (accuracy) in patients. Degree in several prefrontal and parietal areas was associated with cognitive performance only in patients. In regions that are critical for sustained attention, these correlations were primarily driven by between-network connectivity in patients. Moreover, a cross-validated prediction analysis showed that a linear model using a summary degree score can be used to predict an individual’s working memory accuracy (r = 0.35). Our results suggest that schizophrenia is associated with dysfunctional hubs in the cortical systems supporting internal and external cognition and highlight the importance of topological network analysis in the search of biomarkers for cognitive deficits in schizophrenia.
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19
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Pandey A, Kalita KN. Treatment-resistant schizophrenia: How far have we traveled? Front Psychiatry 2022; 13:994425. [PMID: 36111312 PMCID: PMC9468267 DOI: 10.3389/fpsyt.2022.994425] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Treatment-resistant schizophrenia is a lack of adequate response to antipsychotic medications resulting in incomplete functional and social recovery from the illness. Different definitions have been proposed for clinical practice and research work. Antipsychotics that are used in the management of schizophrenia mainly act on multiple dopaminergic pathways which are implicated in the development of symptoms of schizophrenia. Newer antipsychotics also are implicated to affect the serotonergic pathways. Clozapine is the only evidence-based treatment available for the management of treatment-resistant cases. Neurobiologically, there is a considerable overlap between treatment-resistant and treatment-responsive cases. The factors that are implicated in the evolution of treatment resistance are still not conclusive. These make the management of such patients a challenge. However, certain peculiarities of treatment-resistant schizophrenia have been identified which can guide us in the early identification and precise treatment of the treatment-resistant cases.
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Affiliation(s)
- Ambu Pandey
- Department of Psychiatry, Maharshi Devraha Baba Autonomous State Medical College, Deoria, India
| | - Kamal Narayan Kalita
- Department of Psychiatry, Lokpriya Gopinath Bordoloi Regional Institute of Mental Health, Tezpur, India
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20
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Differences in small-world networks between methamphetamine and heroin use disorder patients and their relationship with psychiatric symptoms. Brain Imaging Behav 2022; 16:1973-1982. [PMID: 36018531 DOI: 10.1007/s11682-022-00667-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2022] [Indexed: 11/02/2022]
Abstract
Both methamphetamine use disorder (MAUD) and heroin use disorder (HUD) implicated in substance-induced psychosis, but the psychiatirc symptoms induced by MAUD and HUD are significantly different. The functional network organizations that may underlie these differences remains unknown. Image data was acquired by resting-state fMRI from 19 MAUD patients, 21 HUD patients, and 20 healthy controls. The small-world properties, node attributes, and functional connectivity of brain regions were analyzed among the three groups. Psychiatric status was evaluated by the Symptom Checklist 90 in all participants. The MAUD patients had significantly higher psychiatric scores than the controls and HUD patients. Both MAUD and HUD patients still had economical small-world properties. The MAUD patients showed increased nodal efficiency and betweenness centrality in the right inferior occipital gyrus, left insular lobe, bilateral Heschl gyrus, and bilateral superior temporal gyrus, while the node attributes decreased in the right parahippocampal gyrus and right hippocampus compared to the HUD patients. The MAUD patients also showed reduced edge connectivity between left dorsolateral prefrontal cortex (dlPFC) and left middle occipital gyrus (MOG), as well as between bilateral orbitofrontal cortex (OFC) and bilateral superior occipital gyrus (SOG), left MOG, or right cuneus. In the MAUD group, the functional connection between left dlPFC and left MOG was negatively correlated with depression, while the connection between right cuneus lobe and right OFC was negatively correlated with depression and interpersonal sensitivity. These brain regions related to cognitive, emotional, and auditory/visual regulation may play an important role in the psychiatric symptoms of MAUD.
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21
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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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22
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Liu C, Kim WS, Shen J, Tsogt U, Kang NI, Lee KH, Chung YC. Altered Neuroanatomical Signatures of Patients With Treatment-Resistant Schizophrenia Compared to Patients With Early-Stage Schizophrenia and Healthy Controls. Front Psychiatry 2022; 13:802025. [PMID: 35664476 PMCID: PMC9158464 DOI: 10.3389/fpsyt.2022.802025] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/12/2022] [Indexed: 11/25/2022] Open
Abstract
Background The relationship between brain structural changes and cognitive dysfunction in schizophrenia is strong. However, few studies have investigated both neuroanatomical abnormalities and cognitive dysfunction in treatment-resistant schizophrenia (TRS). We examined neuroanatomical markers and cognitive function between patients with TRS or early-stage schizophrenia (ES-S) and healthy controls (HCs). Relationships between neuroanatomical markers and cognitive function in the patient groups were also investigated. Methods A total of 46 and 45 patients with TRS and ES-S and 61 HCs underwent structural magnetic resonance imaging (MRI) brain scanning and comprehensive cognitive tests. MRI scans were analyzed using the FreeSurfer to investigate differences in cortical surface area (CSA), cortical thickness (CT), cortical volume (CV), and subcortical volume (SCV) among the groups. Four cognitive domains (attention, verbal memory, executive function, and language) were assessed. Comparisons of neuroanatomical and cognitive function results among the three groups were performed. Results A widespread reduction in CT was observed in patients with TRS compared to HCs, but differences in cortical thinning between TRS and ES-S patients were mainly limited to the inferior frontal gyrus and insula. Several subcortical structures (accumbens, amygdala, hippocampus, putamen, thalamus and ventricles) were significantly altered in TRS patients compared to both ES-S patients and HCs. Performance in the verbal memory domain was significantly worse in TRS patients compared to ES-S patients. A positive relationship between the thickness of the left middle temporal gyrus and the composite score for language was identified in patients with ES-S. Conclusions Our findings suggest significant cognitive impairment and reductions in CT and SCV in individuals with TRS compared to those with ES-S and HCs. These abnormalities could act as biomarkers for earlier identification of TRS.
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Affiliation(s)
- Congcong Liu
- Department of Psychiatry, Medical School, Jeonbuk National University, Jeonju, South Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Medical School, Jeonbuk National University, Jeonju, South Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea
| | - Jie Shen
- Department of Psychiatry, Medical School, Jeonbuk National University, Jeonju, South Korea
| | - Uyanga Tsogt
- Department of Psychiatry, Medical School, Jeonbuk National University, Jeonju, South Korea
| | - Nam-In Kang
- Department of Psychiatry, Maeumsarang Hospital, Wanju, South Korea
| | - Keon-Hak Lee
- Department of Psychiatry, Maeumsarang Hospital, Wanju, South Korea
| | - Young-Chul Chung
- Department of Psychiatry, Medical School, Jeonbuk National University, Jeonju, South Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, South Korea
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23
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Krajner F, Hadaya L, McQueen G, Sendt KV, Gillespie A, Avila A, Lally J, Hedges EP, Diederen K, Howes OD, Barker GJ, Lythgoe DJ, Kempton MJ, McGuire P, MacCabe JH, Egerton A. Subcortical volume reduction and cortical thinning 3 months after switching to clozapine in treatment resistant schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:13. [PMID: 35236831 PMCID: PMC8891256 DOI: 10.1038/s41537-022-00230-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 12/06/2021] [Indexed: 11/29/2022]
Abstract
The neurobiological effects of clozapine are under characterised. We examined the effects clozapine treatment on subcortical volume and cortical thickness and investigated whether macrostructural changes were linked to alterations in glutamate or N-acetylaspartate (NAA). Data were acquired in 24 patients with treatment-resistant schizophrenia before and 12 weeks after switching to clozapine. During clozapine treatment we observed reductions in caudate and putamen volume, lateral ventricle enlargement (P < 0.001), and reductions in thickness of the left inferior temporal cortex, left caudal middle frontal cortex, and the right temporal pole. Reductions in right caudate volume were associated with local reductions in NAA (P = 0.002). None of the morphometric changes were associated with changes in glutamate levels. These results indicate that clozapine treatment is associated with subcortical volume loss and cortical thinning and that at least some of these effects are linked to changes in neuronal or metabolic integrity.
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Affiliation(s)
- Fanni Krajner
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Laila Hadaya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Grant McQueen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Kyra-Verena Sendt
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Amy Gillespie
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Alessia Avila
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - John Lally
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Emily P Hedges
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Kelly Diederen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- South London and Maudsley NHS Trust, London, UK
| | - Gareth J Barker
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - David J Lythgoe
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- South London and Maudsley NHS Trust, London, UK
| | - James H MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- South London and Maudsley NHS Trust, London, UK
| | - Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK.
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24
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Matrone M, Kotzalidis GD, Romano A, Bozzao A, Cuomo I, Valente F, Gabaglio C, Lombardozzi G, Trovini G, Amici E, Perrini F, De Persis S, Iasevoli F, De Filippis S, de Bartolomeis A. Treatment-resistant schizophrenia: Addressing white matter integrity, intracortical glutamate levels, clinical and cognitive profiles between early- and adult-onset patients. Prog Neuropsychopharmacol Biol Psychiatry 2022; 114:110493. [PMID: 34883221 DOI: 10.1016/j.pnpbp.2021.110493] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 11/05/2021] [Accepted: 11/29/2021] [Indexed: 01/30/2023]
Abstract
BACKGROUND Treatment-resistance in schizophrenia is 30-40%. Its neurobiology remains unclear; to explore it, we conducted a combined spectrometry/tractography/cognitive battery and psychopathological rating study on patients with treatment-resistant schizophrenia (TRS), dividing the sample into early-onset (N = 21) and adult-onset TRS (N = 20). Previous studies did not differentiate between early- (onset 13-18 years) and adult-onset (>18 years at formal diagnosis of schizophrenia) TRS. METHODS We evaluated cross-sectionally 41 TRS patients (26 male and 15 female) and 20 matched healthy controls (HCs) with psychopathological and cognitive testing prior to participating in brain imaging scanning using magnetic resonance spectroscopy and diffusion tensor imaging to determine the relationship between their symptoms and their glutamate levels and white matter integrity. RESULTS TRS patients scored lower than HCs on all cognitive domains; early-onset patients performed better than adult-onset patients only on the Symbol Coding domain. TRS correlated with symptom severity, especially negative symptoms. Glutamate levels and glutamate/creatine were increased in anterior cingulate cortex. Diffusion tensor imaging showed low fractional anisotropy in TRS patients in specific white matter tracts compared to HCs (bilateral anterior thalamic radiation, cortico-spinal tract, forceps minor, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus, and right uncinate fasciculus). CONCLUSIONS We identified specific magnetic resonance spectroscopy and diffusion tensor imaging alterations in TRS patients. Adult-onset TRS differed little from early-onset TRS on most measures; this points to alterations being present since the outset of schizophrenia and may constitute a biological signature of treatment-resistance.
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Affiliation(s)
- Marta Matrone
- Section of Psychiatry Laboratory of Molecular and Translational Psychiatry, Unit of Treatment Resistant Psychosis, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy; Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Georgios D Kotzalidis
- NESMOS (Neurosciences, Mental Health, and Sensory Organs) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Via di Grottarossa 1035-1039, 00189 Rome, Italy.
| | - Andrea Romano
- NESMOS (Neurosciences, Mental Health, and Sensory Organs) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Via di Grottarossa 1035-1039, 00189 Rome, Italy.
| | - Alessandro Bozzao
- NESMOS (Neurosciences, Mental Health, and Sensory Organs) Department, Sapienza University of Rome, Faculty of Medicine and Psychology, Via di Grottarossa 1035-1039, 00189 Rome, Italy.
| | - Ilaria Cuomo
- UOC SM I Distretto ASL ROMA 1, C.C. Regina Cœli, Via della Lungara 29, 00165 Rome, Italy.
| | - Francesca Valente
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy; Department of Human Neurosciences, Institute of Child and Adolescent Neuropsychiatry, Sapienza University of Rome, Italy.
| | - Chiara Gabaglio
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Ginevra Lombardozzi
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Giada Trovini
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Emanuela Amici
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Filippo Perrini
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy; UOC SMREE Distretto ASL ROMA 6, TSMREE, Via S. Biagio, 12, 00049, Velletri, Rome, Italy.
| | - Simone De Persis
- UOSD Attività Terapeutiche Riabilitative per i Disturbi da uso di Sostanze e nuove Dipendenze, ASL Rieti, Via Salaria per Roma 36, 02100 Rieti, Italy.
| | - Felice Iasevoli
- Section of Psychiatry Laboratory of Molecular and Translational Psychiatry, Unit of Treatment Resistant Psychosis, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy.
| | - Sergio De Filippis
- Clinica Neuropsichiatrica Villa von Siebenthal, Department of Neuropsychiatry, Via della Madonnina 1, 00045 Genzano di Roma, RM, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry Laboratory of Molecular and Translational Psychiatry, Unit of Treatment Resistant Psychosis, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy.
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25
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Serum kynurenine metabolites might not be associated with risk factors of treatment-resistant schizophrenia. J Psychiatr Res 2022; 145:339-346. [PMID: 34776248 DOI: 10.1016/j.jpsychires.2021.11.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 10/11/2021] [Accepted: 11/02/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND About a third of patients with schizophrenia do not respond adequately to currently available antipsychotics and thus experiences symptoms of greater severity, known as treatment-resistant schizophrenia (TRS). Some evidence suggests that the tryptophan (TRP) pathway (comprising 5-HT and kynurenine sub-pathways) has an important influence on response to antipsychotics. We therefore hypothesized that TRS is linked to metabolites of TRP pathway. METHODS We measured TRP metabolites in 54 patients with TRS and compared them to 49 age- and sex-matched patients who responded to antipsychotics (NTRS), and 62 healthy controls using liquid chromatography-tandem mass spectrometry. Psychopathology and clinical symptoms were assessed by means of schizophrenia positive and negative scales. Working memory abilities, cortical thickness and white matter diffusion tensor imaging fractional anisotropy were appraised in enrolled subjects by neurophysiological tests, as spatial span and digital sequencing tests, and 3T magnetic resonance imaging. RESULTS Patients with TRS had a significantly higher 5-HT/TRP ratio (p = 0.009) than patients with NTRS. However, the two groups did not differ in kynurenine-pathway metabolites or ratios. Additionally, 5-HT/TRP was positively correlated with disorganized symptoms in TRS (r = 0.59, p < 0.001), and negatively correlated with digit-sequencing test scores (r = -0.34, p = 0.02). These correlations were insignificant among patients with NTRS and healthy controls. In patients with TRS, 5-HT/TRP was strongly linked to the right supramarginal cortex (t = -3.2, p = 0.003), and in healthy controls, to the right transverse temporal (t = 3.40, p = 0.001), but significance disappeared after FDR correction. CONCLUSIONS Present results indicate that an upregulated 5-HT biosynthetic pathway can be associated to TRS, suggesting that targeting mechanisms of 5-HT conversion from tryptophan could shed light on the development of new pharmacological approaches of TRS.
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26
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Zhu T, Wang Z, Zhou C, Fang X, Huang C, Xie C, Ge H, Yan Z, Zhang X, Chen J. Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation. Front Psychiatry 2022; 13:957685. [PMID: 36238945 PMCID: PMC9552970 DOI: 10.3389/fpsyt.2022.957685] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 09/05/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Persistent negative symptoms (PNS) include both primary and secondary negative symptoms that persist after adequate treatment, and represent an unmet therapeutic need. Published magnetic resonance imaging (MRI) evidence of structural and resting-state functional brain abnormalities in schizophrenia with PNS has been inconsistent. Thus, the purpose of this meta-analysis is to identify abnormalities in structural and functional brain regions in patients with PNS compared to healthy controls. METHODS We systematically searched PubMed, Web of Science, and Embase for structural and functional imaging studies based on five research methods, including voxel-based morphometry (VBM), diffusion tensor imaging (DTI), functional connectivity (FC), the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo). Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm. RESULTS Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. Our analysis revealed the presence of structural alterations in patients with PNS in some brain regions including the bilateral insula, medial frontal gyrus, anterior cingulate gyrus, left amygdala, superior temporal gyrus, inferior frontal gyrus, cingulate gyrus and middle temporal gyrus, as well as functional differences in some brain regions including the bilateral precuneus, thalamus, left lentiform nucleus, posterior cingulate gyrus, medial frontal gyrus, and superior frontal gyrus. CONCLUSION Our study suggests that structural brain abnormalities are consistently located in the prefrontal, temporal, limbic and subcortical regions, and functional alterations are concentrated in the thalamo-cortical circuits and the default mode network (DMN). This study provides new insights for targeted treatment and intervention to delay further progression of negative symptoms. SYSTEMATIC REVIEW REGISTRATION [https://www.crd.york.ac.uk/prospero/], identifier [CRD42022338669].
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Affiliation(s)
- Tingting Zhu
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zixu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Zhou
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xinyu Fang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chengbing Huang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Department of Psychiatry, The Third People's Hospital of Huai'an, Huaian, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine Southeast University, Nanjing, China
| | - Honglin Ge
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zheng Yan
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, China
| | - Jiu Chen
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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27
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Zhou S, Huang Y, Kuang Q, Yan S, Li H, Wu K, Wu F, Huang X. Kynurenine pathway metabolites are associated with gray matter volume in subjects with schizophrenia. Front Psychiatry 2022; 13:941479. [PMID: 36016974 PMCID: PMC9395706 DOI: 10.3389/fpsyt.2022.941479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 06/29/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND There has been growing evidence of the existence of abnormalities in the kynurenine pathway (KP) and structural gray matter volume (GMV) in schizophrenia (SCZ). Numerous studies have suggested that abnormal kynurenine metabolism (KM) in the brain is clearly associated with the pathogenesis of schizophrenia and may be one of the pathological mechanisms of SCZ. In this pilot study, we investigated whether there was a correlation between KP and GMV in schizophrenia patients. METHODS The plasma levels of KM were measured in 41 patients who met the Structured Clinical Interview of the Diagnostic IV criteria for schizophrenia and 60 healthy controls by using liquid chromatography-tandem mass spectrometry, and cortical thickness (as measured via magnetic resonance imaging) was obtained. RESULTS Our study showed no statistically significant differences in the concentrations of kynurenine (KYN), tryptophan (TRP), and KYNA/TRP (all p > 0.05), but kynurenic acid (KYNA) and the KYNA/KYN ratio were significantly higher in the schizophrenia subjects than in the healthy controls (F = 4.750, p = 0.032; F = 6.153, p = 0.015, respectively) after controlling for age and sex. Spearman's tests showed that KYN concentrations in SCZ patients were negatively correlated with GMV in the left front cingulate belt (r = -0.325, p = 0.046) and that KYN/TRP was negatively correlated with GMV in the left island (r = -0.396, p = 0.014) and right island (r = -0.385, p = 0.017). CONCLUSION Our findings appear to provide new insights into the predisposition of an imbalance in the relative metabolism of KYN/TRP and KYN to GMV in schizophrenia.
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Affiliation(s)
- Sumiao Zhou
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Huang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qijie Kuang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Su Yan
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hehua Li
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou, China.,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Fengchun Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.,School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou, China.,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Xingbing Huang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
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28
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Sampedro F, Roldán A, Alonso-Solís A, Grasa E, Portella MJ, Aguilar EJ, Núñez-Marín F, Gómez-Ansón B, Corripio I. Grey matter microstructural alterations in schizophrenia patients with treatment-resistant auditory verbal hallucinations. J Psychiatr Res 2021; 138:130-138. [PMID: 33852993 DOI: 10.1016/j.jpsychires.2021.03.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 03/16/2021] [Accepted: 03/19/2021] [Indexed: 01/07/2023]
Abstract
Treatment-resistant auditory verbal hallucinations (TRAVH) are a relatively prevalent and devastating symptom in patients with schizophrenia (SCZ). Even though their pathological mechanisms are poorly understood, they seem to differ from those underlying non-hallucinating SCZ. In this study, we characterise structural brain changes in SCZ patients with TRAVH. With respect to non-hallucinating patients and healthy controls, we studied macrostructural grey matter changes through cortical thickness and subcortical volumetric data. Additionally, we analysed microstructural differences across groups using intracortical and subcortical mean diffusivity data. This latter imaging metric has been claimed to detect incipient neuronal damage, as water can diffuse more freely in regions with reduced neural density. We found brain macrostructrural and microstructural alterations in SCZ patients with TRAVH (n = 29), both with respect to non-hallucinating (n = 20) patients and healthy controls (n = 27). Importantly, a microstructural -rather than a macrostructural- compromise was found in key brain regions such as the ventral ACC, the NAcc and the hippocampus. These microstructural alterations correlated, in turn, with clinical severity. TRAVH patients also showed accentuated age-related cortical deterioration and an abnormal longitudinal loss of cortical integrity over a one-year period. These findings highlight the potential role of microstructural imaging biomarkers in SCZ. Notably, they could be used both to detect and to monitor subtle grey matter alterations in critical brain regions such as deep brain stimulation targets. Moreover, our results support the existence of a more aggressive and active pathological mechanism in patients with TRAVH, providing new insight into the aetiology of this debilitating illness.
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Affiliation(s)
- Frederic Sampedro
- Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spain
| | - Alexandra Roldán
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain
| | - Anna Alonso-Solís
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain.
| | - Eva Grasa
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
| | - Maria J Portella
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
| | - Eduardo J Aguilar
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; INCLIVA, School of Medicine, University of Valencia, Valencia, Spain
| | - Fidel Núñez-Marín
- Neuroradiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB) Barcelona, Spain
| | - Beatriz Gómez-Ansón
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spain; Neuroradiology Department, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB) Barcelona, Spain
| | - Iluminada Corripio
- Psychiatry Department, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau; Universitat Autònoma de Barcelona (UAB), Department of Psychiatry and Forensic Medicine, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
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Pretreatment abnormalities in white matter integrity predict one-year clinical outcome in first episode schizophrenia. Schizophr Res 2021; 228:241-248. [PMID: 33486391 DOI: 10.1016/j.schres.2020.12.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/17/2020] [Accepted: 12/06/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a serious mental illness for which the mainstay of treatment is antipsychotics. Up to 30% of schizophrenia patients show limited response to antipsychotics. Identifying these patients before treatment could guide individualized treatment for improving outcomes in those not likely to show robust benefit from antipsychotics. Diffusion tensor imaging was performed with 56 drug-naïve first-episode schizophrenia patients and 69 matched healthy controls. Patients were followed clinically after one-year of antipsychotic treatment and classified at that point into groups of 17 poor outcome and 39 good outcome patients based on whether they showed at least a 50% reduction of Positive and Negative Syndrome Scale (PANSS) scores from baseline. Tract-based spatial statistics were applied to assess white matter microstructure in the two patient subgroups and healthy controls. Poor outcome patients showed reduced pretreatment fractional anisotropy (FA) in left cingulum and anterior thalamic radiation and increased FA in right superior and inferior longitudinal fasciculus compared with good outcome patients. FA in each of these four tracts was decreased in both patient subgroups relative to healthy controls. Considered together, the four altered tracts showed promising ability to differentiate poor from good outcome patients (sensitivity = 74.4%, specificity = 95.2%, AUC = 0.90, p < 0.001), and superior prediction of clinical outcome to baseline PANSS scores (p < 0.015). Prediction of outcomes using DTI features was not related to duration of untreated psychosis. Baseline alterations in white matter integrity may identify schizophrenia patients less likely to respond to treatment, which could be useful information for stratification in clinical trials and for individualized treatment planning.
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30
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Yao C, Hu N, Cao H, Tang B, Zhang W, Xiao Y, Zhao Y, Gong Q, Lui S. A Multimodal Fusion Analysis of Pretreatment Anatomical and Functional Cortical Abnormalities in Responsive and Non-responsive Schizophrenia. Front Psychiatry 2021; 12:737179. [PMID: 34925087 PMCID: PMC8671303 DOI: 10.3389/fpsyt.2021.737179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/29/2021] [Indexed: 02/05/2023] Open
Abstract
Background: Antipsychotic medications provide limited long-term benefit to ~30% of schizophrenia patients. Multimodal magnetic resonance imaging (MRI) data have been used to investigate brain features between responders and nonresponders to antipsychotic treatment; however, these analytical techniques are unable to weigh the interrelationships between modalities. Here, we used multiset canonical correlation and joint independent component analysis (mCCA + jICA) to fuse MRI data to examine the shared and specific multimodal features between the patients and healthy controls (HCs) and between the responders and non-responders. Method: Resting-state functional and structural MRI data were collected from 55 patients with drug-naïve first-episode schizophrenia (FES) and demographically matched HCs. Based on the decrease in Positive and Negative Syndrome Scale scores from baseline to the 1-year follow-up, FES patients were divided into a responder group (RG) and a non-responder group (NRG). Gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) maps were used as features in mCCA + jICA. Results: Between FES patients and HCs, there were three modality-specific discriminative independent components (ICs) showing the difference in mixing coefficients (GMV-IC7, GMV-IC8, and fALFF-IC5). The fusion analysis indicated one modality-shared IC (GMV-IC2 and ReHo-IC2) and three modality-specific ICs (GMV-IC1, GMV-IC3, and GMV-IC6) between the RG and NRG. The right postcentral gyrus showed a significant difference in GMV features between FES patients and HCs and modality-shared features (GMV and ReHo) between responders and nonresponders. The modality-shared component findings were highlighted by GMV, mainly in the bilateral temporal gyrus and the right cerebellum associated with ReHo in the right postcentral gyrus. Conclusions: This study suggests that joint anatomical and functional features of the cortices may reflect an early pathophysiological mechanism that is related to a 1-year treatment response.
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Affiliation(s)
- Chenyang Yao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.,Department of Imaging Medicine, Inner Mongolia Autonomous Region People's Hospital, Hohhot, China
| | - Na Hu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Hengyi Cao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, United States.,Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, United States
| | - Biqiu Tang
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuan Xiao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Youjin Zhao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Su Lui
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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31
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Wei GX, Ge L, Chen LZ, Cao B, Zhang X. Structural abnormalities of cingulate cortex in patients with first-episode drug-naïve schizophrenia comorbid with depressive symptoms. Hum Brain Mapp 2020; 42:1617-1625. [PMID: 33296139 PMCID: PMC7978138 DOI: 10.1002/hbm.25315] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 11/27/2020] [Accepted: 11/30/2020] [Indexed: 11/07/2022] Open
Abstract
Depressive symptoms are common in patients with first-episode psychosis. However, the neural mechanisms underlying the comorbid depression in schizophrenia are still unknown. The main purpose of this study was to characterize the structural abnormalities of first-episodes drug-naïve (FEDN) schizophrenia comorbid with depression by utilizing both volume-based and surface-based morphometric measurements. Forty-two patients with FEDN schizophrenia and 29 healthy controls were recruited. The 24-item Hamilton Depression Rating Scale (HAMD-24) was administrated to divide all patients into depressive patients (DP) and non-depressive patients (NDP). Compared with NDP, DP had a significantly larger volume and surface area in the left isthmus cingulate cortex and also had a greater volume in the left posterior cingulate cortex. Correlation analysis showed that HAMD total score was positively correlated with the surface area of the left isthmus cingulate and gray matter volume of the left isthmus cingulate cortex. In addition, gray matter volume of the left isthmus cingulate was also correlated with the PANSS general psychopathology or total score. The findings suggest that prominent structural abnormalities of gray matter are mainly concentrated on the cingulate cortex in FEDN schizophrenia patients comorbid with depression, which may contribute to depressive symptoms and psychopathological symptoms.
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Affiliation(s)
- Gao-Xia Wei
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China.,CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Likun Ge
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Li-Zhen Chen
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Alberta, Canada
| | - Xiangyang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
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32
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McNabb CB, McIlwain ME, Anderson VM, Kydd RR, Sundram F, Russell BR. Aberrant white matter microstructure in treatment-resistant schizophrenia ✰. Psychiatry Res Neuroimaging 2020; 305:111198. [PMID: 33035754 DOI: 10.1016/j.pscychresns.2020.111198] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 09/28/2020] [Accepted: 09/28/2020] [Indexed: 02/01/2023]
Abstract
Treatment response in schizophrenia divides into three subcategories: treatment-responsive (first-line responders; FLR), treatment-resistant (TRS), and ultra-treatment-resistant schizophrenia (UTRS). White matter abnormalities could drive antipsychotic resistance but little work has investigated differences between TRS and UTRS. The current study aimed to establish whether differences in white matter structure are present across both treatment-resistant subtypes or if UTRS is distinct from TRS. Diffusion-weighted images were acquired for 18 individuals with TRS, 14 with UTRS, 18 FLR and 20 healthy controls. Measures of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD) were obtained using tract-based spatial statistics. Analysis of variance and post-hoc t-tests were conducted for each measure. Those with TRS had lower FA than healthy controls in superior longitudinal fasciculus, corpus callosum, thalamic radiation, corticospinal tract, internal capsule, corona radiata and fronto-occipital fasciculus (p<.05 FWE-corrected). Lower FA was also observed in TRS compared with UTRS in the superior longitudinal fasciculus (p<.05 FWE-corrected). No post-hoc tests survived corrections for multiple comparisons and no differences in MD, AD or RD were observed. These data suggest that microstructural deficits in white matter could contribute to TRS but suggest that other mechanisms may be more relevant for UTRS.
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Affiliation(s)
- Carolyn B McNabb
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand; School of Psychology and Clinical Language Sciences, University of Reading, Earley Gate, Reading RG6 7BE, United Kingdom
| | - Meghan E McIlwain
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - Valerie M Anderson
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - Robert R Kydd
- Department of Psychological Medicine, University of Auckland, Auckland City Hospital, 2 Park Road, Grafton, Auckland 1023, New Zealand
| | - Frederick Sundram
- Department of Psychological Medicine, University of Auckland, Auckland City Hospital, 2 Park Road, Grafton, Auckland 1023, New Zealand
| | - Bruce R Russell
- School of Pharmacy, University of Otago, PO Box 56, Dunedin 9054, New Zealand.
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Tronchin G, Akudjedu TN, Ahmed M, Holleran L, Hallahan B, Cannon DM, McDonald C. Progressive subcortical volume loss in treatment-resistant schizophrenia patients after commencing clozapine treatment. Neuropsychopharmacology 2020; 45:1353-1361. [PMID: 32268345 PMCID: PMC7298040 DOI: 10.1038/s41386-020-0665-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/20/2020] [Accepted: 03/24/2020] [Indexed: 02/07/2023]
Abstract
The association of antipsychotic medication with abnormal brain morphometry in schizophrenia remains uncertain. This study investigated subcortical morphometric changes 6 months after switching treatment to clozapine in patients with treatment-resistant schizophrenia compared with healthy volunteers, and the relationships between longitudinal volume changes and clinical variables. In total, 1.5T MRI images were acquired at baseline before commencing clozapine and again after 6 months of treatment for 33 patients with treatment-resistant schizophrenia and 31 controls, and processed using the longitudinal pipeline of Freesurfer v.5.3.0. Two-way repeated MANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. Whereas no significant subcortical volume differences were found between patients and controls at baseline (F(8,52) = 1.79; p = 0.101), there was a significant interaction between time, group and structure (F(7,143) = 52.54; p < 0.001). Corrected post-hoc analyses demonstrated that patients had significant enlargement of lateral ventricles (F(1,59) = 48.89; p < 0.001) and reduction of thalamus (F(1,59) = 34.85; p < 0.001), caudate (F(1,59) = 59.35; p < 0.001), putamen (F(1,59) = 87.20; p < 0.001) and hippocampus (F(1,59) = 14.49; p < 0.001) volumes. Thalamus and putamen volume reduction was associated with improvement in PANSS (r = 0.42; p = 0.021, r = 0.39; p = 0.033), SANS (r = 0.36; p = 0.049, r = 0.40; p = 0.027) and GAF (r = -0.39; p = 0.038, r = -0.42; p = 0.024) scores. Reduced thalamic volume over time was associated with increased serum clozapine level at follow-up (r = -0.44; p = 0.010). Patients with treatment-resistant schizophrenia display progressive subcortical volume deficits after switching to clozapine despite experiencing symptomatic improvement. Thalamo-striatal progressive volumetric deficit associated with symptomatic improvement after clozapine exposure may reflect an adaptive response related to improved outcome rather than a harmful process.
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Affiliation(s)
- Giulia Tronchin
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland.
| | - Theophilus N Akudjedu
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
- Institute of Medical Imaging & Visualisation, Faculty of Health & Social Science, Department of Medical Science & Public Science, Bournemouth University, Bournemouth, UK
| | - Mohamed Ahmed
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Laurena Holleran
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Brian Hallahan
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Dara M Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, Galway, H91TK33, Ireland
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Shah P, Plitman E, Iwata Y, Kim J, Nakajima S, Chan N, Brown EE, Caravaggio F, Torres E, Hahn M, Chakravarty MM, Remington G, Gerretsen P, Graff-Guerrero A. Glutamatergic neurometabolites and cortical thickness in treatment-resistant schizophrenia: Implications for glutamate-mediated excitotoxicity. J Psychiatr Res 2020; 124:151-158. [PMID: 32169688 DOI: 10.1016/j.jpsychires.2020.02.032] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 02/28/2020] [Accepted: 02/28/2020] [Indexed: 12/21/2022]
Abstract
Treatment-resistant schizophrenia may be related to structural brain alterations. However, the mechanisms underlying these changes remain unclear. The present study had two main aims: (1) to explore differences in cortical thickness between patients with treatment-resistant schizophrenia non-responsive to clozapine (ultra-treatment-resistant schizophrenia, UTRS), patients with treatment-resistant schizophrenia responsive to clozapine (Cloz-Resp), patients responsive to first-line non-clozapine antipsychotics (FL-Resp), and healthy controls (HCs); and (2) to test our hypothesis of structural compromise as a manifestation of neurotoxic effects from elevated glutamate (Glu) (i.e. glutamate-mediated excitotoxicity) by examining the relationships between glutamatergic neurometabolite levels (Glu and glutamate + glutamine (Glx)) in the dorsal anterior cingulate cortex (dACC) and cortical thickness. T1-weighted images and 1H-MRS data were obtained from UTRS (n = 24), Cloz-Resp (n = 25), FL-Resp (n = 19), and HCs (n = 26). Vertex-wise analyses showed that patients with UTRS had widespread cortical thinning in the bilateral frontal, temporal, parietal, and occipital gyri compared to HCs and FL-Resp patients. In the patient group, negative associations were found between dACC Glx levels and cortical thickness in the right dorsolateral prefrontal cortex after correcting for multiple comparisons and controlling for age, sex, antipsychotic dose, and illness severity. In conclusion, glutamate-mediated excitotoxicity may be one of the mechanisms underlying structural compromise seen in treatment-resistant schizophrenia. Future studies should longitudinally examine the associations between glutamatergic neurometabolite levels and cortical thickness in the context of treatment and illness progression.
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Affiliation(s)
- Parita Shah
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Eric Plitman
- Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Yusuke Iwata
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Julia Kim
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Shinichiro Nakajima
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Nathan Chan
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Eric E Brown
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada
| | - Fernando Caravaggio
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Edgardo Torres
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Margaret Hahn
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
| | - M Mallar Chakravarty
- Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Gary Remington
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
| | - Philip Gerretsen
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Ontario, Canada.
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Kim J, Plitman E, Iwata Y, Nakajima S, Mar W, Patel R, Chavez S, Chung JK, Caravaggio F, Chakravarty MM, Remington G, Gerretsen P, Graff-Guerrero A. Neuroanatomical profiles of treatment-resistance in patients with schizophrenia spectrum disorders. Prog Neuropsychopharmacol Biol Psychiatry 2020; 99:109839. [PMID: 31843627 DOI: 10.1016/j.pnpbp.2019.109839] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 11/10/2019] [Accepted: 12/12/2019] [Indexed: 01/18/2023]
Abstract
Widespread structrual abnormalities in subcortical brain regions have been identified in patients with schizophrenia. However, only a few studies have examined the neuroanatomical profiles of patients with treatment-resistant schizophrenia. The aim of this study was to compare differences in subcortical and hippocampal volumes between: (i) treatment-resistant patients who are non-responders to both first-line antipsychotics and clozapine (URS), (ii) treatment-resistant patients who are non-responders to first-line antipsychotics but are responders to clozapine (CLZ-Resp), (iii) responders to first-line antipsychotics (FL-Resp), and (iv) healthy controls. T1-weighted images of 103 participants (27 URS, 29 CLZ-Resp, 21 FL-Resp, and 26 healthy controls) were obtained. Group differences in striatal, thalamic, globus pallidus, amygdala, and hippocampus volumes were examined. Multiple regression analyses were performed to examine the associations between subcortical and hippocampal volumes and participant characteristics. The FL-Resp group showed larger striatal and globus pallidus volumes compared to the URS group and larger post-commissural putamen and globus pallidus volumes compared to healthy controls. The URS group showed smaller thalamic volume compared to healthy controls. There were no subcortical or hippocampal volume differences between the URS and CLZ-Resp groups. Differences in subcortical and hippocampal structural volumes were not related to symptom severity or chlorpromazine antipsychotic dose equivalents. Our findings suggest different structural volume alterations in subcortical brain regions between treatment-resistant schizophrenia and responders to first-line antipsychotics. Whether subcortical structure compromise is a distinct pathophysiological marker of treatment-resistant schizophrenia, or a result of antipsychotic exposure, remains to be explored.
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Affiliation(s)
- Julia Kim
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Eric Plitman
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Yusuke Iwata
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | | | - Wanna Mar
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Sofia Chavez
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Jun Ku Chung
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Fernando Caravaggio
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Gary Remington
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada; Schizophrenia Division, CAMH, Toronto, Ontario, Canada
| | - Philip Gerretsen
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada.
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Indicated association between polygenic risk score and treatment-resistance in a naturalistic sample of patients with schizophrenia spectrum disorders. Schizophr Res 2020; 218:55-62. [PMID: 32171635 DOI: 10.1016/j.schres.2020.03.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 03/02/2020] [Accepted: 03/05/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND One third of people diagnosed with schizophrenia fail to respond adequately to antipsychotic medication, resulting in persisting disabling symptoms, higher rates of hospitalization and higher costs for society. In an effort to better understand the mechanisms behind resistance to antipsychotic treatment in schizophrenia, we investigated its potential relationship to the genetic architecture of the disorder. METHODS Patients diagnosed with a schizophrenia spectrum disorder (N = 321) were classified as either being treatment-resistant (N = 108) or non-treatment-resistant (N = 213) to antipsychotic medication using defined consensus criteria. A schizophrenia polygenic risk score based on genome-wide association studies (GWAS) was calculated for each patient and binary logistic regression was performed to investigate the association between polygenetic risk and treatment resistance. We adjusted for principal components, batch number, age and sex. Additional analyses were performed to investigate associations with demographic and clinical variables. RESULTS High levels of polygenic risk score for schizophrenia significantly predicted treatment resistance (p = 0.003). The positive predictive value of the model was 61.5% and the negative predictive value was 71.7%. The association was significant for one (p = 0.01) out of five tested SNP significance thresholds. Season of birth was able to predict treatment-resistance in the regression model (p = 0.05). CONCLUSIONS The study indicates that treatment-resistance to antipsychotic medication is associated with higher polygenetic risk of schizophrenia, suggesting a link between antipsychotics mechanism of action and the genetic underpinnings of the disorder.
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Nucifora FC, Woznica E, Lee BJ, Cascella N, Sawa A. Treatment resistant schizophrenia: Clinical, biological, and therapeutic perspectives. Neurobiol Dis 2019; 131:104257. [PMID: 30170114 PMCID: PMC6395548 DOI: 10.1016/j.nbd.2018.08.016] [Citation(s) in RCA: 122] [Impact Index Per Article: 24.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 08/07/2018] [Accepted: 08/26/2018] [Indexed: 12/16/2022] Open
Abstract
Treatment resistant schizophrenia (TRS) refers to the significant proportion of schizophrenia patients who continue to have symptoms and poor outcomes despite treatment. While many definitions of TRS include failure of two different antipsychotics as a minimum criterion, the wide variability in inclusion criteria has challenged the consistency and reproducibility of results from studies of TRS. We begin by reviewing the clinical, neuroimaging, and neurobiological characteristics of TRS. We further review the current treatment strategies available, addressing clozapine, the first-line pharmacological agent for TRS, as well as pharmacological and non-pharmacological augmentation of clozapine including medication combinations, electroconvulsive therapy, repetitive transcranial magnetic stimulation, deep brain stimulation, and psychotherapies. We conclude by highlighting the most recent consensus for defining TRS proposed by the Treatment Response and Resistance in Psychosis Working Group, and provide our overview of future perspectives and directions that could help advance the field of TRS research, including the concept of TRS as a potential subtype of schizophrenia.
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Affiliation(s)
- Frederick C Nucifora
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA.
| | - Edgar Woznica
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Brian J Lee
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Nicola Cascella
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
| | - Akira Sawa
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Hospital, 600 N. Wolfe St., Baltimore, MD 21287, USA
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Kochunov P, Huang J, Chen S, Li Y, Tan S, Fan F, Feng W, Wang Y, Rowland LM, Savransky A, Du X, Chiappelli J, Chen S, Jahanshad N, Thompson PM, Ryan MC, Adhikari B, Sampath H, Cui Y, Wang Z, Yang F, Tan Y, Hong LE. White Matter in Schizophrenia Treatment Resistance. Am J Psychiatry 2019; 176:829-838. [PMID: 31352812 PMCID: PMC6773514 DOI: 10.1176/appi.ajp.2019.18101212] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
OBJECTIVE Failure of antipsychotic medications to resolve symptoms in patients with schizophrenia creates a clinical challenge that is known as treatment resistance. The causes of treatment resistance are unknown, but it is associated with earlier age at onset and more severe cognitive deficits. The authors tested the hypothesis that white matter deficits that are involved in both neurodevelopment and severity of cognitive deficits in schizophrenia are associated with a higher risk of treatment resistance. METHODS The study sample (N=122; mean age, 38.2 years) included schizophrenia patients at treatment initiation (N=45), patients whose symptoms were treatment responsive (N=40), and patients whose symptoms were treatment resistant (N=37), as well as healthy control subjects (N=78; mean age, 39.2 years). White matter regional vulnerability index (RVI) was tested as a predictor of treatment resistance and cognitive deficits. Higher RVI is indicative of better agreement between diffusion tensor imaging fractional anisotropy across the brain in an individual and the pattern identified by the largest-to-date meta-analysis of white matter deficits in schizophrenia. RESULTS Patients with treatment-resistant symptoms showed the highest white matter RVI (mean=0.38 [SD=0.2]), which was significantly higher than the RVI among patients with treatment-responsive symptoms (mean=0.30 [SD=0.02]). At the onset of treatment, schizophrenia patients showed significantly higher RVI than healthy control subjects (mean=0.18 [SD=0.03] and mean=0.13 [SD=0.02], respectively). RVIs were significantly correlated with performance on processing speed and negative symptoms. CONCLUSIONS Schizophrenia affects white matter microstructure in specific regional patterns. Susceptibility to white matter regional deficits is associated with an increased likelihood of treatment resistance. Developments to overcome schizophrenia treatment resistance should consider white matter as an important target.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA,Corresponding Authors: Dr. Kochunov (), Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA, Phone: (410) 402-6110, Fax: (410) 402-6778; Dr. Tan (), Beijing Huilongguan Hospital, Peking University, Huilongguan Clinical Medical School, Beijing, P. R. China, Phone: (800) 010-83024532, Fax: (800) 010-83020156
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yanli Li
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Wei Feng
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yunhui Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Laura M. Rowland
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Anya Savransky
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Meghann C. Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Bhim Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hemalatha Sampath
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yimin Cui
- Department of Pharmacy, Peking University First Hospital, Beijing, P.R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China,Corresponding Authors: Dr. Kochunov (), Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA, Phone: (410) 402-6110, Fax: (410) 402-6778; Dr. Tan (), Beijing Huilongguan Hospital, Peking University, Huilongguan Clinical Medical School, Beijing, P. R. China, Phone: (800) 010-83024532, Fax: (800) 010-83020156
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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Guo W, Liu F, Chen J, Wu R, Li L, Zhang Z, Chen H, Zhao J. Treatment effects of olanzapine on homotopic connectivity in drug-free schizophrenia at rest. World J Biol Psychiatry 2019. [PMID: 28649941 DOI: 10.1080/15622975.2017.1346280] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
OBJECTIVES Deficits in homotopic connectivity have been implicated in schizophrenia. However, alterations in homotopic connectivity associated with antipsychotic treatments in schizophrenia remain unclear due to lack of longitudinal studies. METHODS Seventeen drug-free patients with recurrent schizophrenia and 24 healthy controls underwent resting-state functional magnetic resonance imaging scans. The patients were scanned at three time points (baseline, at 6 weeks of treatment, and at 6 months of treatment). Voxel-mirrored homotopic connectivity (VMHC) was applied to analyse the imaging data to examine alterations in VMHC associated with antipsychotic treatment. RESULTS The results showed that patients with schizophrenia exhibited decreased VMHC in the default-mode network (such as the precuneus and inferior parietal lobule) and the motor and sensory processing regions (such as the lingual gyrus, fusiform gyrus and cerebellum lobule VI), which could be normalised or denormalised by olanzapine treatment. In addition, negative correlations were found between decreased VMHC and symptom severity in the patients at baseline. CONCLUSIONS The present study shows that olanzapine treatment can normalise or denormalise decreased homotopic connectivity in schizophrenia. The findings also provide a new perspective to understand treatment effects of antipsychotic drugs on homotopic connectivity in schizophrenia that contribute to the disconnection hypothesis of this disease.
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Affiliation(s)
- Wenbin Guo
- a Department of Psychiatry , The Second Xiangya Hospital, Central South University , Changsha , Hunan , China.,b Mental Health Institute of the Second Xiangya Hospital , Central South University , Changsha , Hunan , China.,c National Clinical Research Center on Mental Disorders , Changsha , Hunan , China.,d National Technology Institute on Mental Disorders , Changsha , Hunan , China.,e Hunan Key Laboratory of Psychiatry and Mental Health , Changsha , Hunan , China
| | - Feng Liu
- f Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology , University of Electronic Science and Technology of China , Chengdu , Sichuan , China
| | - Jindong Chen
- a Department of Psychiatry , The Second Xiangya Hospital, Central South University , Changsha , Hunan , China.,b Mental Health Institute of the Second Xiangya Hospital , Central South University , Changsha , Hunan , China.,c National Clinical Research Center on Mental Disorders , Changsha , Hunan , China.,d National Technology Institute on Mental Disorders , Changsha , Hunan , China.,e Hunan Key Laboratory of Psychiatry and Mental Health , Changsha , Hunan , China
| | - Renrong Wu
- a Department of Psychiatry , The Second Xiangya Hospital, Central South University , Changsha , Hunan , China.,b Mental Health Institute of the Second Xiangya Hospital , Central South University , Changsha , Hunan , China.,d National Technology Institute on Mental Disorders , Changsha , Hunan , China.,e Hunan Key Laboratory of Psychiatry and Mental Health , Changsha , Hunan , China.,f Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology , University of Electronic Science and Technology of China , Chengdu , Sichuan , China
| | - Lehua Li
- a Department of Psychiatry , The Second Xiangya Hospital, Central South University , Changsha , Hunan , China.,b Mental Health Institute of the Second Xiangya Hospital , Central South University , Changsha , Hunan , China.,c National Clinical Research Center on Mental Disorders , Changsha , Hunan , China.,d National Technology Institute on Mental Disorders , Changsha , Hunan , China.,e Hunan Key Laboratory of Psychiatry and Mental Health , Changsha , Hunan , China
| | - Zhikun Zhang
- g Mental Health Center , The First Affiliated Hospital, Guangxi Medical University , Nanning , Guangxi , China
| | - Huafu Chen
- f Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology , University of Electronic Science and Technology of China , Chengdu , Sichuan , China
| | - Jingping Zhao
- a Department of Psychiatry , The Second Xiangya Hospital, Central South University , Changsha , Hunan , China.,b Mental Health Institute of the Second Xiangya Hospital , Central South University , Changsha , Hunan , China.,c National Clinical Research Center on Mental Disorders , Changsha , Hunan , China.,d National Technology Institute on Mental Disorders , Changsha , Hunan , China.,e Hunan Key Laboratory of Psychiatry and Mental Health , Changsha , Hunan , China.,h Guangzhou Hui Ai Hospital , Affliated Brain Hospital of Guangzhou Medical University , Guangzhou , Guangdong , China
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Lin AS, Chan HY, Peng YC, Chen WJ. Severity in sustained attention impairment and clozapine-resistant schizophrenia: a retrospective study. BMC Psychiatry 2019; 19:220. [PMID: 31299940 PMCID: PMC6626410 DOI: 10.1186/s12888-019-2204-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 07/04/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Among patients with treatment-resistant schizophrenia (TRS), some exhibited further clozapine resistance (CR). This study aimed to investigate whether greater severity of treatment resistance in schizophrenia is associated with greater impairments in sustained attention. METHODS Patients with a DSM-IV-defined schizophrenia were recruited from a psychiatric center in northern Taiwan (April 2010 to October 2010). Both TRS and CR were determined retrospectively from participants' medical records following the consensus guidelines. The patients were divided into three groups: 102 non-TRS, 48 TRS without CR, and 54 TRS with CR. They underwent both undegraded and degraded Continuous Performance Tests (CPT), and their performance scores (d') were standardized against a community sample to derive age-, sex-, and education-adjusted z scores. RESULTS The TRS with CR group had significantly lower adjusted z scores of d' on both undegraded and degraded CPTs than the other two groups. Meanwhile, the differences between the TRS without CR group and the non-TRS group were not significant. Multivariable linear regression analyses with adjustment for covariates revealed a trend of gradient impairments on the degraded CPT from non-TRS to TRS without CR and to TRS with CR. The proportions of attentional deficits (an adjusted z score of ≤ - 2.5) on the degraded CPT also exhibited a significant trend, from 36.3% in the non-TRS group to 62.5% in the TRS without CR group and to 83.3% in the TRS with CR group. CONCLUSIONS Greater severity of treatment resistance in schizophrenia was associated with greater impairments in sustained attention, indicating some common vulnerability.
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Affiliation(s)
- An-Sheng Lin
- grid.454740.6Department of General Psychiatry, Taoyuan Psychiatric Center, Ministry of Health and Welfare, Taoyuan, Taiwan
| | - Hung-Yu Chan
- grid.454740.6Office of Superintendent, Taoyuan Psychiatric Center, Ministry of Health and Welfare, Taoyuan, Taiwan ,0000 0004 0546 0241grid.19188.39Department of Psychiatry, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ying-Chieh Peng
- grid.454740.6Department of General Psychiatry, Bali Psychiatric Center, Ministry of Health and Welfare, New Taipei City, Taiwan
| | - Wei J. Chen
- 0000 0004 0546 0241grid.19188.39Department of Psychiatry, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan ,0000 0004 0546 0241grid.19188.39Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, 17 Xu-Zhou Road, Taipei, 100 Taiwan
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41
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Soni S, Muthukrishnan SP, Samanchi R, Sood M, Kaur S, Sharma R. Pre-trial and pre-response EEG microstates in schizophrenia: An endophenotypic marker. Behav Brain Res 2019; 371:111964. [PMID: 31129232 DOI: 10.1016/j.bbr.2019.111964] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 04/17/2019] [Accepted: 05/18/2019] [Indexed: 01/15/2023]
Abstract
Cognitive deficits in Schizophrenia interfere with everyday functioning and social functioning. Strong familial associations in schizophrenia might serve to establish cognitive impairments as endophenotypic markers. Therefore, visuo-spatial working memory simulating day-to-day activities at high memory load was assessed in patients with schizophrenia, their first-degree relatives and healthy controls to explore pre-trial and pre-response EEG microstates and their intracranial generators. Twenty-eight patients with schizophrenia, first-degree relatives and matched healthy controls participated in the study. Brain activity during visuo-spatial working memory task was recorded using 128-channel electroencephalography. Pre-trial and pre-response microstate maps of correct and error trials were clustered across groups according to their topography. Microstate map parameters and underlying cortical sources were compared among groups. Pre-trial (correct) microstate Map 1 was significantly different between controls and patients which could qualify it as a state marker with its intracranial generator localized to right inferior frontal gyrus (rIFG). Pre-response (correct) microstate map was significantly different between controls and first-degree relatives which could be considered an endophenotypic marker for schizophrenia. No significant differences were observed for error trials between groups. rIFG which is involved in the execution of multi-component behaviour and selective inhibitory control could distinguish patients with schizophrenia from their first-degree relatives and healthy controls. Further, microstate based biomarkers have the potential to facilitate diagnosis of schizophrenia at a preclinical stage resulting in efficient diagnosis and better prognosis.
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Affiliation(s)
- Sunaina Soni
- Stress and Cognitive Electroimaging Laboratory, Department of Physiology, All India Institute of Medical Sciences, New Delhi, India.
| | - Suriya Prakash Muthukrishnan
- Stress and Cognitive Electroimaging Laboratory, Department of Physiology, All India Institute of Medical Sciences, New Delhi, India.
| | - Rupesh Samanchi
- Stress and Cognitive Electroimaging Laboratory, Department of Physiology, All India Institute of Medical Sciences, New Delhi, India.
| | - Mamta Sood
- Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India.
| | - Simran Kaur
- Stress and Cognitive Electroimaging Laboratory, Department of Physiology, All India Institute of Medical Sciences, New Delhi, India.
| | - Ratna Sharma
- Stress and Cognitive Electroimaging Laboratory, Department of Physiology, All India Institute of Medical Sciences, New Delhi, India.
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42
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Vita A, Minelli A, Barlati S, Deste G, Giacopuzzi E, Valsecchi P, Turrina C, Gennarelli M. Treatment-Resistant Schizophrenia: Genetic and Neuroimaging Correlates. Front Pharmacol 2019; 10:402. [PMID: 31040787 PMCID: PMC6476957 DOI: 10.3389/fphar.2019.00402] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Accepted: 04/01/2019] [Indexed: 12/11/2022] Open
Abstract
Schizophrenia is a severe neuropsychiatric disorder that affects approximately 0.5–1% of the population. Response to antipsychotic therapy is highly variable, and it is not currently possible to predict those patients who will or will not respond to antipsychotic medication. Furthermore, a high percentage of patients, approximately 30%, are classified as treatment-resistant (treatment-resistant schizophrenia; TRS). TRS is defined as a non-response to at least two trials of antipsychotic medication of adequate dose and duration. These patients are usually treated with clozapine, the only evidence-based pharmacotherapy for TRS. However, clozapine is associated with severe adverse events. For these reasons, there is an increasing interest to identify better targets for drug development of new compounds and to establish better biomarkers for existing medications. The ability of antipsychotics to improve psychotic symptoms is dependent on their antagonist and reverse agonist activities at different neuroreceptors, and some genetic association studies of TRS have focused on different pharmacodynamic factors. Some genetic studies have shown an association between antipsychotic response or TRS and neurodevelopment candidate genes, antipsychotic mechanisms of action (such as dopaminergic, serotonergic, GABAergic, and glutamatergic) or pharmacokinetic factors (i.e., differences in the cytochrome families). Moreover, there is a growing body of literature on the structural and functional neuroimaging research into TRS. Neuroimaging studies can help to uncover the underlying neurobiological reasons for such resistance and identify resistant patients earlier. Studies examining the neuropharmacological mechanisms of antipsychotics, including clozapine, can help to improve our knowledge of their action on the central nervous system, with further implications for the discovery of biomarkers and the development of new treatments. The identification of the underlying mechanisms of TRS is a major challenge for developing personalized medicine in the psychiatric field for schizophrenia treatment. The main goal of precision medicine is to use genetic and brain-imaging information to improve the safety, effectiveness, and health outcomes of patients via more efficiently targeted risk stratification, prevention, and tailored medication and treatment management approaches. The aim of this review is to summarize the state of art of pharmacogenetic, pharmacogenomic and neuroimaging studies in TRS.
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Affiliation(s)
- Antonio Vita
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alessandra Minelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Stefano Barlati
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Giacomo Deste
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy
| | - Edoardo Giacopuzzi
- Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Paolo Valsecchi
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Cesare Turrina
- Department of Mental Health and Addiction Services, ASST Spedali Civili, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.,Genetic Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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43
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Barry EF, Vanes LD, Andrews DS, Patel K, Horne CM, Mouchlianitis E, Hellyer PJ, Shergill SS. Mapping cortical surface features in treatment resistant schizophrenia with in vivo structural MRI. Psychiatry Res 2019; 274:335-344. [PMID: 30851596 DOI: 10.1016/j.psychres.2019.02.028] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 02/12/2019] [Accepted: 02/12/2019] [Indexed: 12/16/2022]
Abstract
Decreases in cortical volume (CV), thickness (CT) and surface area (SA) have been reported in individuals with schizophrenia by in vivo MRI studies. However, there are few studies that examine these cortical measures as potential biomarkers of treatment resistance (TR) and treatment response (NTR) in schizophrenia. This study used structural MRI to examine differences in CV, CT, and SA in 42 adults with schizophrenia (TR = 21, NTR = 21) and 23 healthy controls (HC) to test the hypothesis that individuals with TR schizophrenia have significantly greater reductions in these cortical measures compared to individuals with NTR schizophrenia. We found that individuals with TR schizophrenia showed significant reductions in CV and CT compared to individuals with NTR schizophrenia in right frontal and precentral regions, right parietal and occipital cortex, left temporal cortex and bilateral cingulate cortex. In line with previous literature, the temporal lobe and cingulate gyrus in both patient groups showed significant reductions of all three measures when compared to healthy controls. Taken together these results suggest that regional changes in CV and CT may index mechanisms specific to TR schizophrenia and potentially identify patients with TR schizophrenia for earlier treatment.
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Affiliation(s)
- Erica F Barry
- Cognition Schizophrenia and Imaging Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Department of Clinical Sciences, Cornell University College of Veterinary Medicine, Ithaca, NY, USA
| | - Lucy D Vanes
- Cognition Schizophrenia and Imaging Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Derek S Andrews
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Krisna Patel
- Cognition Schizophrenia and Imaging Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Charlotte M Horne
- Cognition Schizophrenia and Imaging Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Elias Mouchlianitis
- Cognition Schizophrenia and Imaging Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Peter J Hellyer
- Cognition Schizophrenia and Imaging Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Sukhi S Shergill
- Cognition Schizophrenia and Imaging Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
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44
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Crocker CE, Tibbo PG. Confused Connections? Targeting White Matter to Address Treatment Resistant Schizophrenia. Front Pharmacol 2018; 9:1172. [PMID: 30405407 PMCID: PMC6201564 DOI: 10.3389/fphar.2018.01172] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Accepted: 09/28/2018] [Indexed: 12/14/2022] Open
Abstract
Despite development of comprehensive approaches to treat schizophrenia and other psychotic disorders and improve outcomes, there remains a proportion (approximately one-third) of patients who are treatment resistant and will not have remission of psychotic symptoms despite adequate trials of pharmacotherapy. This level of treatment response is stable across all stages of the spectrum of psychotic disorders, including early phase psychosis and chronic schizophrenia. Our current pharmacotherapies are beneficial in decreasing positive symptomology in most cases, however, with little to no impact on negative or cognitive symptoms. Not all individuals with treatment resistant psychosis unfortunately, even benefit from the potential pharmacological reductions in positive symptoms. The existing pharmacotherapy for psychosis is targeted at neurotransmitter receptors. The current first and second generation antipsychotic medications all act on dopamine type 2 receptors with the second generation drugs also interacting significantly with serotonin type 1 and 2 receptors, and with varying pharmacodynamic profiles overall. This focus on developing dopaminergic/serotonergic antipsychotics, while beneficial, has not reduced the proportion of patients experiencing treatment resistance to date. Another pharmacological approach is imperative to address treatment resistance both for response overall and for negative symptoms in particular. There is research suggesting that changes in white matter integrity occur in schizophrenia and these may be more associated with cognition and even negative symptomology. Here we review the evidence that white matter abnormalities in the brain may be contributing to the symptomology of psychotic disorders. Additionally, we propose that white matter may be a viable pharmacological target for pharmacoresistant schizophrenia and discuss current treatments in development for schizophrenia that target white matter.
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Affiliation(s)
- Candice E Crocker
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.,Department of Diagnostic Imaging, Nova Scotia Health Authority, Halifax, NS, Canada
| | - Philip G Tibbo
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
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45
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Liu P, Fan Y, Wei Y, Zeng F, Li R, Fei N, Qin W. Altered structural and functional connectivity of the insula in functional dyspepsia. Neurogastroenterol Motil 2018; 30:e13345. [PMID: 29687532 DOI: 10.1111/nmo.13345] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2017] [Accepted: 03/02/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND Functional dyspepsia (FD) is a common functional gastrointestinal disease. Neuroimaging studies have identified that insula is involved in the pathogenesis of FD. However, less is known about structural and functional connectivity of insula in FD. METHODS In this study, 67 FD patients and 46 healthy controls (HCs) underwent structural MRI, resting-state functional MRI, diffusion tensor imaging (DTI) scans, and clinical assessment. We used the 3 neuroimaging modalities to investigate structural and functional connectivity of insula between FD patients and HCs, and we examined relationships between the neuroimaging findings and clinical symptoms. KEY RESULTS Compared with HCs, (i) FD patients had decreased gray matter density in right insula according to voxel-based morphometry method, which region was targeted as region of interest for further analysis of structural and functional connectivity; (ii) FD patients had lower connection probability in right anterior insula with right thalamus, right internal capsule (IC), and right external capsule (EC); (iii) FD patients had decreased functional connectivity of the right anterior insula with right thalamus and right pregenual anterior cingulate cortex (pACC); and (iv) FD patients had negative correlation between disease duration and the functional connectivity of right anterior insula with thalamus. CONCLUSIONS AND INFERENCES The present findings reveal that alterations of structural and/or functional connectivity of right anterior insula with regions, including thalamus, IC, EC, and pACC, may be mainly implicated in abnormalities of visceral sensory processing and related affective responses in FD patients. Finally, this study could enhance understanding of the pathophysiology of FD.
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Affiliation(s)
- P Liu
- School of Life Science and Technology, Life Science Research Center, Xidian University, Xi'an, China.,School of Life Science and Technology, Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xidian University, Xi'an, China
| | - Y Fan
- School of Life Science and Technology, Life Science Research Center, Xidian University, Xi'an, China.,School of Life Science and Technology, Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xidian University, Xi'an, China
| | - Y Wei
- School of Life Science and Technology, Life Science Research Center, Xidian University, Xi'an, China.,School of Life Science and Technology, Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xidian University, Xi'an, China
| | - F Zeng
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - R Li
- School of Life Science and Technology, Life Science Research Center, Xidian University, Xi'an, China.,School of Life Science and Technology, Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xidian University, Xi'an, China
| | - N Fei
- School of Life Science and Technology, Life Science Research Center, Xidian University, Xi'an, China.,School of Life Science and Technology, Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xidian University, Xi'an, China
| | - W Qin
- School of Life Science and Technology, Life Science Research Center, Xidian University, Xi'an, China.,School of Life Science and Technology, Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xidian University, Xi'an, China
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46
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Samanaite R, Gillespie A, Sendt KV, McQueen G, MacCabe JH, Egerton A. Biological Predictors of Clozapine Response: A Systematic Review. Front Psychiatry 2018; 9:327. [PMID: 30093869 PMCID: PMC6070624 DOI: 10.3389/fpsyt.2018.00327] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 06/29/2018] [Indexed: 01/04/2023] Open
Abstract
Background: Clozapine is the recommended antipsychotic for treatment-resistant schizophrenia (TRS) but there is significant variability between patients in the degree to which clozapine will improve symptoms. The biological basis of this variability is unknown. Although clozapine has efficacy in TRS, it can elicit adverse effects and initiation is often delayed. Identification of predictive biomarkers of clozapine response may aid initiation of clozapine treatment, as well as understanding of its mechanism of action. In this article we systematically review prospective or genetic studies of biological predictors of response to clozapine. Methods: We searched the PubMed database until 20th January 2018 for studies investigating "clozapine" AND ("response" OR "outcome") AND "schizophrenia." Inclusion required that studies examined a biological variable in relation to symptomatic response to clozapine. For all studies except genetic-studies, inclusion required that biological variables were measured before clozapine initiation. Results: Ninety-eight studies met the eligibility criteria and were included in the review, including neuroimaging, blood-based, cerebrospinal fluid (CSF)-based, and genetic predictors. The majority (70) are genetic studies, collectively investigating 379 different gene variants, however only three genetic variants (DRD3 Ser9Gly, HTR2A His452Tyr, and C825T GNB3) have independently replicated significant findings. Of the non-genetic variables, the most consistent predictors of a good response to clozapine are higher prefrontal cortical structural integrity and activity, and a lower ratio of the dopamine and serotonin metabolites, homovanillic acid (HVA): 5-hydroxyindoleacetic acid (5-HIAA) in CSF. Conclusions: Recommendations include that future studies should ensure adequate clozapine trial length and clozapine plasma concentrations, and may include multivariate models to increase predictive accuracy.
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Affiliation(s)
- Ruta Samanaite
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Amy Gillespie
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Kyra-Verena Sendt
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Grant McQueen
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - James H. MacCabe
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Alice Egerton
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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47
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Liu F, Tian H, Li J, Li S, Zhuo C. Altered voxel-wise gray matter structural brain networks in schizophrenia: Association with brain genetic expression pattern. Brain Imaging Behav 2018; 13:493-502. [DOI: 10.1007/s11682-018-9880-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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48
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Jiang Y, Luo C, Li X, Duan M, He H, Chen X, Yang H, Gong J, Chang X, Woelfer M, Biswal BB, Yao D. Progressive Reduction in Gray Matter in Patients with Schizophrenia Assessed with MR Imaging by Using Causal Network Analysis. Radiology 2018; 287:633-642. [DOI: 10.1148/radiol.2017171832] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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49
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McNabb CB, Tait RJ, McIlwain ME, Anderson VM, Suckling J, Kydd RR, Russell BR. Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia. Schizophr Res 2018; 195:160-167. [PMID: 29042073 DOI: 10.1016/j.schres.2017.10.015] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 09/25/2017] [Accepted: 10/09/2017] [Indexed: 12/21/2022]
Abstract
Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalization Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc t-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis.
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Affiliation(s)
- Carolyn B McNabb
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - Roger J Tait
- Department of Psychiatry, University of Cambridge, Cambridge and Peterborough Foundation NHS Trust, Herchel Smith Buidling for Brain & Mind Sciences, Forvie Site, Robinson Way, Cambridge CB2 0SZ, United Kingdom; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom
| | - Meghan E McIlwain
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - Valerie M Anderson
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge and Peterborough Foundation NHS Trust, Herchel Smith Buidling for Brain & Mind Sciences, Forvie Site, Robinson Way, Cambridge CB2 0SZ, United Kingdom; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom
| | - Robert R Kydd
- Department of Psychological Medicine, University of Auckland, Auckland City Hospital, 2 Park Road, Grafton, Auckland 1023, New Zealand
| | - Bruce R Russell
- School of Pharmacy, University of Otago, PO Box 56, Dunedin 9054, New Zealand.
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50
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de Bartolomeis A, Prinzivalli E, Callovini G, D'Ambrosio L, Altavilla B, Avagliano C, Iasevoli F. Treatment resistant schizophrenia and neurological soft signs may converge on the same pathology: Evidence from explanatory analysis on clinical, psychopathological, and cognitive variables. Prog Neuropsychopharmacol Biol Psychiatry 2018; 81:356-366. [PMID: 28887181 DOI: 10.1016/j.pnpbp.2017.09.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 08/17/2017] [Accepted: 09/03/2017] [Indexed: 12/31/2022]
Abstract
Here, we investigated neurological soft signs (NSSs) in treatment resistant schizophrenia (TRS) vs treatment responder schizophrenia (SZ) patients. TRS is a severe condition, affecting approximately one-third of schizophrenia patients and representing a relevant clinical challenge. NSSs are neurological abnormalities reportedly described in schizophrenia patients and linked to dysregulated network connections. We explored the possibility that NSSs may be: i) more severe in TRS patients; ii) differentially associated to clinical/cognitive variables in TRS vs SZ; iii) predictive of having TRS. In addition, we evaluated whether diagnosis may mediate NSSs associations with the above-mentioned variables. Consecutive patients with schizophrenia diagnosis underwent stringent assessment for TRS diagnosis. Demographics and clinical variables were recorded. Psychopathology (by Positive and Negative Syndrome Scale, PANSS), cognitive performances, and NSSs (by Neurological Evaluation Scale, NES) were tested. TRS had higher scores than SZ patients in total NES score and in almost all NES subscales, even after correction for duration of illness and antipsychotic dose (ANCOVA, p<0.05). NSSs significantly correlated with multiple clinical, psychopathological, and cognitive variables (above all: duration of disease and negative symptoms) in TRS but not in SZ patients. Two-way ANOVA showed NSS-x-diagnosis interaction in determining outcomes on multiple cognitive performances, but not in other clinical variables. However, simple main effect analysis detected a significant relationship between high severity NSSs and TRS diagnosis on multiple clinical and cognitive outcomes. Hierarchical regression analysis showed that diagnosis was among a discrete number of predictors yielding significant increases in variance explained on NES total, Sensory Integration and Other Signs subscales' scores. NSSs, together with antipsychotic dose and disease severity, were found to be significantly predictive of TRS diagnosis in a binary logistic regression model. These results suggest a stringent association between NSSs and TRS diagnosis, and may imply that NSSs association with clinical, psychopathological, and cognitive variables may be in part mediated by TRS diagnosis.
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Affiliation(s)
- Andrea de Bartolomeis
- Section of Psychiatry - Unit on Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, University School of Medicine Federico II, Naples, Italy.
| | - Emiliano Prinzivalli
- Section of Psychiatry - Unit on Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, University School of Medicine Federico II, Naples, Italy
| | - Gemma Callovini
- Section of Psychiatry - Unit on Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, University School of Medicine Federico II, Naples, Italy
| | - Luigi D'Ambrosio
- Section of Psychiatry - Unit on Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, University School of Medicine Federico II, Naples, Italy
| | - Benedetta Altavilla
- Section of Psychiatry - Unit on Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, University School of Medicine Federico II, Naples, Italy
| | - Camilla Avagliano
- Section of Psychiatry - Unit on Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, University School of Medicine Federico II, Naples, Italy
| | - Felice Iasevoli
- Section of Psychiatry - Unit on Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, University School of Medicine Federico II, Naples, Italy
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