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Rivera AD, Normanton JR, Butt AM, Azim K. The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials. Int J Mol Sci 2024; 25:4452. [PMID: 38674040 PMCID: PMC11050044 DOI: 10.3390/ijms25084452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 03/28/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
Schizophrenia is a significant worldwide health concern, affecting over 20 million individuals and contributing to a potential reduction in life expectancy by up to 14.5 years. Despite its profound impact, the precise pathological mechanisms underlying schizophrenia continue to remain enigmatic, with previous research yielding diverse and occasionally conflicting findings. Nonetheless, one consistently observed phenomenon in brain imaging studies of schizophrenia patients is the disruption of white matter, the bundles of myelinated axons that provide connectivity and rapid signalling between brain regions. Myelin is produced by specialised glial cells known as oligodendrocytes, which have been shown to be disrupted in post-mortem analyses of schizophrenia patients. Oligodendrocytes are generated throughout life by a major population of oligodendrocyte progenitor cells (OPC), which are essential for white matter health and plasticity. Notably, a decline in a specific subpopulation of OPC has been identified as a principal factor in oligodendrocyte disruption and white matter loss in the aging brain, suggesting this may also be a factor in schizophrenia. In this review, we analysed genomic databases to pinpoint intersections between aging and schizophrenia and identify shared mechanisms of white matter disruption and cognitive dysfunction.
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Affiliation(s)
- Andrea D. Rivera
- Department of Neuroscience, Institute of Human Anatomy, University of Padova, Via A. Gabelli 65, 35127 Padua, Italy;
| | - John R. Normanton
- GliaGenesis Limited, Orchard Lea, Horns Lane, Oxfordshire, Witney OX29 8NH, UK; (J.R.N.); (K.A.)
| | - Arthur M. Butt
- GliaGenesis Limited, Orchard Lea, Horns Lane, Oxfordshire, Witney OX29 8NH, UK; (J.R.N.); (K.A.)
- School of Pharmacy and Biomedical Science, University of Portsmouth, Hampshire PO1 2UP, UK
| | - Kasum Azim
- GliaGenesis Limited, Orchard Lea, Horns Lane, Oxfordshire, Witney OX29 8NH, UK; (J.R.N.); (K.A.)
- Independent Data Lab UG, Frauenmantelanger 31, 80937 Munich, Germany
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2
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López-Caballero F, Curtis M, Coffman BA, Salisbury DF. Is source-resolved magnetoencephalographic mismatch negativity a viable biomarker for early psychosis? Eur J Neurosci 2024; 59:1889-1906. [PMID: 37537883 PMCID: PMC10837325 DOI: 10.1111/ejn.16107] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/04/2023] [Accepted: 07/20/2023] [Indexed: 08/05/2023]
Abstract
Mismatch negativity (MMN) is an auditory event-related response reflecting the pre-attentive detection of novel stimuli and is a biomarker of cortical dysfunction in schizophrenia (SZ). MMN to pitch (pMMN) and to duration (dMMN) deviant stimuli are impaired in chronic SZ, but it is less clear if MMN is reduced in first-episode SZ, with inconsistent findings in scalp-level EEG studies. Here, we investigated the neural generators of pMMN and dMMN with MEG recordings in 26 first-episode schizophrenia spectrum (FEsz) and 26 matched healthy controls (C). We projected MEG inverse solutions into precise functionally meaningful auditory cortex areas. MEG-derived MMN sources were in bilateral primary auditory cortex (A1) and belt areas. In A1, pMMN FEsz reduction showed a trend towards statistical significance (F(1,50) = 3.31; p = .07), and dMMN was reduced in FEsz (F(1,50) = 4.11; p = .04). Hypothesis-driven comparisons at each hemisphere revealed dMMN reduction in FEsz occurred in the left (t(56) = 2.23; p = .03; d = .61) but not right (t(56) = 1.02; p = .31; d = .28) hemisphere, with a moderate effect size. The added precision of MEG source solution with high-resolution MRI and parcellation of A1 may be requisite to detect the emerging pathophysiology and indicates a critical role for left hemisphere pathology at psychosis onset. However, the moderate effect size in left A1, albeit larger than reported in scalp MMN meta-analyses, casts doubt on the clinical utility of MMN for differential diagnosis, as a majority of patients will overlap with the healthy individual's distribution.
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Affiliation(s)
- Fran López-Caballero
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Mark Curtis
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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3
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Salisbury DF, Seebold D, Longenecker JM, Coffman BA, Yeh FC. White matter tracts differentially associated with auditory hallucinations in first-episode psychosis: A correlational tractography diffusion spectrum imaging study. Schizophr Res 2024; 265:4-13. [PMID: 37321880 PMCID: PMC10719419 DOI: 10.1016/j.schres.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 06/02/2023] [Accepted: 06/03/2023] [Indexed: 06/17/2023]
Abstract
Auditory hallucinations (AH) are a debilitating symptom in psychosis, impacting cognition and real world functioning. Recent thought conceptualizes AH as a consequence of long-range brain communication dysfunction, or circuitopathy, within the auditory sensory/perceptual, language, and cognitive control systems. Recently we showed in first-episode psychosis (FEP) that, despite overall intact white matter integrity in the cortical-cortical and cortical-subcortical language tracts and the callosal tracts connecting auditory cortices, the severity of AH correlated inversely with white matter integrity. However, that hypothesis-driven isolation of specific tracts likely missed important white matter concomitants of AH. In this report, we used a whole-brain data-driven dimensional approach using correlational tractography to associate AH severity with white matter integrity in a sample of 175 individuals. Diffusion Spectrum Imaging (DSI) was used to image diffusion distribution. Quantitative Anisotropy (QA) in three tracts was greater with increased AH severity (FDR < 0.001) and QA in three tracts was lower with increased AH severity (FDR < 0.01). White matter tracts showing associations between QA and AH were generally associated with frontal-parietal-temporal connectivity (tracts with known relevance for cognitive control and the language system), in the cingulum bundle, and in prefrontal inter-hemispheric connectivity. The results of this whole brain data-driven analysis suggest that subtle white matter alterations connecting frontal, parietal, and temporal lobes in the service of sensory-perceptual, language/semantic, and cognitive control processes impact the expression of auditory hallucination in FEP. Disentangling the distributed neural circuits involved in AH should help to develop novel interventions, such as non-invasive brain stimulation.
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Affiliation(s)
- Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Dylan Seebold
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Julia M Longenecker
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; VISN 4 Mental Illness Research Education and Clinical Center (MIRECC), Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Fang-Chen Yeh
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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4
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Constantinides C, Baltramonaityte V, Caramaschi D, Han LKM, Lancaster TM, Zammit S, Freeman TP, Walton E. Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study. Cortex 2024; 172:1-13. [PMID: 38154374 DOI: 10.1016/j.cortex.2023.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 09/22/2023] [Accepted: 11/23/2023] [Indexed: 12/30/2023]
Abstract
Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often 'older' than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21-24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = -.21; 95% CI -2.00, 1.58; p = .82; Cohen's d = -.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.
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Affiliation(s)
| | | | - Doretta Caramaschi
- Department of Psychology, Faculty of Health and Life Sciences, University of Exeter, UK
| | - Laura K M Han
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; Orygen, Parkville, Australia
| | | | - Stanley Zammit
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom P Freeman
- Addiction and Mental Health Group (AIM), Department of Psychology, University of Bath, UK
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5
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Georgiadis F, Larivière S, Glahn D, Hong LE, Kochunov P, Mowry B, Loughland C, Pantelis C, Henskens FA, Green MJ, Cairns MJ, Michie PT, Rasser PE, Catts S, Tooney P, Scott RJ, Schall U, Carr V, Quidé Y, Krug A, Stein F, Nenadić I, Brosch K, Kircher T, Gur R, Gur R, Satterthwaite TD, Karuk A, Pomarol-Clotet E, Radua J, Fuentes-Claramonte P, Salvador R, Spalletta G, Voineskos A, Sim K, Crespo-Facorro B, Tordesillas Gutiérrez D, Ehrlich S, Crossley N, Grotegerd D, Repple J, Lencer R, Dannlowski U, Calhoun V, Rootes-Murdy K, Demro C, Ramsay IS, Sponheim SR, Schmidt A, Borgwardt S, Tomyshev A, Lebedeva I, Höschl C, Spaniel F, Preda A, Nguyen D, Uhlmann A, Stein DJ, Howells F, Temmingh HS, Diaz Zuluaga AM, López Jaramillo C, Iasevoli F, Ji E, Homan S, Omlor W, Homan P, Kaiser S, Seifritz E, Misic B, Valk SL, Thompson P, van Erp TGM, Turner JA, Bernhardt B, Kirschner M. Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study. Mol Psychiatry 2024:10.1038/s41380-024-02442-7. [PMID: 38336840 DOI: 10.1038/s41380-024-02442-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/08/2024] [Accepted: 01/18/2024] [Indexed: 02/12/2024]
Abstract
Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.
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Affiliation(s)
- Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland.
| | - Sara Larivière
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - David Glahn
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, US
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, US
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, Australia
| | - Carmel Loughland
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, USA
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, VIC, Australia
| | - Frans A Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Melissa J Green
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Murray J Cairns
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Patricia T Michie
- School of Psychological Sciences, University of Newcastle, Newcastle, NSW, Australia
| | - Paul E Rasser
- School of Medicine and Public Health, College of Health, Medicine, and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia
| | - Stanley Catts
- Faculty of Medicine, University of Queensland, St Lucia, QLD, Australia
| | - Paul Tooney
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Rodney J Scott
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Vaughan Carr
- School of Clinical Medicine, Discipline of Psychiatry, UNSW Sydney, Sydney, NSW, Australia
| | - Yann Quidé
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Axel Krug
- University Hospital Bonn, Department of Psychiatry and Psychotherapy, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Frederike Stein
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Igor Nenadić
- Department. of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Raquel Gur
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ruben Gur
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | | | - Aristotle Voineskos
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
| | | | - Diana Tordesillas Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
| | - Stefan Ehrlich
- Division of Psychological & Social Medicine and Developmental Neurosciences, Technischen Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Nicolas Crossley
- Department of Psychiatry, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Vince Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Kelly Rootes-Murdy
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Caroline Demro
- University of Minnesota Department of Psychology, Minneapolis, MN, USA
- Minneapolis VA Health Care System, Minneapolis, MN, USA
| | - Ian S Ramsay
- University of Minnesota Department of Psychiatry & Behavioral Sciences, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- University of Minnesota Department of Psychiatry & Behavioral Sciences, Minneapolis, MN, USA
| | - Andre Schmidt
- University of Basel, Department of Psychiatry, Basel, Switzerland
| | | | | | - Irina Lebedeva
- Mental Health Research Center, Moscow, Russian Federation
| | - Cyril Höschl
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Dana Nguyen
- Department of Pediatric Neurology, University of California Irvine, Irvine, CA, USA
| | - Anne Uhlmann
- Department of child and adolescent psychiatry, TU Dresden, Dresden, Germany
| | - Dan J Stein
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Fleur Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Henk S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Ana M Diaz Zuluaga
- Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia
| | - Carlos López Jaramillo
- Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia
| | - Felice Iasevoli
- University of Naples, Department of Neuroscience, Naples, Italy
| | - Ellen Ji
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Wolfgang Omlor
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Bratislav Misic
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - Sofie L Valk
- Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
| | - Paul Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Theo G M van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, the Ohio State University, Columbus, OH, USA
| | - Boris Bernhardt
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland.
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland.
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Mohan KN. Editorial: New insights into investigating schizophrenia as a disorder of molecular pathways. Front Mol Neurosci 2024; 17:1360616. [PMID: 38274843 PMCID: PMC10805877 DOI: 10.3389/fnmol.2024.1360616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 01/02/2024] [Indexed: 01/27/2024] Open
Affiliation(s)
- Kommu Naga Mohan
- Molecular Biology and Genetics Laboratory, Department of Biological Sciences, BITS Pilani Hyderabad Campus, Hyderabad, India
- Centre for Human Disease Research, BITS Pilani Hyderabad Campus, Hyderabad, India
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7
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Howes OD, Bukala BR, Beck K. Schizophrenia: from neurochemistry to circuits, symptoms and treatments. Nat Rev Neurol 2024; 20:22-35. [PMID: 38110704 DOI: 10.1038/s41582-023-00904-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2023] [Indexed: 12/20/2023]
Abstract
Schizophrenia is a leading cause of global disability. Current pharmacotherapy for the disease predominantly uses one mechanism - dopamine D2 receptor blockade - but often shows limited efficacy and poor tolerability. These limitations highlight the need to better understand the aetiology of the disease to aid the development of alternative therapeutic approaches. Here, we review the latest meta-analyses and other findings on the neurobiology of prodromal, first-episode and chronic schizophrenia, and the link to psychotic symptoms, focusing on imaging evidence from people with the disorder. This evidence demonstrates regionally specific neurotransmitter alterations, including higher glutamate and dopamine measures in the basal ganglia, and lower glutamate, dopamine and γ-aminobutyric acid (GABA) levels in cortical regions, particularly the frontal cortex, relative to healthy individuals. We consider how dysfunction in cortico-thalamo-striatal-midbrain circuits might alter brain information processing to underlie psychotic symptoms. Finally, we discuss the implications of these findings for developing new, mechanistically based treatments and precision medicine for psychotic symptoms, as well as negative and cognitive symptoms.
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Affiliation(s)
- Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Faculty of Medicine, Institute of Clinical Sciences, Imperial College London, London, UK.
| | - Bernard R Bukala
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Katherine Beck
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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Lewis L, Corcoran M, Cho KIK, Kwak Y, Hayes RA, Larsen B, Jalbrzikowski M. Age-associated alterations in thalamocortical structural connectivity in youths with a psychosis-spectrum disorder. Schizophrenia (Heidelb) 2023; 9:86. [PMID: 38081873 PMCID: PMC10713597 DOI: 10.1038/s41537-023-00411-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/30/2023] [Indexed: 12/23/2023]
Abstract
Psychotic symptoms typically emerge in adolescence. Age-associated thalamocortical connectivity differences in psychosis remain unclear. We analyzed diffusion-weighted imaging data from 1254 participants 8-23 years old (typically developing (TD):N = 626, psychosis-spectrum (PS): N = 329, other psychopathology (OP): N = 299) from the Philadelphia Neurodevelopmental Cohort. We modeled thalamocortical tracts using deterministic fiber tractography, extracted Q-Space Diffeomorphic Reconstruction (QSDR) and diffusion tensor imaging (DTI) measures, and then used generalized additive models to determine group and age-associated thalamocortical connectivity differences. Compared to other groups, PS exhibited thalamocortical reductions in QSDR global fractional anisotropy (GFA, p-values range = 3.0 × 10-6-0.05) and DTI fractional anisotropy (FA, p-values range = 4.2 × 10-4-0.03). Compared to TD, PS exhibited shallower thalamus-prefrontal age-associated increases in GFA and FA during mid-childhood, but steeper age-associated increases during adolescence. TD and OP exhibited decreases in thalamus-frontal mean and radial diffusivities during adolescence; PS did not. Altered developmental trajectories of thalamocortical connectivity may contribute to the disruptions observed in adults with psychosis.
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Affiliation(s)
- Lydia Lewis
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Mary Corcoran
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Kang Ik K Cho
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - YooBin Kwak
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Rebecca A Hayes
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Bart Larsen
- Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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Chopra S, Segal A, Oldham S, Holmes A, Sabaroedin K, Orchard ER, Francey SM, O’Donoghue B, Cropley V, Nelson B, Graham J, Baldwin L, Tiego J, Yuen HP, Allott K, Alvarez-Jimenez M, Harrigan S, Fulcher BD, Aquino K, Pantelis C, Wood SJ, Bellgrove M, McGorry PD, Fornito A. Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis. JAMA Psychiatry 2023; 80:1246-1257. [PMID: 37728918 PMCID: PMC10512169 DOI: 10.1001/jamapsychiatry.2023.3293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 06/21/2023] [Indexed: 09/22/2023]
Abstract
Importance Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. Objective To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. Design, Settings, and Participants This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. Main Outcomes and Measures Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance. Results Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression. Conclusion and Relevance These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.
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Affiliation(s)
- Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Ashlea Segal
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Stuart Oldham
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Alexander Holmes
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Kristina Sabaroedin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Radiology, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Paediatrics, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Edwina R. Orchard
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Child Study Centre, Yale University, New Haven, Connecticut
| | - Shona M. Francey
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Brian O’Donoghue
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
| | - Barnaby Nelson
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jessica Graham
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lara Baldwin
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jeggan Tiego
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Hok Pan Yuen
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Kelly Allott
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Mario Alvarez-Jimenez
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Susy Harrigan
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Mental Health, Melbourne School of Global and Population Health, The University of Melbourne, Parkville, Victoria, Australian
| | - Ben D. Fulcher
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Kevin Aquino
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Centre for Complex Systems, University of Sydney, Sydney, New South Wales, Australia
| | - Christos Pantelis
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
- NorthWestern Mental Health, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Western Health Sunshine Hospital, St Albans, Victoria, Australia
| | - Stephen J. Wood
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- School of Psychology, University of Birmingham, Edgbaston, United Kingdom
| | - Mark Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
| | - Patrick D. McGorry
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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10
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Calarco N, Oliver LD, Joseph M, Hawco C, Dickie EW, DeRosse P, Gold JM, Foussias G, Argyelan M, Malhotra AK, Buchanan RW, Voineskos AN. Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls. Schizophr Bull 2023; 49:1518-1529. [PMID: 36869812 PMCID: PMC10686342 DOI: 10.1093/schbul/sbac216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
BACKGROUND AND HYPOTHESIS Neurocognitive and social cognitive abilities are important contributors to functional outcomes in schizophrenia spectrum disorders (SSDs). An unanswered question of considerable interest is whether neurocognitive and social cognitive deficits arise from overlapping or distinct white matter impairment(s). STUDY DESIGN We sought to fill this gap, by harnessing a large sample of individuals from the multi-center Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) dataset, unique in its collection of advanced diffusion imaging and an extensive battery of cognitive assessments. We applied canonical correlation analysis to estimates of white matter microstructure, and cognitive performance, across people with and without an SSD. STUDY RESULTS Our results established that white matter circuitry is dimensionally and strongly related to both neurocognition and social cognition, and that microstructure of the uncinate fasciculus and the rostral body of the corpus callosum may assume a "privileged role" subserving both. Further, we found that participant-wise estimates of white matter microstructure, weighted by cognitive performance, were largely consistent with participants' categorical diagnosis, and predictive of (cross-sectional) functional outcomes. CONCLUSIONS The demonstrated strength of the relationship between white matter circuitry and neurocognition and social cognition underscores the potential for using relationships among these variables to identify biomarkers of functioning, with potential prognostic and therapeutic implications.
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Affiliation(s)
- Navona Calarco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Michael Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Pamela DeRosse
- Division of Psychiatry Research, Division of Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - James M Gold
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - George Foussias
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Miklos Argyelan
- Division of Psychiatry Research, Division of Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Anil K Malhotra
- Division of Psychiatry Research, Division of Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Robert W Buchanan
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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11
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McKenna F, Gupta PK, Sui YV, Bertisch H, Gonen O, Goff DC, Lazar M. Microstructural and Microvascular Alterations in Psychotic Spectrum Disorders: A Three-Compartment Intravoxel Incoherent Imaging and Free Water Model. Schizophr Bull 2023; 49:1542-1553. [PMID: 36921060 PMCID: PMC10686346 DOI: 10.1093/schbul/sbad019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
BACKGROUND AND HYPOTHESIS Microvascular and inflammatory mechanisms have been hypothesized to be involved in the pathophysiology of psychotic spectrum disorders (PSDs). However, data evaluating these hypotheses remain limited. STUDY DESIGN We applied a three-compartment intravoxel incoherent motion free water imaging (IVIM-FWI) technique that estimates the perfusion fraction (PF), free water fraction (FW), and anisotropic diffusion of tissue (FAt) to examine microvascular and microstructural changes in gray and white matter in 55 young adults with a PSD compared to 37 healthy controls (HCs). STUDY RESULTS We found significantly increased PF, FW, and FAt in gray matter regions, and significantly increased PF, FW, and decreased FAt in white matter regions in the PSD group versus HC. Furthermore, in patients, but not in the HC group, increased PF, FW, and FAt in gray matter and increased PF in white matter were significantly associated with poor performance on several cognitive tests assessing memory and processing speed. We additionally report significant associations between IVIM-FWI metrics and myo-inositol, choline, and N-acetylaspartic acid magnetic resonance spectroscopy imaging metabolites in the posterior cingulate cortex, which further supports the validity of PF, FW, and FAt as microvascular and microstructural biomarkers of PSD. Finally, we found significant relationships between IVIM-FWI metrics and the duration of psychosis in gray and white matter regions. CONCLUSIONS The three-compartment IVIM-FWI model provides metrics that are associated with cognitive deficits and may reflect disease progression.
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Affiliation(s)
- Faye McKenna
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - Pradeep Kumar Gupta
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Yu Veronica Sui
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - Hilary Bertisch
- Northwell Health, Zucker Hillside Hospital, New York, NY, USA
| | - Oded Gonen
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
| | - Donald C Goff
- Department of Psychiatry, New York University School of Medicine, New York, NY, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Mariana Lazar
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, USA
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12
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Domagała A, Domagała L, Kopiś-Posiej N, Harciarek M, Krukow P. Differentiation of the retinal morphology aging trajectories in schizophrenia and their associations with cognitive dysfunctions. Front Psychiatry 2023; 14:1207608. [PMID: 37539329 PMCID: PMC10396397 DOI: 10.3389/fpsyt.2023.1207608] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 06/30/2023] [Indexed: 08/05/2023] Open
Abstract
Previous studies evaluating the morphology of the selected retinal layers in schizophrenia showed abnormalities regarding macular thickness, retinal nerve fiber layer (RNLF), and ganglion cell complex (GCC). Concurrently, accumulating neuroimaging results suggest that structural alterations of the brain in this disease might be an effect of accelerated aging. Referring to these findings, we aimed to determine whether the thinning of the retinal layers assessed with the optic coherence tomography (OCT) in a group of schizophrenia patients (n = 60) presents a significant age-related decrease exceeding potential changes noted in the control group (n = 61). Samples of patients and controls were divided into three age subgroups, namely, younger, middle-aged, and older participants. OCT outcomes, such as macular thickness and volume, macular RNFL, peripapillary RNFL, and GCC, were analyzed concerning a diagnosis status (controls vs. patients) and age subgroups. Additionally, associations between retinal parameters, age, and selected cognitive functions were evaluated. post-hoc tests revealed that macular thickness and volume in patients undergo significant age-dependent thinning, which was not observed in the control group. Regression analyses confirmed the association between macular morphology and age. Selected speed-dependent cognitive functions in patients decreased significantly with age, and these features were also significantly associated with some OCT outcomes also after controlling for antipsychotic treatment. Our results suggest that reduced measures of retinal structure detected in schizophrenia may be an effect of accelerated aging; however, further research is needed using computational solutions derived from brain imaging studies based on large datasets covering representatives of all age groups.
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Affiliation(s)
- Adam Domagała
- Department of Clinical Neuropsychiatry, Medical University of Lublin, Lublin, Poland
| | - Lucyna Domagała
- Non-Public Health Facility “OKO-MED”, Sandomierz, Sandomierz County, Poland
| | - Natalia Kopiś-Posiej
- Department of Clinical Neuropsychiatry, Medical University of Lublin, Lublin, Poland
| | - Michał Harciarek
- Department of Neuropsychology, Institute of Psychology, University of Gdańsk, Gdansk, Poland
| | - Paweł Krukow
- Department of Clinical Neuropsychiatry, Medical University of Lublin, Lublin, Poland
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13
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Abstract
The synaptic hypothesis of schizophrenia has been highly influential. However, new approaches mean there has been a step-change in the evidence available, and some tenets of earlier versions are not supported by recent findings. Here, we review normal synaptic development and evidence from structural and functional imaging and post-mortem studies that this is abnormal in people at risk and with schizophrenia. We then consider the mechanism that could underlie synaptic changes and update the hypothesis. Genome-wide association studies have identified a number of schizophrenia risk variants converging on pathways regulating synaptic elimination, formation and plasticity, including complement factors and microglial-mediated synaptic pruning. Induced pluripotent stem cell studies have demonstrated that patient-derived neurons show pre- and post-synaptic deficits, synaptic signalling alterations, and elevated, complement-dependent elimination of synaptic structures compared to control-derived lines. Preclinical data show that environmental risk factors linked to schizophrenia, such as stress and immune activation, can lead to synapse loss. Longitudinal MRI studies in patients, including in the prodrome, show divergent trajectories in grey matter volume and cortical thickness compared to controls, and PET imaging shows in vivo evidence for lower synaptic density in patients with schizophrenia. Based on this evidence, we propose version III of the synaptic hypothesis. This is a multi-hit model, whereby genetic and/or environmental risk factors render synapses vulnerable to excessive glia-mediated elimination triggered by stress during later neurodevelopment. We propose the loss of synapses disrupts pyramidal neuron function in the cortex to contribute to negative and cognitive symptoms and disinhibits projections to mesostriatal regions to contribute to dopamine overactivity and psychosis. It accounts for the typical onset of schizophrenia in adolescence/early adulthood, its major risk factors, and symptoms, and identifies potential synaptic, microglial and immune targets for treatment.
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Affiliation(s)
- Oliver D Howes
- Faculty of Medicine, Institute of Clinical Sciences (ICS), Imperial College London, London, W12 0NN, UK.
- Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, W12 0NN, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
| | - Ellis Chika Onwordi
- Faculty of Medicine, Institute of Clinical Sciences (ICS), Imperial College London, London, W12 0NN, UK.
- Psychiatric Imaging Group, Medical Research Council, London Institute of Medical Sciences, Hammersmith Hospital, London, W12 0NN, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
- Centre for Psychiatry and Mental Health, Wolfson Institute of Population Health, Queen Mary University of London, London, E1 2AB, UK.
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14
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Cetin-Karayumak S, Lyall AE, Di Biase MA, Seitz-Holland J, Zhang F, Kelly S, Elad D, Pearlson G, Tamminga CA, Sweeney JA, Clementz BA, Schretlen D, Stegmayer K, Walther S, Lee J, Crow T, James A, Voineskos A, Buchanan RW, Szeszko PR, Malhotra AK, Keshavan M, Shenton ME, Rathi Y, Pasternak O, Kubicki M. Characterization of the extracellular free water signal in schizophrenia using multi-site diffusion MRI harmonization. Mol Psychiatry 2023; 28:2030-2038. [PMID: 37095352 DOI: 10.1038/s41380-023-02068-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 03/06/2023] [Accepted: 04/05/2023] [Indexed: 04/26/2023]
Abstract
Studies applying Free Water Imaging have consistently reported significant global increases in extracellular free water (FW) in populations of individuals with early psychosis. However, these published studies focused on homogenous clinical participant groups (e.g., only first episode or chronic), thereby limiting our understanding of the time course of free water elevations across illness stages. Moreover, the relationship between FW and duration of illness has yet to be directly tested. Leveraging our multi-site diffusion magnetic resonance imaging(dMRI) harmonization approach, we analyzed dMRI scans collected by 12 international sites from 441 healthy controls and 434 individuals diagnosed with schizophrenia-spectrum disorders at different illness stages and ages (15-58 years). We characterized the pattern of age-related FW changes by assessing whole brain white matter in individuals with schizophrenia and healthy controls. In individuals with schizophrenia, average whole brain FW was higher than in controls across all ages, with the greatest FW values observed from 15 to 23 years (effect size range = [0.70-0.87]). Following this peak, FW exhibited a monotonic decrease until reaching a minima at the age of 39 years. After 39 years, an attenuated monotonic increase in FW was observed, but with markedly smaller effect sizes when compared to younger patients (effect size range = [0.32-0.43]). Importantly, FW was found to be negatively associated with duration of illness in schizophrenia (p = 0.006), independent of the effects of other clinical and demographic data. In summary, our study finds in a large, age-diverse sample that participants with schizophrenia with a shorter duration of illness showed higher FW values compared to participants with more prolonged illness. Our findings provide further evidence that elevations in the FW are present in individuals with schizophrenia, with the greatest differences in the FW being observed in those at the early stages of the disorder, which might suggest acute extracellular processes.
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Affiliation(s)
- Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria A Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sinead Kelly
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Doron Elad
- Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | | | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Katharina Stegmayer
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Jungsun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Tim Crow
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Anthony James
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | | | - Robert W Buchanan
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Philip R Szeszko
- Departments of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education, and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Anil K Malhotra
- The Feinstein Institutes for Medical Research and Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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15
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Wagner SK, Cortina-Borja M, Silverstein SM, Zhou Y, Romero-Bascones D, Struyven RR, Trucco E, Mookiah MRK, MacGillivray T, Hogg S, Liu T, Williamson DJ, Pontikos N, Patel PJ, Balaskas K, Alexander DC, Stuart KV, Khawaja AP, Denniston AK, Rahi JS, Petzold A, Keane PA. Association Between Retinal Features From Multimodal Imaging and Schizophrenia. JAMA Psychiatry 2023; 80:478-487. [PMID: 36947045 PMCID: PMC10034669 DOI: 10.1001/jamapsychiatry.2023.0171] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/23/2023] [Indexed: 03/23/2023]
Abstract
Importance The potential association of schizophrenia with distinct retinal changes is of clinical interest but has been challenging to investigate because of a lack of sufficiently large and detailed cohorts. Objective To investigate the association between retinal biomarkers from multimodal imaging (oculomics) and schizophrenia in a large real-world population. Design, Setting, and Participants This cross-sectional analysis used data from a retrospective cohort of 154 830 patients 40 years and older from the AlzEye study, which linked ophthalmic data with hospital admission data across England. Patients attended Moorfields Eye Hospital, a secondary care ophthalmic hospital with a principal central site, 4 district hubs, and 5 satellite clinics in and around London, United Kingdom, and had retinal imaging during the study period (January 2008 and April 2018). Data were analyzed from January 2022 to July 2022. Main Outcomes and Measures Retinovascular and optic nerve indices were computed from color fundus photography. Macular retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (mGC-IPL) thicknesses were extracted from optical coherence tomography. Linear mixed-effects models were used to examine the association between schizophrenia and retinal biomarkers. Results A total of 485 individuals (747 eyes) with schizophrenia (mean [SD] age, 64.9 years [12.2]; 258 [53.2%] female) and 100 931 individuals (165 400 eyes) without schizophrenia (mean age, 65.9 years [13.7]; 53 253 [52.8%] female) were included after images underwent quality control and potentially confounding conditions were excluded. Individuals with schizophrenia were more likely to have hypertension (407 [83.9%] vs 49 971 [48.0%]) and diabetes (364 [75.1%] vs 28 762 [27.6%]). The schizophrenia group had thinner mGC-IPL (-4.05 μm, 95% CI, -5.40 to -2.69; P = 5.4 × 10-9), which persisted when investigating only patients without diabetes (-3.99 μm; 95% CI, -6.67 to -1.30; P = .004) or just those 55 years and younger (-2.90 μm; 95% CI, -5.55 to -0.24; P = .03). On adjusted analysis, retinal fractal dimension among vascular variables was reduced in individuals with schizophrenia (-0.14 units; 95% CI, -0.22 to -0.05; P = .001), although this was not present when excluding patients with diabetes. Conclusions and Relevance In this study, patients with schizophrenia had measurable differences in neural and vascular integrity of the retina. Differences in retinal vasculature were mostly secondary to the higher prevalence of diabetes and hypertension in patients with schizophrenia. The role of retinal features as adjunct outcomes in patients with schizophrenia warrants further investigation.
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Affiliation(s)
- Siegfried K. Wagner
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Mario Cortina-Borja
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Steven M. Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, New York
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, New York
- Department of Neuroscience, University of Rochester Medical Center, Rochester, New York
- Center for Visual Science, University of Rochester, Rochester, New York
| | - Yukun Zhou
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - David Romero-Bascones
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Biomedical Engineering Department, Faculty of Engineering (MU-ENG), Mondragon Unibertsitatea, Mondragón, Spain
| | - Robbert R. Struyven
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Emanuele Trucco
- VAMPIRE Project, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Muthu R. K. Mookiah
- VAMPIRE Project, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Tom MacGillivray
- VAMPIRE Project, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen Hogg
- VAMPIRE Project, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Timing Liu
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Dominic J. Williamson
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Nikolas Pontikos
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Praveen J. Patel
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Konstantinos Balaskas
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Daniel C. Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Kelsey V. Stuart
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Anthony P. Khawaja
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Alastair K. Denniston
- University of Birmingham, Birmingham, United Kingdom
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
- NIHR Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, United Kingdom
| | - Jugnoo S. Rahi
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
- Great Ormond Street Hospital NHS Foundation Trust, London, United Kingdom
- Ulverscroft Vision Research Group, University College London, London, United Kingdom
- NIHR Biomedical Research Centre at UCL Great Ormond Street Institute of Child Health and Great Ormond Street Hospital, London, United Kingdom
| | - Axel Petzold
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Pearse A. Keane
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
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16
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Lotan A, Luza S, Opazo CM, Ayton S, Lane DJR, Mancuso S, Pereira A, Sundram S, Weickert CS, Bousman C, Pantelis C, Everall IP, Bush AI. Perturbed iron biology in the prefrontal cortex of people with schizophrenia. Mol Psychiatry 2023; 28:2058-2070. [PMID: 36750734 PMCID: PMC10575779 DOI: 10.1038/s41380-023-01979-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 01/10/2023] [Accepted: 01/20/2023] [Indexed: 02/09/2023]
Abstract
Despite loss of grey matter volume and emergence of distinct cognitive deficits in young adults diagnosed with schizophrenia, current treatments for schizophrenia do not target disruptions in late maturational reshaping of the prefrontal cortex. Iron, the most abundant transition metal in the brain, is essential to brain development and function, but in excess, it can impair major neurotransmission systems and lead to lipid peroxidation, neuroinflammation and accelerated aging. However, analysis of cortical iron biology in schizophrenia has not been reported in modern literature. Using a combination of inductively coupled plasma-mass spectrometry and western blots, we quantified iron and its major-storage protein, ferritin, in post-mortem prefrontal cortex specimens obtained from three independent, well-characterised brain tissue resources. Compared to matched controls (n = 85), among schizophrenia cases (n = 86) we found elevated tissue iron, unlikely to be confounded by demographic and lifestyle variables, by duration, dose and type of antipsychotic medications used or by copper and zinc levels. We further observed a loss of physiologic age-dependent iron accumulation among people with schizophrenia, in that the iron level among cases was already high in young adulthood. Ferritin, which stores iron in a redox-inactive form, was paradoxically decreased in individuals with the disorder. Such iron-ferritin uncoupling could alter free, chemically reactive, tissue iron in key reasoning and planning areas of the young-adult schizophrenia cortex. Using a prediction model based on iron and ferritin, our data provide a pathophysiologic link between perturbed cortical iron biology and schizophrenia and indicate that achievement of optimal cortical iron homeostasis could offer a new therapeutic target.
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Affiliation(s)
- Amit Lotan
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
- Department of Psychiatry and the Biological Psychiatry Laboratory, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Sandra Luza
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton, VIC, Australia
| | - Carlos M Opazo
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, 3010, Australia.
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton, VIC, Australia.
| | - Scott Ayton
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Darius J R Lane
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Serafino Mancuso
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton, VIC, Australia
| | - Avril Pereira
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton, VIC, Australia
| | - Suresh Sundram
- Department of Psychiatry, School of Clinical Sciences, Monash University, Melbourne, VIC, Australia
- Mental Health Program, Monash Health, Melbourne, VIC, Australia
| | - Cynthia Shannon Weickert
- Schizophrenia Research Laboratory, Neuroscience Research Australia, Randwick, NSW, Australia
- School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Chad Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton, VIC, Australia
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Departments of Medical Genetics, Psychiatry, Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
- The Cooperative Research Centre (CRC) for Mental Health, Melbourne, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton, VIC, Australia
- North Western Mental Health, Melbourne, VIC, Australia
| | - Ian P Everall
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton, VIC, Australia
- North Western Mental Health, Melbourne, VIC, Australia
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ashley I Bush
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, 3010, Australia.
- The Cooperative Research Centre (CRC) for Mental Health, Melbourne, VIC, Australia.
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17
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Cai J, Xie M, Zhao L, Li X, Liang S, Deng W, Guo W, Ma X, Sham PC, Wang Q, Li T. White matter changes and its relationship with clinical symptom in medication-naive first-episode early onset schizophrenia. Asian J Psychiatr 2023; 82:103482. [PMID: 36709613 DOI: 10.1016/j.ajp.2023.103482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/17/2023] [Accepted: 01/23/2023] [Indexed: 01/26/2023]
Abstract
Previous studies have highlighted the role of white matter (WM) alterations as biomarkers of the disease state and prognosis of schizophrenia. However, less is known about WM abnormalities in the rarely occurring adolescent early onset schizophrenia (EOS). In this study, T1-weighted and diffusion-weighted images were collected in 56 medication-naive first-episode participants with EOS and 43 healthy controls (HCs). Using Tract-based Spatial Statistics, we calculate case-control differences in scalar diffusion measures, i.e. fractional anisotropy (FA) and mean diffusivity (MD), and investigated their association with clinical feature in participants with EOS. Compared with HCs, decreased MD was found in EOS group most notably in the inferior longitudinal fasciculus, anterior thalamic radiation, inferior fronto-occipital fasciculus and corticospinal tract in the right hemisphere. No significant difference was found in FA between these two groups. The FA values of the forceps minor and the right superior longitudinal fasciculus were suggested to be related to the severity of clinical symptom in participants with EOS. These results provide clues about the neural basis of schizophrenia and a potential biomarker for clinical studies.
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Affiliation(s)
- Jia Cai
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Min Xie
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Liansheng Zhao
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaojing Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Sugai Liang
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wei Deng
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wanjun Guo
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaohong Ma
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Pak C Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
| | - Qiang Wang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
| | - Tao Li
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
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18
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Zhu JD, Wu YF, Tsai SJ, Lin CP, Yang AC. Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and brain-age prediction: a multicenter study. Transl Psychiatry 2023; 13:82. [PMID: 36882419 DOI: 10.1038/s41398-023-02379-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/09/2023] Open
Abstract
Although many studies on brain-age prediction in patients with schizophrenia have been reported recently, none has predicted brain age based on different neuroimaging modalities and different brain regions in these patients. Here, we constructed brain-age prediction models with multimodal MRI and examined the deviations of aging trajectories in different brain regions of participants with schizophrenia recruited from multiple centers. The data of 230 healthy controls (HCs) were used for model training. Next, we investigated the differences in brain age gaps between participants with schizophrenia and HCs from two independent cohorts. A Gaussian process regression algorithm with fivefold cross-validation was used to train 90, 90, and 48 models for gray matter (GM), functional connectivity (FC), and fractional anisotropy (FA) maps in the training dataset, respectively. The brain age gaps in different brain regions for all participants were calculated, and the differences in brain age gaps between the two groups were examined. Our results showed that most GM regions in participants with schizophrenia in both cohorts exhibited accelerated aging, particularly in the frontal lobe, temporal lobe, and insula. The parts of the white matter tracts, including the cerebrum and cerebellum, indicated deviations in aging trajectories in participants with schizophrenia. However, no accelerated brain aging was noted in the FC maps. The accelerated aging in 22 GM regions and 10 white matter tracts in schizophrenia potentially exacerbates with disease progression. In individuals with schizophrenia, different brain regions demonstrate dynamic deviations of brain aging trajectories. Our findings provided more insights into schizophrenia neuropathology.
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19
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Curtis MT, Sklar AL, Coffman BA, Salisbury DF. Functional connectivity and gray matter deficits within the auditory attention circuit in first-episode psychosis. Front Psychiatry 2023; 14:1114703. [PMID: 36860499 PMCID: PMC9968732 DOI: 10.3389/fpsyt.2023.1114703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
Background Selective attention deficits in first episode of psychosis (FEP) can be indexed by impaired attentional modulation of auditory M100. It is unknown if the pathophysiology underlying this deficit is restricted to auditory cortex or involves a distributed attention network. We examined the auditory attention network in FEP. Methods MEG was recorded from 27 FEP and 31 matched healthy controls (HC) while alternately ignoring or attending tones. A whole-brain analysis of MEG source activity during auditory M100 identified non-auditory areas with increased activity. Time-frequency activity and phase-amplitude coupling were examined in auditory cortex to identify the attentional executive carrier frequency. Attention networks were defined by phase-locking at the carrier frequency. Spectral and gray matter deficits in the identified circuits were examined in FEP. Results Attention-related activity was identified in prefrontal and parietal regions, markedly in precuneus. Theta power and phase coupling to gamma amplitude increased with attention in left primary auditory cortex. Two unilateral attention networks were identified with precuneus seeds in HC. Network synchrony was impaired in FEP. Gray matter thickness was reduced within the left hemisphere network in FEP but did not correlate with synchrony. Conclusion Several extra-auditory attention areas with attention-related activity were identified. Theta was the carrier frequency for attentional modulation in auditory cortex. Left and right hemisphere attention networks were identified, with bilateral functional deficits and left hemisphere structural deficits, though FEP showed intact auditory cortex theta phase-gamma amplitude coupling. These novel findings indicate attention-related circuitopathy early in psychosis potentially amenable to future non-invasive interventions.
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Affiliation(s)
| | | | | | - Dean F. Salisbury
- Clinical Neurophysiology Research Laboratory, Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
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20
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Ballester PL, Suh JS, Ho NCW, Liang L, Hassel S, Strother SC, Arnott SR, Minuzzi L, Sassi RB, Lam RW, Milev R, Müller DJ, Taylor VH, Kennedy SH, Reilly JP, Palaniyappan L, Dunlop K, Frey BN. Gray matter volume drives the brain age gap in schizophrenia: a SHAP study. Schizophrenia (Heidelb) 2023; 9:3. [PMID: 36624107 PMCID: PMC9829754 DOI: 10.1038/s41537-022-00330-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023]
Abstract
Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term β = 1.71 [0.53; 3.23]; pcorr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.
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Affiliation(s)
- Pedro L. Ballester
- grid.25073.330000 0004 1936 8227Neuroscience Graduate Program, McMaster University, Hamilton, ON Canada
| | - Jee Su Suh
- grid.25073.330000 0004 1936 8227Neuroscience Graduate Program, McMaster University, Hamilton, ON Canada
| | - Natalie C. W. Ho
- grid.17063.330000 0001 2157 2938Faculty of Arts & Science, University of Toronto, Toronto, ON Canada ,grid.415502.7Keenan Research Centre for Biomedical Science, Unity Health Toronto, Toronto, Canada
| | - Liangbing Liang
- grid.39381.300000 0004 1936 8884Graduate Program in Neuroscience, Western University, London, ON Canada ,grid.39381.300000 0004 1936 8884Robarts Research Institute, Western University, London, ON Canada
| | - Stefanie Hassel
- grid.22072.350000 0004 1936 7697Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB Canada
| | - Stephen C. Strother
- grid.17063.330000 0001 2157 2938Rotman Research Institute, Baycrest, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, ON Canada
| | - Stephen R. Arnott
- grid.17063.330000 0001 2157 2938Rotman Research Institute, Baycrest, Toronto, ON Canada
| | - Luciano Minuzzi
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, Hamilton, ON Canada ,grid.416721.70000 0001 0742 7355Women’s Health Concerns Clinic, St. Joseph’s Healthcare Hamilton, Hamilton, ON Canada
| | - Roberto B. Sassi
- grid.17091.3e0000 0001 2288 9830Department of Psychiatry, University of British Columbia, Vancouver, BC Canada
| | - Raymond W. Lam
- grid.17091.3e0000 0001 2288 9830Department of Psychiatry, University of British Columbia, Vancouver, BC Canada
| | - Roumen Milev
- grid.410356.50000 0004 1936 8331Departments of Psychiatry and Psychology, Queen’s University, and Providence Care, Kingston, ON Canada
| | - Daniel J. Müller
- grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada
| | - Valerie H. Taylor
- grid.22072.350000 0004 1936 7697Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB Canada
| | - Sidney H. Kennedy
- grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Centre for Mental Health, University Health Network, Toronto, ON Canada ,grid.231844.80000 0004 0474 0428Krembil Research Institute, University Health Network, Toronto, ON Canada ,grid.415502.7Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON Canada
| | - James P. Reilly
- grid.25073.330000 0004 1936 8227Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON Canada
| | - Lena Palaniyappan
- grid.39381.300000 0004 1936 8884Robarts Research Institute, Western University, London, ON Canada ,grid.39381.300000 0004 1936 8884Department of Medical Biophysics, Western University, London, ON Canada ,grid.415847.b0000 0001 0556 2414Lawson Health Research Institute, London, ON Canada ,grid.39381.300000 0004 1936 8884Department of Psychiatry, Western University, London, ON Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, Douglas Mental Health University Institute, McGill, Douglas, QC Canada
| | - Katharine Dunlop
- grid.415502.7Keenan Research Centre for Biomedical Science, Unity Health Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Medical Science, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,Centre for Depression & Suicide Studies, Unity Health Toronto, Toronto, ON Canada
| | - Benicio N. Frey
- Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, Hamilton, ON Canada ,grid.416721.70000 0001 0742 7355Women’s Health Concerns Clinic, St. Joseph’s Healthcare Hamilton, Hamilton, ON Canada ,grid.25073.330000 0004 1936 8227Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON Canada
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Shen CL, Tsai SJ, Lin CP, Yang AC. Progressive brain abnormalities in schizophrenia across different illness periods: a structural and functional MRI study. Schizophrenia (Heidelb) 2023; 9:2. [PMID: 36604437 DOI: 10.1038/s41537-022-00328-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 11/16/2022] [Indexed: 01/07/2023]
Abstract
Schizophrenia is a chronic brain disorder, and neuroimaging abnormalities have been reported in different stages of the illness for decades. However, when and how these brain abnormalities occur and evolve remains undetermined. We hypothesized structural and functional brain abnormalities progress throughout the illness course at different rates in schizophrenia. A total of 115 patients with schizophrenia were recruited and stratified into three groups of different illness periods: 5-year group (illness duration: ≤5 years), 15-year group (illness duration: 12-18 years), and 25-year group (illness duration: ≥25 years); 230 healthy controls were matched by age and sex to the three groups, respectively. All participants underwent resting-state MRI scanning. Each group of patients with schizophrenia was compared with the corresponding controls in terms of voxel-based morphometry (VBM), fractional anisotropy (FA), global functional connectivity density (gFCD), and sample entropy (SampEn) abnormalities. In the 5-year group we observed only SampEn abnormalities in the putamen. In the 15-year group, we observed VBM abnormalities in the insula and cingulate gyrus and gFCD abnormalities in the temporal cortex. In the 25-year group, we observed FA abnormalities in nearly all white matter tracts, and additional VBM and gFCD abnormalities in the frontal cortex and cerebellum. By using two structural and two functional MRI analysis methods, we demonstrated that individual functional abnormalities occur in limited brain areas initially, functional connectivity and gray matter density abnormalities ensue later in wider brain areas, and structural connectivity abnormalities involving almost all white matter tracts emerge in the third decade of the course in schizophrenia.
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22
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Zhu JD, Tsai SJ, Lin CP, Lee YJ, Yang AC. Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia. Schizophrenia (Heidelb) 2023; 9:1. [PMID: 36596800 PMCID: PMC9810255 DOI: 10.1038/s41537-022-00325-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 12/20/2022] [Indexed: 01/05/2023]
Abstract
Brain-age prediction is a novel approach to assessing deviated brain aging trajectories in different diseases. However, most studies have used an average brain age gap (BAG) of individuals with schizophrenia of different illness durations for comparison with healthy participants. Therefore, this study investigated whether declined brain structures as reflected by BAGs may be present in schizophrenia in terms of brain volume, cortical thickness, and fractional anisotropy across different illness durations. We used brain volume, cortical thickness, and fractional anisotropy as features to train three models from the training dataset. Three models were applied to predict brain ages in the hold-out test and schizophrenia datasets and calculate BAGs. We divided the schizophrenia dataset into multiple groups based on the illness duration using a sliding time window approach for ANCOVA analysis. The brain volume and cortical thickness models revealed that, in comparison with healthy controls, individuals with schizophrenia had larger BAGs across different illness durations, whereas the BAG in terms of fractional anisotropy did not differ from that of healthy controls after disease onset. Moreover, the BAG at the initial stage of schizophrenia was the largest in the cortical thickness model. In contrast, the BAG from approximately two decades after disease onset was the largest in the brain volume model. Our findings suggest that schizophrenia differentially affects the decline of different brain structures during the disease course. Moreover, different trends of decline in thickness and volume-based measures suggest a differential decline in dimensions of brain structure throughout the course of schizophrenia.
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Affiliation(s)
- Jun-Ding Zhu
- grid.260539.b0000 0001 2059 7017Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- grid.260539.b0000 0001 2059 7017Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan ,grid.278247.c0000 0004 0604 5314Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Ching-Po Lin
- grid.260539.b0000 0001 2059 7017Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yi-Ju Lee
- grid.28665.3f0000 0001 2287 1366Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Albert C. Yang
- grid.260539.b0000 0001 2059 7017Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan ,grid.260539.b0000 0001 2059 7017Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan ,grid.278247.c0000 0004 0604 5314Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
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23
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Howes OD, Cummings C, Chapman GE, Shatalina E. Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes. Neuropsychopharmacology 2023; 48:151-167. [PMID: 36056106 PMCID: PMC9700830 DOI: 10.1038/s41386-022-01426-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 08/03/2022] [Accepted: 08/05/2022] [Indexed: 11/09/2022]
Abstract
Over the last five decades, a large body of evidence has accrued for structural and metabolic brain alterations in schizophrenia. Here we provide an overview of these findings, focusing on measures that have traditionally been thought to reflect synaptic spine density or synaptic activity and that are relevant for understanding if there is lower synaptic density in the disorder. We conducted literature searches to identify meta-analyses or other relevant studies in patients with chronic or first-episode schizophrenia, or in people at high genetic or clinical risk for psychosis. We identified 18 meta-analyses including over 50,000 subjects in total, covering: structural MRI measures of gyrification index, grey matter volume, grey matter density and cortical thickness, neurite orientation dispersion and density imaging, PET imaging of regional glucose metabolism and magnetic resonance spectroscopy measures of N-acetylaspartate. We also review preclinical evidence on the relationship between ex vivo synaptic measures and structural MRI imaging, and PET imaging of synaptic protein 2A (SV2A). These studies show that schizophrenia is associated with lower grey matter volumes and cortical thickness, accelerated grey matter loss over time, abnormal gyrification patterns, and lower regional SV2A levels and metabolic markers in comparison to controls (effect sizes from ~ -0.11 to -1.0). Key regions affected include frontal, anterior cingulate and temporal cortices and the hippocampi. We identify several limitations for the interpretation of these findings in terms of understanding synaptic alterations. Nevertheless, taken with post-mortem findings, they suggest that schizophrenia is associated with lower synaptic density in some brain regions. However, there are several gaps in evidence, in particular whether SV2A findings generalise to other cohorts.
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Affiliation(s)
- Oliver D Howes
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- South London and Maudsley NHS Foundation Trust, London, UK.
| | - Connor Cummings
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- Clare Hall (College), University of Cambridge, Cambridge, UK
| | - George E Chapman
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Ekaterina Shatalina
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
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24
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Dixon TA, Muotri AR. Advancing preclinical models of psychiatric disorders with human brain organoid cultures. Mol Psychiatry 2023; 28:83-95. [PMID: 35948659 PMCID: PMC9812789 DOI: 10.1038/s41380-022-01708-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 07/05/2022] [Accepted: 07/07/2022] [Indexed: 01/11/2023]
Abstract
Psychiatric disorders are often distinguished from neurological disorders in that the former do not have characteristic lesions or findings from cerebrospinal fluid, electroencephalograms (EEGs), or brain imaging, and furthermore do not have commonly recognized convergent mechanisms. Psychiatric disorders commonly involve clinical diagnosis of phenotypic behavioral disturbances of mood and psychosis, often with a poorly understood contribution of environmental factors. As such, psychiatric disease has been challenging to model preclinically for mechanistic understanding and pharmaceutical development. This review compares commonly used animal paradigms of preclinical testing with evolving techniques of induced pluripotent cell culture with a focus on emerging three-dimensional models. Advances in complexity of 3D cultures, recapitulating electrical activity in utero, and disease modeling of psychosis, mood, and environmentally induced disorders are reviewed. Insights from these rapidly expanding technologies are discussed as they pertain to the utility of human organoid and other models in finding novel research directions, validating pharmaceutical action, and recapitulating human disease.
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Affiliation(s)
- Thomas Anthony Dixon
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California San Diego, La Jolla, CA 92093 USA
| | - Alysson R. Muotri
- grid.266100.30000 0001 2107 4242Department of Pediatrics and Department of Cellular & Molecular Medicine, University of California San Diego, School of Medicine, Center for Academic Research and Training in Anthropogeny (CARTA), Kavli Institute for Brain and Mind, Archealization Center (ArchC), La Jolla, CA 92037 USA
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25
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Yuan Z, Liu H, Zhang X, He Y, Gu S, Mo D, Wang S, Huang Z, Wu K, Zhou R, Zhong Q, Huang Y, Cao B, Chen H, Wu X. Role of uric acid as a biomarker of cognitive function in schizophrenia during maintenance period. Front Psychiatry 2023; 14:1123127. [PMID: 37032942 PMCID: PMC10073439 DOI: 10.3389/fpsyt.2023.1123127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 02/27/2023] [Indexed: 04/11/2023] Open
Abstract
Background Previous studies involving uric acid (UA) in some specialized disease populations have found that high UA is associated with enhanced patient function. The mechanism to explain this association may be that UA, an important antioxidant, exerts neuroprotective effects. Patients with schizophrenia (SCZ) have severe oxidative stress abnormalities, and cognitive impairment is a major obstacle to their rehabilitation. Only few studies have been conducted on UA and cognitive impairment in SCZ. This study aims to clarify the relationship between UA and cognitive impairment and explore whether UA could be used as a potential biological marker of cognition in SCZ during maintenance period. Methods A total of 752 cases of SCZ during maintenance period from Baiyun Jingkang Hospital were included. Cognition was measured using the Mini-Mental State Examination scale. UA was measured using the Plus method. The participants were grouped on the basis of UA to evaluate the association of cognition with low-normal (3.50-5.07 mg/dL for men, 2.50-4.19 mg/dL for women), middle-normal (5.07-6.39 mg/dL for men, 4.19-5.18 mg/dL for women), high-normal (6.39-7.00 mg/dL for men, 5.18-6.00 mg/dL for women), and high (>7.00 mg/dL for men, >6.00 mg/dL for women) levels of UA. Multiple logistic regression and linear regression models and restricted cubic spline (RCS) were utilized to evaluate the relationship. Results Uric acid was positively associated with cognitive function. Subgroup analyses showed that high UA was associated with enhanced cognition in participants with low anticholinergic cognitive burden (ACB). Conclusion Uric acid may be used as a simple objective biological indicator to assess cognition in SCZ during maintenance period.
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Affiliation(s)
- Zelin Yuan
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Huamin Liu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Xiaochun Zhang
- Department of Psychiatry, Baiyun Jingkang Hospital, Guangzhou, Guangdong, China
| | - Yong He
- Department of Psychiatry, Baiyun Jingkang Hospital, Guangzhou, Guangdong, China
| | - Shanyuan Gu
- Department of Psychiatry, Baiyun Jingkang Hospital, Guangzhou, Guangdong, China
| | - Dan Mo
- Department of Psychiatry, Baiyun Jingkang Hospital, Guangzhou, Guangdong, China
| | - Shaoli Wang
- Department of Psychiatry, Baiyun Jingkang Hospital, Guangzhou, Guangdong, China
| | - Zhiwei Huang
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Keyi Wu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Rui Zhou
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Qi Zhong
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Yining Huang
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Bifei Cao
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Haowen Chen
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
| | - Xianbo Wu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Diseases), Guangzhou, China
- *Correspondence: Xianbo Wu, ; orcid.org/0000-0002-2706-9599
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26
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Vinogradov S, Chafee MV, Lee E, Morishita H. Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity. Neuropsychopharmacology 2023; 48:168-185. [PMID: 36180784 PMCID: PMC9700720 DOI: 10.1038/s41386-022-01451-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/17/2022] [Accepted: 08/21/2022] [Indexed: 01/05/2023]
Abstract
Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.
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Affiliation(s)
- Sophia Vinogradov
- Department of Psychiatry & Behavioral Science, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Matthew V Chafee
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Erik Lee
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Hirofumi Morishita
- Department of Psychiatry, Neuroscience, & Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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27
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Abram SV, Roach BJ, Hua JPY, Han LKM, Mathalon DH, Ford JM, Fryer SL. Advanced brain age correlates with greater rumination and less mindfulness in schizophrenia. Neuroimage Clin 2023; 37:103301. [PMID: 36586360 PMCID: PMC9830317 DOI: 10.1016/j.nicl.2022.103301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/05/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Individual variation in brain aging trajectories is linked with several physical and mental health outcomes. Greater stress levels, worry, and rumination correspond with advanced brain age, while other individual characteristics, like mindfulness, may be protective of brain health. Multiple lines of evidence point to advanced brain aging in schizophrenia (i.e., neural age estimate > chronological age). Whether psychological dimensions such as mindfulness, rumination, and perceived stress contribute to brain aging in schizophrenia is unknown. METHODS We estimated brain age from high-resolution anatomical scans in 54 healthy controls (HC) and 52 individuals with schizophrenia (SZ) and computed the brain predicted age difference (BrainAGE-diff), i.e., the delta between estimated brain age and chronological age. Emotional well-being summary scores were empirically derived to reflect individual differences in trait mindfulness, rumination, and perceived stress. Core analyses evaluated relationships between BrainAGE-diff and emotional well-being, testing for slopes differences across groups. RESULTS HC showed higher emotional well-being (greater mindfulness and less rumination/stress), relative to SZ. We observed a significant group difference in the relationship between BrainAge-diff and emotional well-being, explained by BrainAGE-diff negatively correlating with emotional well-being scores in SZ, and not in HC. That is, SZ with younger appearing brains (predicted age < chronological age) had emotional summary scores that were more like HC, a relationship that endured after accounting for several demographic and clinical variables. CONCLUSIONS These data reveal clinically relevant aspects of brain age heterogeneity among SZ and point to case-control differences in the relationship between advanced brain aging and emotional well-being.
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Affiliation(s)
- Samantha V Abram
- Sierra Pacific Mental Illness Research Education and Clinical Centers, San Francisco Veterans Affairs Medical Center, and the University of California, San Francisco, CA, United States; Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA, United States; Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Brian J Roach
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA, United States
| | - Jessica P Y Hua
- Sierra Pacific Mental Illness Research Education and Clinical Centers, San Francisco Veterans Affairs Medical Center, and the University of California, San Francisco, CA, United States; Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA, United States; Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Laura K M Han
- Orygen, Parkville, VIC, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Daniel H Mathalon
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA, United States; Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Judith M Ford
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA, United States; Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Susanna L Fryer
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA, United States; Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
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28
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Khan MM. Role of de novo lipogenesis in insulin resistance in first-episode psychosis and therapeutic options. Neurosci Biobehav Rev 2022; 143:104919. [DOI: 10.1016/j.neubiorev.2022.104919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 10/07/2022] [Accepted: 10/15/2022] [Indexed: 11/06/2022]
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29
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Jia X, Wang J, Jiang W, Kong Z, Deng H, Lai W, Ye C, Guan F, Li P, Zhao M, Yang M. Common gray matter loss in the frontal cortex in patients with methamphetamine-associated psychosis and schizophrenia. Neuroimage Clin 2022; 36:103259. [PMID: 36510408 PMCID: PMC9668661 DOI: 10.1016/j.nicl.2022.103259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 10/08/2022] [Accepted: 11/02/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND AND HYPOTHESIS Methamphetamine (MA)-associated psychosis has become a public concern. However, its mechanism is not clear. Investigating similarities and differences between MA-associated psychosis and schizophrenia in brain alterations would be informative for neuropathology. STUDY DESIGN This study compared gray matter volumes of the brain across four participant groups: healthy controls (HC, n = 53), MA users without psychosis (MA, n = 22), patients with MA-associated psychosis (MAP, n = 34) and patients with schizophrenia (SCZ, n = 33). Clinical predictors of brain alterations, as well as association of brain alterations with psychotic symptoms and attention impairment were further investigated. STUDY RESULTS Compared with the HC, the MAP and the SCZ showed similar gray matter reductions in the frontal cortex, particularly in prefrontal areas. Moreover, a stepwise extension of gray matter reductions was exhibited across the MA - MAP - SCZ. Duration of abstinence was associated with regional volumetric recovery in the MAP, while this amendment in brain morphometry was not accompanied with symptom's remission. Illness duration of psychosis was among the predictive factors of regional gray matter reductions in both psychotic groups. Volume reductions were found to be associated with attention impairment in the SCZ, while this association was reversed in the MAP in frontal cortex. CONCLUSIONS This study suggested MA-associated psychosis and schizophrenia had common neuropathology in cognitive-related frontal cortices. A continuum of neuropathology between MA use and schizophrenia was tentatively implicated. Illness progressions and glial repairments could both play roles in neuropathological changes in MA-associated psychosis.
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Affiliation(s)
- Xiaojian Jia
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China
| | - Jianhong Wang
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China
| | - Wentao Jiang
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China
| | - Zhi Kong
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China
| | - Huan Deng
- School of International Education, Beijing University of Chemical Technology, Beijing 100029, China
| | - Wentao Lai
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China
| | - Caihong Ye
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China
| | - Fen Guan
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China
| | - Peng Li
- Peking University Sixth Hospital, Peking University, Beijing 100191, China
| | - Min Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Mei Yang
- Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Clinical Research Center for Mental Disorders, Shenzhen 518020, China.
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30
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Eratne D, Janelidze S, Malpas CB, Loi S, Walterfang M, Merritt A, Diouf I, Blennow K, Zetterberg H, Cilia B, Wannan C, Bousman C, Everall I, Zalesky A, Jayaram M, Thomas N, Berkovic SF, Hansson O, Velakoulis D, Pantelis C, Santillo A, Stehmann C, Cadwallader C, Fowler C, Ravanfar P, Farrand S, Keem M, Kang M, Watson R, Yassi N, Kaylor-Hughes C, Kanaan R, Perucca P, Vivash L, Ali R, O’Brien TJ, Masters CL, Collins S, Kelso W, Evans A, King A, Kwan P, Gunn J, Goranitis I, Pan T, Lewis C, Kalincik T. Plasma neurofilament light chain protein is not increased in treatment-resistant schizophrenia and first-degree relatives. Aust N Z J Psychiatry 2022; 56:1295-1305. [PMID: 35179048 DOI: 10.1177/00048674211058684] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVE Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The processes underlying these abnormalities, and whether a subset of people with schizophrenia have a neuroprogressive or neurodegenerative component to schizophrenia, remain largely unknown. Examining fluid biomarkers of diverse types of neuronal damage could increase our understanding of these processes, as well as potentially provide clinically useful biomarkers, for example with assisting with differentiation from progressive neurodegenerative disorders such as Alzheimer and frontotemporal dementias. METHODS This study measured plasma neurofilament light chain protein (NfL) using ultrasensitive Simoa technology, to investigate the degree of neuronal injury in a well-characterised cohort of people with treatment-resistant schizophrenia on clozapine (n = 82), compared to first-degree relatives (an at-risk group, n = 37), people with schizophrenia not treated with clozapine (n = 13), and age- and sex-matched controls (n = 59). RESULTS We found no differences in NfL levels between treatment-resistant schizophrenia (mean NfL, M = 6.3 pg/mL, 95% confidence interval: [5.5, 7.2]), first-degree relatives (siblings, M = 6.7 pg/mL, 95% confidence interval: [5.2, 8.2]; parents, M after adjusting for age = 6.7 pg/mL, 95% confidence interval: [4.7, 8.8]), controls (M = 5.8 pg/mL, 95% confidence interval: [5.3, 6.3]) and not treated with clozapine (M = 4.9 pg/mL, 95% confidence interval: [4.0, 5.8]). Exploratory, hypothesis-generating analyses found weak correlations in treatment-resistant schizophrenia, between NfL and clozapine levels (Spearman's r = 0.258, 95% confidence interval: [0.034, 0.457]), dyslipidaemia (r = 0.280, 95% confidence interval: [0.064, 0.470]) and a negative correlation with weight (r = -0.305, 95% confidence interval: [-0.504, -0.076]). CONCLUSION Treatment-resistant schizophrenia does not appear to be associated with neuronal, particularly axonal degeneration. Further studies are warranted to investigate the utility of NfL to differentiate treatment-resistant schizophrenia from neurodegenerative disorders such as behavioural variant frontotemporal dementia, and to explore NfL in other stages of schizophrenia such as the prodome and first episode.
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Affiliation(s)
- Dhamidhu Eratne
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Charles B Malpas
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia.,Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Samantha Loi
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mark Walterfang
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Antonia Merritt
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Ibrahima Diouf
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute, University College London (UCL), London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Brandon Cilia
- The University of Melbourne, Parkville, VIC, Australia
| | - Cassandra Wannan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Chad Bousman
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Ian Everall
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mahesh Jayaram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Naveen Thomas
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Dennis Velakoulis
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Alexander Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
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31
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Howes OD, Shatalina E. Integrating the Neurodevelopmental and Dopamine Hypotheses of Schizophrenia and the Role of Cortical Excitation-Inhibition Balance. Biol Psychiatry 2022; 92:501-513. [PMID: 36008036 DOI: 10.1016/j.biopsych.2022.06.017] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 05/16/2022] [Accepted: 06/04/2022] [Indexed: 12/23/2022]
Abstract
The neurodevelopmental and dopamine hypotheses are leading theories of the pathoetiology of schizophrenia, but they were developed in isolation. However, since they were originally proposed, there have been considerable advances in our understanding of the normal neurodevelopmental refinement of synapses and cortical excitation-inhibition (E/I) balance, as well as preclinical findings on the interrelationship between cortical and subcortical systems and new in vivo imaging and induced pluripotent stem cell evidence for lower synaptic density markers in patients with schizophrenia. Genetic advances show that schizophrenia is associated with variants linked to genes affecting GABA (gamma-aminobutyric acid) and glutamatergic signaling as well as neurodevelopmental processes. Moreover, in vivo studies on the effects of stress, particularly during later development, show that it leads to synaptic elimination. We review these lines of evidence as well as in vivo evidence for altered cortical E/I balance and dopaminergic dysfunction in schizophrenia. We discuss mechanisms through which frontal cortex circuitry may regulate striatal dopamine and consider how frontal E/I imbalance may cause dopaminergic dysregulation to result in psychotic symptoms. This integrated neurodevelopmental and dopamine hypothesis suggests that overpruning of synapses, potentially including glutamatergic inputs onto frontal cortical interneurons, disrupts the E/I balance and thus underlies cognitive and negative symptoms. It could also lead to disinhibition of excitatory projections from the frontal cortex and possibly other regions that regulate mesostriatal dopamine neurons, resulting in dopamine dysregulation and psychotic symptoms. Together, this explains a number of aspects of the epidemiology and clinical presentation of schizophrenia and identifies new targets for treatment and prevention.
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Affiliation(s)
- Oliver D Howes
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, United Kingdom; Department of Psychosis, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
| | - Ekaterina Shatalina
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, United Kingdom
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32
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Seitz-Holland J, Wojcik JD, Cetin-Karayumak S, Lyall AE, Pasternak O, Rathi Y, Vangel M, Pearlson G, Tamminga C, Sweeney JA, Clementz BA, Schretlen DA, Viher PV, Stegmayer K, Walther S, Lee J, Crow T, James A, Voineskos A, Buchanan RW, Szeszko PR, Malhotra AK, Kelly S, Shenton ME, Keshavan MS, Mesholam-Gately RI, Kubicki M. Cognitive deficits, clinical variables, and white matter microstructure in schizophrenia: a multisite harmonization study. Mol Psychiatry 2022; 27:3719-3730. [PMID: 35982257 PMCID: PMC10538303 DOI: 10.1038/s41380-022-01731-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 07/18/2022] [Accepted: 07/29/2022] [Indexed: 02/08/2023]
Abstract
Cognitive deficits are among the best predictors of real-world functioning in schizophrenia. However, our understanding of how cognitive deficits relate to neuropathology and clinical presentation over the disease lifespan is limited. Here, we combine multi-site, harmonized cognitive, imaging, demographic, and clinical data from over 900 individuals to characterize a) cognitive deficits across the schizophrenia lifespan and b) the association between cognitive deficits, clinical presentation, and white matter (WM) microstructure. Multimodal harmonization was accomplished using T-scores for cognitive data, previously reported standardization methods for demographic and clinical data, and an established harmonization method for imaging data. We applied t-tests and correlation analysis to describe cognitive deficits in individuals with schizophrenia. We then calculated whole-brain WM fractional anisotropy (FA) and utilized regression-mediation analyses to model the association between diagnosis, FA, and cognitive deficits. We observed pronounced cognitive deficits in individuals with schizophrenia (p < 0.006), associated with more positive symptoms and medication dosage. Regression-mediation analyses showed that WM microstructure mediated the association between schizophrenia and language/processing speed/working memory/non-verbal memory. In addition, processing speed mediated the influence of diagnosis and WM microstructure on the other cognitive domains. Our study highlights the critical role of cognitive deficits in schizophrenia. We further show that WM is crucial when trying to understand the role of cognitive deficits, given that it explains the association between schizophrenia and cognitive deficits (directly and via processing speed).
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Joanne D Wojcik
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Harvard Medical School, Boston, MA, USA
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Vangel
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Carol Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett A Clementz
- Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA
| | - David A Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Petra Verena Viher
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Katharina Stegmayer
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Jungsun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Tim Crow
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Anthony James
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Aristotle Voineskos
- Center for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Philip R Szeszko
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center, Bronx, New York, NY, USA
| | - Anil K Malhotra
- The Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Sinead Kelly
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Harvard Medical School, Boston, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Harvard Medical School, Boston, MA, USA
| | - Raquelle I Mesholam-Gately
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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33
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Wannan CMJ, Bartholomeusz CF, Pantelis C, Di Biase MA, Syeda WT, Chakravarty MM, Bousman CA, Everall IP, McGorry PD, Zalesky A, Cropley VL. Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness. Eur Arch Psychiatry Clin Neurosci 2022; 272:971-83. [PMID: 34557990 DOI: 10.1007/s00406-021-01333-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 09/09/2021] [Indexed: 12/13/2022]
Abstract
Episodic memory ability relies on hippocampal-prefrontal connectivity. However, few studies have examined relationships between memory performance and white matter (WM) microstructure in hippocampal-prefrontal pathways in schizophrenia-spectrum disorder (SSDs). Here, we investigated these relationships in individuals with first-episode psychosis (FEP) and chronic schizophrenia-spectrum disorders (SSDs) using tractography analysis designed to interrogate the microstructure of WM tracts in the hippocampal-prefrontal pathway. Measures of WM microstructure (fractional anisotropy [FA], radial diffusivity [RD], and axial diffusivity [AD]) were obtained for 47 individuals with chronic SSDs, 28 FEP individuals, 52 older healthy controls, and 27 younger healthy controls. Tractography analysis was performed between the hippocampus and three targets involved in hippocampal-prefrontal connectivity (thalamus, amygdala, nucleus accumbens). Measures of WM microstructure were then examined in relation to episodic memory performance separately across each group. Both those with FEP and chronic SSDs demonstrated impaired episodic memory performance. However, abnormal WM microstructure was only observed in individuals with chronic SSDs. Abnormal WM microstructure in the hippocampal-thalamic pathway in the right hemisphere was associated with poorer memory performance in individuals with chronic SSDs. These findings suggest that disruptions in WM microstructure in the hippocampal-prefrontal pathway may contribute to memory impairments in individuals with chronic SSDs but not FEP.
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34
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Yue W, Huang H, Duan J. Potential diagnostic biomarkers for schizophrenia. Med Rev (Berl) 2022; 2:385-416. [PMID: 37724326 PMCID: PMC10388817 DOI: 10.1515/mr-2022-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/20/2022] [Indexed: 09/20/2023]
Abstract
Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.
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Affiliation(s)
- Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University) and Chinese Academy of Medical Sciences Research Unit, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University Health System, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
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35
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Zhao Y, Zhang Q, Shah C, Li Q, Sweeney JA, Li F, Gong Q. Cortical Thickness Abnormalities at Different Stages of the Illness Course in Schizophrenia: A Systematic Review and Meta-analysis. JAMA Psychiatry 2022; 79:560-570. [PMID: 35476125 PMCID: PMC9047772 DOI: 10.1001/jamapsychiatry.2022.0799] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
IMPORTANCE Questions of whether and how cortical thickness (CTh) alterations differ over the course of schizophrenia (SCZ) have yet to be resolved. OBJECTIVE To characterize CTh alterations across illness stages in SCZ. DATA SOURCES PubMed, Embase, Web of Science, and Science Direct were screened for CTh studies published before June 15, 2021. STUDY SELECTION Original studies comparing whole-brain CTh alterations from healthy controls in individuals at clinical high-risk (CHR), first episode of psychosis (FEP), and long-term illness stages of SCZ were included. DATA EXTRACTION AND SYNTHESIS This preregistered systematic review and meta-analysis followed PRISMA reporting guidelines. Separate and pooled meta-analyses were performed using seed-based d mapping. Meta-regression analyses were conducted. MAIN OUTCOMES AND MEASURES Cortical thickness differences from healthy control individuals across illness stages. RESULTS Ten studies comprising 859 individuals with CHR (mean [SD] age, 21.02 [2.66] years; male, 573 [66.7%]), 12 studies including 671 individuals with FEP (mean [SD] age, 22.87 [3.99] years; male, 439 [65.4%]), and 10 studies comprising 579 individuals with long-term SCZ (mean [SD] age, 41.58 [6.95] years; male, 396 [68.4%]) were included. Compared with healthy control individuals, individuals with CHR showed cortical thinning in bilateral medial prefrontal cortex (z = -1.01; P < .001). Individuals with FEP showed cortical thinning in right lateral superior temporal cortex (z = -1.34; P < .001), right anterior cingulate cortex (z = -1.44; P < .001), and right insula (z = -1.14; P = .002). Individuals with long-term SCZ demonstrated CTh reductions in right insula (z = -3.25; P < .001), right inferior frontal cortex (z = -2.19; P < .001), and left (z = -2.37; P < .001) and right (z = -1.94; P = .002) temporal pole. There were no significant CTh differences between CHR and FEP. Individuals with long-term SCZ showed greater cortical thinning in right insula (z = -2.58; P < .001), right inferior frontal cortex (z = -2.32; P < .001), left lateral temporal cortex (z = -1.91; P = .002), and right temporal pole (z = -1.82; P = .002) than individuals with FEP. Combining all studies on SCZ, accelerated age-related CTh reductions were found in bilateral lateral middle temporal cortex and right pars orbitalis in inferior frontal cortex. CONCLUSIONS AND RELEVANCE The absence of significant differences between FEP and CHR noted in this systematic review and meta-analysis suggests that the onset of psychosis was not associated with robust CTh reduction. The greater cortical thinning in long-term SCZ compared with FEP with accelerated age-related reduction in CTh suggests progressive neuroanatomic alterations following illness onset. Caution in interpretation is needed because heterogeneity in samples and antipsychotic treatment may confound these results.
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Affiliation(s)
- Youjin Zhao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qian Zhang
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Chandan Shah
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Qian Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - John A. Sweeney
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio
| | - Fei Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China,Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
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36
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Kwateng KO, Tetteh FK, Asare N, Manu D. Can intercluster coordination mediate the relationship between supply chain flexibility and humanitarian supply chain performance? JHLSCM 2022. [DOI: 10.1108/jhlscm-09-2021-0086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeThe occurrence of disaster and crisis is increasing. They are complex as well as challenging for humanitarian organizations (HOs) and societies involved in disaster relief operations. This study examined the nexus between supply chain flexibility (SCF) and humanitarian supply chain performance (HSCP) among HOs with empirical evidence from HOs in Ghana.Design/methodology/approachThe study employed the quantitative method to explore the interdependencies among the variables. In congruence with this, the study employed the purposive and convenience sampling technique to obtain information from 168 respondents. The analysis was done using SPSS version 23 and Smart PLS version 3.FindingsThe outcome indicates that intercluster coordination (ICC) plays a significant mediating role between SCF and HSCP.Practical implicationsThe outcome of the study indicates that a closer and stronger relationship ensures proper channel use among the HOs. This will improve the performance of the supply chain of HOs and their ability to deal with supply chain uncertainties.Originality/valueThe discovery of this study provides empirical support to the resource-based view theory. Thus, practitioners in the humanitarian setting give priority to factors that could enhance flexibility in their supply chain as well as implement coordination strategies to achieve a responsive humanitarian supply chain (HSC) system in the quest to minimize the outcome of disasters.
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37
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Chen CR, Hung CF, Lee YW, Tseng WT, Chen ML, Chen TT. Functional Outcomes in a Randomized Controlled Trial of Animal-Assisted Therapy on Middle-Aged and Older Adults with Schizophrenia. IJERPH 2022; 19:ijerph19106270. [PMID: 35627807 PMCID: PMC9141906 DOI: 10.3390/ijerph19106270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/17/2022] [Accepted: 05/18/2022] [Indexed: 12/10/2022]
Abstract
Deficits in cognition, physical, and social functions in adults with schizophrenia may become salient with aging. While animal-assisted therapy (AAT) can benefit physical function in older adults and improve symptoms of psychotic disorders, the effect of AAT on middle-aged patients with schizophrenia is unclear. The current randomized controlled trial aimed to explore the efficacy of AAT for middle-aged patients with schizophrenia. Forty participants were randomly assigned to either the AAT or control group. The AAT group participated in one-hour sessions with dog-assisted group activities once a week for 12 weeks. The controls participated in dose-matched, non-animal-related recreational activities. Both groups remained on their usual psychotropic medication during the trial. Evaluations included the Chair Stand Test (CST), Timed Up-and-Go (TUG) test, Montreal Cognitive Assessment (MoCA), 5-Meter walk test (5MWT), and Assessment of Communication and Interaction Skills (ACIS). The increases in CST repetitions and ACIS scores were larger in the AAT group than in the controls. The two groups did not differ significantly in MoCA scores, TUG performance, or the 5MWT. The AAT group showed a greater increase in lower extremity strength and social skills, but no improvement in cognitive function, agility, or mobility. Further research with more sensitive evaluations and longer follow-up is needed.
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Affiliation(s)
- Chyi-Rong Chen
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833401, Taiwan; (C.-R.C.); (C.-F.H.); (W.-T.T.)
- School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei 100025, Taiwan
- Department of Occupational Therapy, Shu-Zen Junior College of Medicine and Management, Kaohsiung 821004, Taiwan
| | - Chi-Fa Hung
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833401, Taiwan; (C.-R.C.); (C.-F.H.); (W.-T.T.)
- Department of Post-Baccalaureate Medicine, National Sun Yat-Sen University, Kaohsiung 804201, Taiwan
- College of Humanities and Social Sciences, National Pintung University of Science and Technology, Pingtung 912301, Taiwan
| | - Yi-Wen Lee
- Department of Nursing, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833401, Taiwan;
| | - Wei-Ting Tseng
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833401, Taiwan; (C.-R.C.); (C.-F.H.); (W.-T.T.)
| | - Mei-Li Chen
- School of Nursing, National Taipei University of Nursing and Health Sciences, Taipei 112303, Taiwan;
- Professional Animal-Assisted Therapy Association of Taiwan, Taipei 112303, Taiwan
| | - Tzu-Ting Chen
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833401, Taiwan; (C.-R.C.); (C.-F.H.); (W.-T.T.)
- School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei 100025, Taiwan
- Professional Animal-Assisted Therapy Association of Taiwan, Taipei 112303, Taiwan
- Correspondence: or
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38
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Alkan E, Evans SL. Clustering of cognitive subtypes in schizophrenia patients and their siblings: relationship with regional brain volumes. Schizophr 2022; 8:50. [PMID: 35853888 PMCID: PMC9261107 DOI: 10.1038/s41537-022-00242-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 02/23/2022] [Indexed: 11/09/2022]
Abstract
AbstractSchizophrenia patients (SZH) often show impaired cognition and reduced brain structural volumes; these deficits are also detectable in healthy relatives of SZH. However, there is considerable heterogeneity: a sizable percentage of SZH are relatively cognitively intact; clustering strategies have proved useful for categorising into cognitive subgroups. We used a clustering strategy to investigate relationships between subgroup assignment and brain volumes, in 102 SZH (N = 102) and 32 siblings of SZH (SZH-SIB), alongside 92 controls (CON) and 48 of their siblings. SZH had poorer performance in all cognitive domains, and smaller brain volumes within prefrontal and temporal regions compared to controls. We identified three distinct cognitive clusters (‘neuropsychologically normal’, ‘intermediate’, ‘cognitively impaired’) based on age- and gender-adjusted cognitive domain scores. The majority of SZH (60.8%) were assigned to the cognitively impaired cluster, while the majority of SZH-SIB (65.6%) were placed in the intermediate cluster. Greater right middle temporal volume distinguished the normal cluster from the more impaired clusters. Importantly, the observed brain volume differences between SZH and controls disappeared after adjustment for cluster assignment. This suggests an intimate link between cognitive performance levels and regional brain volume differences in SZH. This highlights the importance of accounting for heterogeneity in cognitive performance within SZH populations when attempting to characterise the brain structural abnormalities associated with the disease.
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39
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Stone WS, Phillips MR, Yang LH, Kegeles LS, Susser ES, Lieberman JA. Neurodegenerative model of schizophrenia: Growing evidence to support a revisit. Schizophr Res 2022; 243:154-162. [PMID: 35344853 PMCID: PMC9189010 DOI: 10.1016/j.schres.2022.03.004] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/07/2022] [Accepted: 03/11/2022] [Indexed: 12/21/2022]
Abstract
Multidimensional progressive declines in the absence of standard biomarkers for neurodegeneration are observed commonly in the development of schizophrenia, and are accepted as consistent with neurodevelopmental etiological hypotheses to explain the origins of the disorder. Far less accepted is the possibility that neurodegenerative processes are involved as well, or even that key dimensions of function, such as cognition and aspects of biological integrity, such as white matter function, decline in chronic schizophrenia beyond levels associated with normal aging. We propose that recent research germane to these issues warrants a current look at the question of neurodegeneration. We propose the view that a neurodegenerative hypothesis provides a better explanation of some features of chronic schizophrenia, including accelerated aging, than is provided by neurodevelopmental hypotheses. Moreover, we suggest that neurodevelopmental influences in early life, including those that may extend to later life, do not preclude the development of neurodegenerative processes in later life, including some declines in cognitive and biological integrity. We evaluate these views by integrating recent findings in representative domains such as cognition and white and gray matter integrity with results from studies on accelerated aging, together with functional implications of neurodegeneration for our understanding of chronic schizophrenia.
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Affiliation(s)
- William S. Stone
- Harvard Medical School Department of Psychiatry at Beth Israel Deaconess Medical Center, Boston, Massachusetts,Corresponding Author: William S. Stone, Ph.D., Massachusetts Mental Health Center, 75 Fenwood Road, Boston, Massachusetts, USA,
| | - Michael R. Phillips
- Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, Shanghai, China,Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Lawrence H. Yang
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York,New York University College of Global Public Health, New York, New York
| | - Lawrence S. Kegeles
- Department of Psychiatry, Columbia University, New York, New York,New York State Psychiatric Institute, New York, New York
| | - Ezra S. Susser
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
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40
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Rodríguez-Sánchez JM, Setién-Suero E, Suárez-Pinilla P, Mayoral Van Son J, Vázquez-Bourgon J, Gil López P, Crespo-Facorro B, Ayesa-Arriola R. Ten-year course of cognition in first-episode non-affective psychosis patients: PAFIP cohort. Psychol Med 2022; 52:770-779. [PMID: 32686636 DOI: 10.1017/s0033291720002408] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
BACKGROUND A large body of research states that cognitive impairment in schizophrenia is static. Nevertheless, most previous studies lack a control group or have small study samples or short follow-up periods. METHOD We aimed to address these limitations by studying a large epidemiological cohort of patients with first-episode schizophrenia spectrum disorders and a comparable control sample for a 10-year period. RESULTS Our results support the generalized stability of cognitive functions in schizophrenia spectrum disorders considering the entire group. However, the existence of a subgroup of patients characterized by deteriorating cognition and worse long-term clinical outcomes must be noted. Nevertheless, it was not possible to identify concomitant factors or predictors of deterioration (all Ps > 0.05). CONCLUSIONS Cognitive functions in schizophrenia spectrum disorder are stable; however, a subgroup of subjects that deteriorate can be characterized.
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Affiliation(s)
- José Manuel Rodríguez-Sánchez
- Red de Salud Mental de Bizkaia. Biocruces Bizkaia Health Research Institute, Plaza de Cruces 12 48903, Barakaldo, Bizkaia, España
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Spain
| | - Esther Setién-Suero
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL. School of Medicine, University of Cantabria, Santander, Spain
| | - Paula Suárez-Pinilla
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL. School of Medicine, University of Cantabria, Santander, Spain
| | | | - Javier Vázquez-Bourgon
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL. School of Medicine, University of Cantabria, Santander, Spain
| | - Patxi Gil López
- Red de Salud Mental de Bizkaia. Biocruces Bizkaia Health Research Institute, Plaza de Cruces 12 48903, Barakaldo, Bizkaia, España
| | - Benedicto Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Spain
- Hospital universitario Virgen del Roció, IBiS, Universidad de Sevilla, Spain
| | - Rosa Ayesa-Arriola
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL. School of Medicine, University of Cantabria, Santander, Spain
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Rahman T, Purves-Tyson T, Geddes AE, Huang XF, Newell KA, Weickert CS. N-Methyl-d-Aspartate receptor and inflammation in dorsolateral prefrontal cortex in schizophrenia. Schizophr Res 2022; 240:61-70. [PMID: 34952289 DOI: 10.1016/j.schres.2021.11.045] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 11/02/2021] [Accepted: 11/27/2021] [Indexed: 10/19/2022]
Abstract
Lower N-methyl-d-aspartate receptor (NMDAR) GluN1 subunit levels and heightened neuroinflammation are found in the cortex in schizophrenia. Since neuroinflammation can lead to changes in NMDAR function, it is possible that these observations are linked in schizophrenia. We aimed to extend our previous studies by measuring molecular indices of NMDARs that define key functional properties of this receptor - particularly the ratio of GluN2A and GluN2B subunits - in dorsolateral prefrontal cortex (DLPFC) from schizophrenia and control cases (37/37). We sought to test whether changes in these measures are specific to the subset of schizophrenia cases with high levels of inflammation-related mRNAs, defined as a high inflammatory subgroup. Quantitative autoradiography was used to detect 'functional' NMDARs ([3H]MK-801), GluN1-coupled-GluN2A subunits ([3H]CGP-39653), and GluN1-coupled-GluN2B subunits ([3H]Ifenprodil). Quantitative RT-PCR was used to measure NMDAR subunit transcripts (GRIN1, GRIN2A and GRIN2B). The ratios of GluN2A:GluN2B binding and GRIN2A:GRIN2B mRNAs were calculated as an index of putative NMDAR composition. We found: 1) GluN2A binding, and 2) the ratios of GluN2A:GluN2B binding and GRIN2A:GRIN2B mRNAs were lower in schizophrenia cases versus controls (p < 0.05), and 3) lower GluN2A:GluN2B binding and GRIN2A:GRIN2B mRNA ratios were exaggerated in the high inflammation/schizophrenia subgroup compared to the low inflammation/control subgroup (p < 0.05). No other NMDAR-related indices were significantly changed in the high inflammation/schizophrenia subgroup. This suggests that neuroinflammation may alter NMDAR stoichiometry rather than targeting total NMDAR levels overall, and future studies could aim to determine if anti-inflammatory treatment can alleviate this aspect of NMDAR-related pathology.
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Affiliation(s)
- Tasnim Rahman
- Neuroscience Research Australia (NeuRA), Sydney, NSW, Australia; School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Tertia Purves-Tyson
- Neuroscience Research Australia (NeuRA), Sydney, NSW, Australia; School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Amy E Geddes
- School of Medicine and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia; Illawarra Health and Medical Research Institute, Wollongong, Australia
| | - Xu-Feng Huang
- School of Medicine and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia; Illawarra Health and Medical Research Institute, Wollongong, Australia
| | - Kelly A Newell
- School of Medicine and Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia; Illawarra Health and Medical Research Institute, Wollongong, Australia.
| | - Cynthia Shannon Weickert
- Neuroscience Research Australia (NeuRA), Sydney, NSW, Australia; School of Psychiatry, University of New South Wales, Sydney, NSW, Australia; Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, NY, USA.
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Tang B, Zhang W, Deng S, Liu J, Hu N, Gong Q, Gu S, Lui S. Age-associated network controllability changes in first episode drug-naïve schizophrenia. BMC Psychiatry 2022; 22:26. [PMID: 35012507 DOI: 10.1186/s12888-021-03674-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 12/22/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain's structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. METHODS Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. RESULTS Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. CONCLUSIONS By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.
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43
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Sun Y, Zhang Z, Kakkos I, Matsopoulos GK, Yuan J, Suckling J, Xu L, Cao S, Chen W, Hu X, Li T, Sim K, Qi P, Sun Y. Inferring the Individual Psychopathologic Deficits with Structural Connectivity in a Longitudinal Cohort of Schizophrenia. IEEE J Biomed Health Inform 2022; 26:2536-2546. [PMID: 34982705 DOI: 10.1109/jbhi.2021.3139701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The prediction of schizophrenia-related psychopathologic deficits is exceedingly important in the fields of psychiatry and clinical practice. However, objective association of the brain structure alterations to the illness clinical symptoms is challenging. Although, schizophrenia has been characterized as a brain dysconnectivity syndrome, evidence accounting for neuroanatomical network alterations remain scarce. Moreover, the absence of generalized connectome biomarkers for the assessment of illness progression further perplexes the prediction of long-term symptom severity. In this paper, a combination of individualized prediction models with quantitative graph theoretical analysis was adopted, providing a comprehensive appreciation of the extent to which the brain network properties are affected over time in schizophrenia. Specifically, Connectome-based Prediction Models were employed on Structural Connectivity (SC) features, efficiently capturing individual network-related differences, while identifying the anatomical connectivity disturbances contributing to the prediction of psychopathological deficits. Our results demonstrated distinctions among widespread cortical circuits responsible for different domains of symptoms, indicating the complex neural mechanisms underlying schizophrenia. Furthermore, the generated models were able to significantly predict changes of symptoms using SC features at follow-up, while the preserved SC features suggested an association with improved positive and overall symptoms. Moreover, cross-sectional significant deficits were observed in network efficiency and a progressive aberration of global integration in patients compared to healthy controls, representing a group-consensus pathological map, while supporting the dysconnectivity hypothesis.
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Chen CR, Huang YC, Lee YW, Hsieh HH, Lee YC, Lin KC. The effects of Baduanjin exercise vs. brisk walking on physical fitness and cognition in middle-aged patients with schizophrenia: A randomized controlled trial. Front Psychiatry 2022; 13:983994. [PMID: 36276319 PMCID: PMC9579429 DOI: 10.3389/fpsyt.2022.983994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE Patients with schizophrenia have deficits in physical and cognitive function that may become salient in their middle ages. These deficits need active intervention to prevent functional decline. Baduanjin and brisk walking show promise as interventions in patients with schizophrenia. This study investigated the effects of Baduanjin exercise vs. brisk walking in middle-aged patients with schizophrenia. METHODS In this single-blind, 2-arm, parallel, randomized controlled trial, 48 participants aged older than 40 years were enrolled and assigned to the intervention group (Baduanjin) or the control group (brisk walking). The training of both groups took place twice a week, 60 min per session, for 12 weeks. The participants were evaluated with physical, cognitive, and functional outcomes at baseline, postintervention, and 4 weeks after the intervention. RESULTS The results of the study demonstrated significant time effects in walking distance (p = 0.035, η2 = 0.094) and lower extremity strength (p = 0.006, η2 = 0.152). Post-hoc analysis revealed both groups had significant improvement in changes from baseline to the postintervention assessment (ps < 0.05) and follow-up (ps < 0.05). The results demonstrated a significant group-by-time interaction in change scores of global cognition (F = 7.01, p = 0.011, η2 = 0.133). Post-hoc analysis revealed a significant improvement in the Baduanjin group from baseline to postintervention (p = 0.021), but the improvements were not maintained at the follow-up assessment (p = 0.070). The results also demonstrated significant group effects in balance function (p < 0.001, η2 = 0.283), motor dual-task performance (p = 0.026, η2 = 0.103), and cognitive dual-task performance (p < 0.001, η2 = 0.307). Post-hoc analysis revealed that the Baduanjin group improved more than the brisk walking group in the above outcomes (ps < 0.05). CONCLUSION This study demonstrated the differential effects of Baduanjin exercise and brisk walking in middle-aged patients with schizophrenia. Baduanjin might be a beneficial regimen for improving physical and cognitive function in this population. Further research with a larger sample is warranted. CLINICAL TRIAL REGISTRATION [ClinicalTrials.gov], identifier [202000817B0C602].
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Affiliation(s)
- Chyi-Rong Chen
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.,School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yu-Chi Huang
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yi-Wen Lee
- Department of Nursing, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Hui-Hsien Hsieh
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yi-Chen Lee
- School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Keh-Chung Lin
- School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan.,Division of Occupational Therapy, Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, Taipei, Taiwan
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Valizadeh A, Mbwogge M, Rasouli Yazdi A, Hedayati Amlashi N, Haadi A, Shayestefar M, Moassefi M. The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis. Front Psychiatry 2022; 13:884828. [PMID: 36213922 PMCID: PMC9532849 DOI: 10.3389/fpsyt.2022.884828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 08/16/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Mirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients. METHODS We included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual. RESULTS We included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect. DISCUSSION This finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism. SYSTEMATIC REVIEW REGISTRATION PROSPERO identifier: CRD42021236453.
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Affiliation(s)
- Amir Valizadeh
- Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | | | | | - Ainaaz Haadi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Monir Shayestefar
- Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mana Moassefi
- Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
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Reis-de-Oliveira G, Smith BJ, Martins-de-Souza D. Postmortem Brains: What Can Proteomics Tell us About the Sources of Schizophrenia? Advances in Experimental Medicine and Biology 2022; 1400:1-13. [DOI: 10.1007/978-3-030-97182-3_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Stȩpień-Wyrobiec O, Nowak M, Wyrobiec G, Morawiec E, Wierzbik-Strońska M, Staszkiewicz R, Grabarek BO. Crossroad between current knowledge and new perspective of diagnostic and therapy of late-onset schizophrenia and very late-onset schizophrenia-like psychosis: An update. Front Psychiatry 2022; 13:1025414. [PMID: 36387009 PMCID: PMC9643586 DOI: 10.3389/fpsyt.2022.1025414] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 10/11/2022] [Indexed: 11/23/2022] Open
Abstract
Schizophrenia is a chronic, highly individualized disease with many symptoms that can occur with varying severity in different patients. Schizophrenia affects 1% of the population, but occurs in almost 20% of patients after 40 years of age. It should be noted that the next peak in the incidence of schizophrenia occurs at the age of 60 years, affects mostly females, and is closely associated with a high risk of developing memory disorders. Therefore, postadolescent schizophrenia includes two distinct groups of patients: those whose symptoms onset at the age of 45 or 60. The purposes of this literature review were as follows: (1) synthetically characterize the clinical manifestations of schizophrenia; (2) discuss difficulties in the diagnosis of schizophrenia, especially in patients over 40 years of age; (3) discuss the clinical utility of different classes of marker in diagnostic and differentiating schizophrenia from neurodegenerative diseases in elderly people; (4) discuss therapeutic options for schizophrenia, pharmacotherapy, and psychotherapy, emphasizing the role of caregivers of people with psychosis in therapy, in preadolescence and postadolescence schizophrenia. We have tried to primarily discuss the findings of original articles from the last 10 years with an indication of their clinical implications with the issues discussed in the various subsections. Moreover, despite many years of research, no specific, precise algorithm has been developed that can be used in clinical practice during the diagnosis of schizophrenia. For this reason, the diagnosis of schizophrenia is primarily based on an interview with the patient and his family, as well as on the experience of a psychiatrist. It also seems that schizophrenia treatment should be carried out holistically, including pharmacotherapy, psychotherapy, and the support of caregivers of patients who have this psychosis, which increases the achievement of therapeutic success. Finally, we must be aware of the difficulties in diagnosing schizophrenia in the elderly and the need to modify pharmacological treatment. Currently, no guidelines have been developed for the differentiation of negative symptoms in elderly patients with schizophrenia from amotivation/avolition/apathy symptoms in elderly patients with neurodegenerative disorders.
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Affiliation(s)
- Olga Stȩpień-Wyrobiec
- Department of Geriatrics, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, Zabrze, Poland.,EMC Hospitals, John Paul II Geriatric Hospital in Katowice, Katowice, Poland
| | - Marta Nowak
- Department of Histology and Cell Pathology, Faculty of Medicine in Zabrze, Medical University of Silesia in Katowice, Zabrze, Poland
| | - Grzegorz Wyrobiec
- Department of Histology and Cell Pathology, Faculty of Medicine in Zabrze, Medical University of Silesia in Katowice, Zabrze, Poland
| | - Emilia Morawiec
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, University of Technology, Zabrze, Poland.,Department of Microbiology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, Zabrze, Poland.,Gyncentrum, Laboratory of Molecular Biology and Virology, Katowice, Poland
| | | | - Rafał Staszkiewicz
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, University of Technology, Zabrze, Poland.,5th Military Clinical Hospital with Polyclinic - Independent Public Health Care Facility in Krakow, Kraków, Poland
| | - Beniamin Oskar Grabarek
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, University of Technology, Zabrze, Poland.,Gyncentrum, Laboratory of Molecular Biology and Virology, Katowice, Poland.,Department of Gynecology and Obstetrics, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, Zabrze, Poland
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Joo SW, Kim H, Jo YT, Ahn S, Choi YJ, Park S, Kang Y, Lee J. White matter impairments in patients with schizophrenia: A multisite diffusion MRI study. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110381. [PMID: 34111494 DOI: 10.1016/j.pnpbp.2021.110381] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 05/31/2021] [Accepted: 06/04/2021] [Indexed: 10/21/2022]
Abstract
There is a lack of convincing and replicative findings regarding white matter abnormalities in schizophrenia. Several multisite diffusion magnetic resonance imaging (dMRI) studies have been conducted to increase statistical power and reveal subtle white matter changes. Data pooling methods are crucial in joint analysis to compensate for the use of different scanners and image acquisition parameters. A harmonization method using raw dMRI data was developed to overcome the limited generalizability of previous data pooling methods. We obtained dMRI data of 242 healthy controls and 190 patients with schizophrenia from four different study sites. After applying the harmonization method to the raw dMRI data, a two-tensor whole-brain tractography was performed, and diffusion measures were compared between the two groups. The correlation of fractional anisotropy (FA) with the positive and negative symptoms was evaluated, and the interaction effect of diagnosis-by-age, age-squared, and sex was examined. The following white matter tracts showed significant group differences in the FA: the right superior longitudinal fascicle (SLF), the left-to-right lateral orbitofrontal commissural tract, pars orbitalis (pOr-pOr) commissural tract, and pars triangularis (pTr-pTr) commissural tract. The FA of the right SLF and pTr-pTr commissural tract were significantly associated with the Positive and Negative Syndrome Scale (PANSS) positive and negative scores. No significant interaction effect was observed. These findings add to the evidence on structural brain abnormalities in schizophrenia and can aid in obtaining a better understanding of the biological foundations of schizophrenia.
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Affiliation(s)
- Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Harin Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Soojin Ahn
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Jae Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Soyeon Park
- Department of Psychiatry, Medical Foundation Yongin Mental Hospital, Yongin, Republic of Korea
| | - Yuree Kang
- Department of Psychiatry, Medical Foundation Yongin Mental Hospital, Yongin, Republic of Korea
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
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49
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Yang B, Zhang W, Lencer R, Tao B, Tang B, Yang J, Li S, Zeng J, Cao H, Sweeney JA, Gong Q, Lui S. Grey matter connectome abnormalities and age-related effects in antipsychotic-naive schizophrenia. EBioMedicine 2021; 74:103749. [PMID: 34906839 PMCID: PMC8671864 DOI: 10.1016/j.ebiom.2021.103749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/12/2021] [Accepted: 11/29/2021] [Indexed: 02/05/2023] Open
Abstract
Background Convergent evidence is increasing to indicate progressive brain abnormalities in schizophrenia. Knowing the brain network features over the illness course in schizophrenia, independent of effects of antipsychotic medications, would extend our sight on this question. Methods We recruited 237 antipsychotic-naive patients with schizophrenia range from 16 to 73 years old, and 254 healthy controls. High-resolution T1 weighted images were obtained with a 3.0T MR scanner. Grey matter networks were constructed individually based on the similarities of regional grey matter measurements. Network metrics were compared between patient groups and healthy controls, and regression analyses with age were conducted to determine potential differential rate of age-related changes between them. Findings Nodal centrality abnormalities were observed in patients with untreated schizophrenia, particularly in the central executive, default mode and salience networks. Accelerated age-related declines and illness duration-related declines were observed in global assortativity, and in nodal metrics of left superior temporal pole in schizophrenia patients. Although no significant intergroup differences in age-related regression were observed, the pattern of network metric alternation of left thalamus indicated higher nodal properties in early course patients, which decreased in long-term ill patients. Interpretations Global and nodal alterations in the grey matter connectome related to age and duration of illness in antipsychotic-naive patients, indicating potentially progressive network organizations mainly involving temporal regions and thalamus in schizophrenia independent from medication effects. Funding The National Natural Science Foundation of China, Sichuan Science and Technology Program, the Fundamental Research Funds for the Central Universities, Post-Doctor Research Project, West China Hospital, Sichuan University , the Science and Technology Project of the Health Planning Committee of Sichuan, Postdoctoral Interdisciplinary Research Project of Sichuan University and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.
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Affiliation(s)
- Beisheng Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Muenster, Germany
| | - Bo Tao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Biqiu Tang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jing Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Siyi Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jiaxin Zeng
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Hengyi Cao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, United States
| | - John A Sweeney
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
| | - Su Lui
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
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Di Biase MA, Cetin-Karayumak S, Lyall AE, Zalesky A, Cho KIK, Zhang F, Kubicki M, Rathi Y, Lyons MG, Bouix S, Billah T, Anticevic A, Schleifer C, Adkinson BD, Ji JL, Tamayo Z, Addington J, Bearden CE, Cornblatt BA, Keshavan MS, Mathalon DH, McGlashan TH, Perkins DO, Cadenhead KS, Tsuang MT, Woods SW, Stone WS, Shenton ME, Cannon TD, Pasternak O. White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis. Mol Psychiatry 2021; 26:6833-6844. [PMID: 34024906 PMCID: PMC8611104 DOI: 10.1038/s41380-021-01128-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 04/14/2021] [Indexed: 02/04/2023]
Abstract
Subtle alterations in white matter microstructure are observed in youth at clinical high risk (CHR) for psychosis. However, the timing of these changes and their relationships to the emergence of psychosis remain unclear. Here, we track the evolution of white matter abnormalities in a large, longitudinal cohort of CHR individuals comprising the North American Prodrome Longitudinal Study (NAPLS-3). Multi-shell diffusion magnetic resonance imaging data were collected across multiple timepoints (1-5 over 1 year) in 286 subjects (aged 12-32 years): 25 CHR individuals who transitioned to psychosis (CHR-P; 61 scans), 205 CHR subjects with unknown transition outcome after the 1-year follow-up period (CHR-U; 596 scans), and 56 healthy controls (195 scans). Linear mixed effects models were fitted to infer the impact of age and illness-onset on variation in the fractional anisotropy of cellular tissue (FAT) and the volume fraction of extracellular free water (FW). Baseline measures of white matter microstructure did not differentiate between HC, CHR-U and CHR-P individuals. However, age trajectories differed between the three groups in line with a developmental effect: CHR-P and CHR-U groups displayed higher FAT in adolescence, and 4% lower FAT by 30 years of age compared to controls. Furthermore, older CHR-P subjects (20+ years) displayed 4% higher FW in the forceps major (p < 0.05). Prospective analysis in CHR-P did not reveal a significant impact of illness onset on regional FAT or FW, suggesting that transition to psychosis is not marked by dramatic change in white matter microstructure. Instead, clinical high risk for psychosis-regardless of transition outcome-is characterized by subtle age-related white matter changes that occur in tandem with development.
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Affiliation(s)
- Maria A Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Kang Ik Kevin Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Monica G Lyons
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tashrif Billah
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alan Anticevic
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | | | - Brendan D Adkinson
- Yale Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
| | - Jie Lisa Ji
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Zailyn Tamayo
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Jean Addington
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior and Department of Psychology, University of California-Los Angeles, Los Angeles, CA, USA
| | - Barbara A Cornblatt
- Department of Psychiatry and Psychology, The Feinstein Institute for Medical Research, Manhasset, NY, USA
- Department of Psychology, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
- The Zucker Hillside Hospital, New York, NY, USA
| | - Matcheri S Keshavan
- Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniel H Mathalon
- University of California, San Francisco, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Thomas H McGlashan
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Diana O Perkins
- Department of Psychology, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
- University of North Carolina (UNC), Chapel Hill, NC, USA
| | - Kristen S Cadenhead
- Department of Psychiatry, University of California San Diego (UCSD), La Jolla, CA, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego (UCSD), La Jolla, CA, USA
| | - Scott W Woods
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - William S Stone
- Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tyrone D Cannon
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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