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Padmanabhan A, Prabhu PB, Vidyadharan V, Tharayil HM. Retinal Nerve Fiber Layer Thickness in Patients with Schizophrenia and Its Relation with Cognitive Impairment. Indian J Psychol Med 2024; 46:238-244. [PMID: 38699767 PMCID: PMC11062300 DOI: 10.1177/02537176231223311] [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] [Indexed: 05/05/2024] Open
Abstract
Background Schizophrenia is a chronic severe mental illness with heterogeneous clinical presentation, course, and outcome. Cognitive impairment is one of its core features. Retinal nerve fiber layer (RNFL) imaging using OCT (optical coherence tomography) could provide easy access for in vivo imaging of the retina, rendering it as a "window to the brain." Studies done on schizophrenia have shown RNFL thinning. This study attempts to look into the association between cognitive impairment, disease duration, and RNFL abnormality in patients with schizophrenia using OCT. Methods Patients diagnosed with schizophrenia meeting DSM 5 (Diagnostic and Statistical Manual of Mental Disorders) criteria and who were confirmed to be in remission for at least six months clinically and scoring less than three on PANSS-8 (positive and negative symptom scale-8) remission scale were included. They were administered the Montreal Cognitive Assessment Scale (MoCA) for cognitive assessment. RNFL measures were taken using spectral domain-OCT. Variables were compared using Pearson's correlation test, one-way ANOVA test, and independent t-test as appropriate. Results A total of 36 patients were studied. MoCA scores and RNFL thickness showed a positive correlation. Patients with schizophrenia had reduced average RNFL thickness and reduced RNFL thickness in superior, inferior, and temporal quadrants. Average RNFL thickness, Superior and inferior quadrant RNFL thickness showed a positive correlation with MoCA scores. No correlation was obtained between macular volume, macular thickness, duration of illness, and MoCA scores. Conclusion Patients with schizophrenia have reduced average RNFL thickness. Patients with low MoCA scores have RNFL thinning.
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Affiliation(s)
- Anu Padmanabhan
- Dept. of Psychiatry, Government Medical College, Kozhikode, Kerala, India
| | - Padma B. Prabhu
- Dept. of Ophthalmology, Government Medical College, Kozhikode, Kerala, India
| | - Varsha Vidyadharan
- Dept. of Psychiatry, Government Medical College, Kozhikode, Kerala, India
| | - Harish M. Tharayil
- Dept. of Psychiatry, Government Medical College, Kozhikode, Kerala, India
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Li F, Zhao Q, Tang T, Liu Y, Wang Z, Wang Z, Han X, Xu Z, Chang Y, Li Y. Brain imaging derived phenotypes: a biomarker for the onset of inflammatory bowel disease and a potential mediator of mental complications. Front Immunol 2024; 15:1359540. [PMID: 38469291 PMCID: PMC10925669 DOI: 10.3389/fimmu.2024.1359540] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/14/2024] [Indexed: 03/13/2024] Open
Abstract
Background and aims Inflammatory bowel disease (IBD), mainly categorized into Crohn's disease (CD) and ulcerative colitis (UC), is a chronic relapsing gastrointestinal disorder that significantly impairs patients' quality of life. IBD patients often experience comorbidities such as anxiety and depression, and the underlying mechanisms and treatment strategies remain areas of investigation. Methods We conducted a Mendelian randomization(MR) analysis utilizing brain image derived phenotypes (IDP) from the UK Biobank database to investigate the causal relationships between IBD and alterations in brain structural morphology and connectivity of neural tracts. This study aimed to identify biological evidence linking IBD to psychiatric disorders such as anxiety and depression. Results Specifically, the volume of grey matter in the Left Frontal Orbital Cortex exhibited a negative association with the onset of Crohn's disease (odds ratio (OR) [95% confidence interval (CI)]: 0.315[0.180~0.551], adjusted P=0.001), while the volume of the superior frontal cortex in the right hemisphere showed a positive correlation with the development of Ulcerative colitis (OR [95% CI]: 2.285[1.793~2.911], adjusted P<0.001), and the volume of lateral occipital cortex in the left hemisphere demonstrated a positive relationship with Crohn's disease onset (OR [95% CI]: 1.709[1.671~1.747], adjusted P<0.001). In the context of reverse causality, the onset of UC or CD has led to alterations in imaging derived phenotypes associated with five disorders (anxiety, depression, schizophrenia, bipolar disorder, pain) and three functions (memory, emotion, language). Conclusion Our study has demonstrated a causal relationship between IBD and IDPs. IDPs may serve as potential biomarkers for the progression of IBD and as predictive intermediaries for the development of neurological diseases in IBD patients.
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Affiliation(s)
- Fan Li
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Qi Zhao
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Tongyu Tang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
| | - Yuyuan Liu
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Zhaodi Wang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Zhi Wang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Xiaoping Han
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Zifeng Xu
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Yu Chang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Yuqin Li
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
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Wenzel J, Badde L, Haas SS, Bonivento C, Van Rheenen TE, Antonucci LA, Ruef A, Penzel N, Rosen M, Lichtenstein T, Lalousis PA, Paolini M, Stainton A, Dannlowski U, Romer G, Brambilla P, Wood SJ, Upthegrove R, Borgwardt S, Meisenzahl E, Salokangas RKR, Pantelis C, Lencer R, Bertolino A, Kambeitz J, Koutsouleris N, Dwyer DB, Kambeitz-Ilankovic L. Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness. Neuropsychopharmacology 2024; 49:573-583. [PMID: 37737273 PMCID: PMC10789737 DOI: 10.1038/s41386-023-01729-7] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 08/03/2023] [Accepted: 08/26/2023] [Indexed: 09/23/2023]
Abstract
Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.
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Affiliation(s)
- Julian Wenzel
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany.
| | - Luzie Badde
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, NY, USA
| | | | - Tamsyn E Van Rheenen
- Centre for Mental Health, School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Melbourne, VIC, Australia
| | - Linda A Antonucci
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Department of Translational Biomedicine and Neuroscience - University of Bari Aldo Moro, Bari, Italy
| | - Anne Ruef
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Nora Penzel
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
- Department of Translational Biomedicine and Neuroscience - University of Bari Aldo Moro, Bari, Italy
| | - Marlene Rosen
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Theresa Lichtenstein
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Paris Alexandros Lalousis
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King's College London, London, UK
| | - Marco Paolini
- Department of Radiology, University Hospital, Ludwig-Maximilian University, Munich, Germany
| | - Alexandra Stainton
- Orygen, Melbourne, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Muenster, Münster, Germany
| | - Georg Romer
- Department of Child and Adolescent Psychiatry, University of Münster, Münster, Germany
| | - Paolo Brambilla
- Department of Neuosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Mental Health, University of Milan, Milan, Italy
| | - Stephen J Wood
- Orygen, Melbourne, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
- School of Psychology, University of Birmingham, Birmingham, UK
| | - Rachel Upthegrove
- School of Psychology, University of Birmingham, Birmingham, UK
- Institute of Mental Health and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Stefan Borgwardt
- Translational Psychiatry Unit (TPU), Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | | | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, University of Melbourne & Western Health, Melbourne, VIC, Australia
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Muenster, Münster, Germany
- Translational Psychiatry Unit (TPU), Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience - University of Bari Aldo Moro, Bari, Italy
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King's College London, London, UK
- Max Planck Institute for Psychiatry, Munich, Germany
| | - Dominic B Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Orygen, Melbourne, VIC, Australia
| | - Lana Kambeitz-Ilankovic
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
- Faculty of Psychology and Educational Sciences, Department of Psychology, Ludwig-Maximilian University, Munich, Germany
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Haatveit B, Westlye LT, Vaskinn A, Flaaten CB, Mohn C, Bjella T, Sæther LS, Sundet K, Melle I, Andreassen OA, Alnæs D, Ueland T. Intra- and inter-individual cognitive variability in schizophrenia and bipolar spectrum disorder: an investigation across multiple cognitive domains. Schizophrenia (Heidelb) 2023; 9:89. [PMID: 38110366 PMCID: PMC10728206 DOI: 10.1038/s41537-023-00414-4] [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] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 11/17/2023] [Indexed: 12/20/2023]
Abstract
There is substantial cognitive heterogeneity among patients with schizophrenia (SZ) and bipolar disorders (BD). More knowledge about the magnitude and clinical correlates of performance variability could improve our understanding of cognitive impairments. Using double generalized linear models (DGLMs) we investigated cognitive mean and variability differences between patients with SZ (n = 905) and BD spectrum disorders (n = 522), and healthy controls (HC, n = 1170) on twenty-two variables. The analysis revealed significant case-control differences on 90% of the variables. Compared to HC, patients showed larger intra-individual (within subject) variability across tests and larger inter-individual (between subject) variability in measures of fine-motor speed, mental processing speed, and inhibitory control (SZ and BD), and in verbal learning and memory and intellectual functioning (SZ). In SZ, we found that lager intra -and inter (on inhibitory control and speed functions) individual variability, was associated with lower functioning and more negative symptoms. Inter-individual variability on single measures of memory and intellectual function was additionally associated with disorganized and positive symptoms, and use of antidepressants. In BD, there were no within-subject associations with symptom severity. However, greater inter-individual variability (primarily on inhibitory control and speeded functions) was associated with lower functioning, more negative -and disorganized symptoms, earlier age at onset, longer duration of illness, and increased medication use. These results highlight larger individual differences in patients compared to controls on various cognitive domains. Further investigations of the causes and correlates of individual differences in cognitive function are warranted.
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Affiliation(s)
- Beathe Haatveit
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Anja Vaskinn
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Research and Education in Forensic Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Camilla Bärthel Flaaten
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Christine Mohn
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Thomas Bjella
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Linn Sofie Sæther
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kjetil Sundet
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Torill Ueland
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
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5
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Alexandros Lalousis P, Schmaal L, Wood SJ, L E P Reniers R, Cropley VL, Watson A, Pantelis C, Suckling J, Barnes NM, Pariante C, Jones PB, Joyce E, Barnes TRE, Lawrie SM, Husain N, Dazzan P, Deakin B, Shannon Weickert C, Upthegrove R. Inflammatory subgroups of schizophrenia and their association with brain structure: A semi-supervised machine learning examination of heterogeneity. Brain Behav Immun 2023; 113:166-175. [PMID: 37423513 DOI: 10.1016/j.bbi.2023.06.023] [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: 10/06/2022] [Revised: 05/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023] Open
Abstract
OBJECTIVE Immune system dysfunction is hypothesised to contribute to structural brain changes through aberrant synaptic pruning in schizophrenia. However, evidence is mixed and there is a lack of evidence of inflammation and its effect on grey matter volume (GMV) in patients. We hypothesised that inflammatory subgroups can be identified and that the subgroups will show distinct neuroanatomical and neurocognitive profiles. METHODS The total sample consisted of 1067 participants (chronic patients with schizophrenia n = 467 and healthy controls (HCs) n = 600) from the Australia Schizophrenia Research Bank (ASRB) dataset, together with 218 recent-onset patients with schizophrenia from the external Benefit of Minocycline on Negative Symptoms of Psychosis: Extent and Mechanism (BeneMin) dataset. HYDRA (HeterogeneitY through DiscRiminant Analysis) was used to separate schizophrenia from HC and define disease-related subgroups based on inflammatory markers. Voxel-based morphometry and inferential statistics were used to explore GMV alterations and neurocognitive deficits in these subgroups. RESULTS An optimal clustering solution revealed five main schizophrenia groups separable from HC: Low Inflammation, Elevated CRP, Elevated IL-6/IL-8, Elevated IFN-γ, and Elevated IL-10 with an adjusted Rand index of 0.573. When compared with the healthy controls, the IL-6/IL-8 cluster showed the most widespread, including the anterior cingulate, GMV reduction. The IFN-γ inflammation cluster showed the least GMV reduction and impairment of cognitive performance. The CRP and the Low Inflammation clusters dominated in the younger external dataset. CONCLUSIONS Inflammation in schizophrenia may not be merely a case of low vs high, but rather there are pluripotent, heterogeneous mechanisms at play which could be reliably identified based on accessible, peripheral measures. This could inform the successful development of targeted interventions.
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Affiliation(s)
- Paris Alexandros Lalousis
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
| | - Lianne Schmaal
- Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, Australia
| | - Stephen J Wood
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Orygen, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, Australia
| | - Renate L E P Reniers
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom; Institute of Clinical Sciences, University of Birmingham, United Kingdom
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Andrew Watson
- The Department of Clinical and Motor Neuroscience, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia; NorthWestern Mental Health, Western Hospital Sunshine, St. Albans, Vicroria, Australia
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, Herchel Smith Building for Brain and Mind Sciences, University of Cambridge, United Kingdom; Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Nicholas M Barnes
- Institute for Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Carmine Pariante
- Stress, Psychiatry and Immunology Lab & Perinatal Psychiatry, The Maurice Wohl Clinical Neuroscience Institute, King's College London, London, United Kingdom
| | - Peter B Jones
- Brain Mapping Unit, Department of Psychiatry, Herchel Smith Building for Brain and Mind Sciences, University of Cambridge, United Kingdom; Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Eileen Joyce
- The Department of Clinical and Motor Neuroscience, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Thomas R E Barnes
- Division of Psychiatry, Imperial College London, London United Kingdom
| | - Stephen M Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Nusrat Husain
- Division of Psychology and Mental Health, University of Manchester & Mersey Care NHS Foundation Trust
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Bill Deakin
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom
| | - Cynthia Shannon Weickert
- Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY, USA; Schizophrenia Research Laboratory, Neuroscience Research Australia, Sydney, New South Wales, Australia; School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom; Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom; Birmingham Early Interventions Service, Birmingham Women's and Children's NHS Foundation Trust, United Kingdom
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Mohamed Saini S, Bousman CA, Mancuso SG, Cropley V, Van Rheenen TE, Lenroot RK, Bruggemann J, Weickert CS, Weickert TW, Sundram S, Everall IP, Pantelis C. Genetic variation in glutamatergic genes moderates the effects of childhood adversity on brain volume and IQ in treatment-resistant schizophrenia. Schizophrenia (Heidelb) 2023; 9:59. [PMID: 37709784 PMCID: PMC10502098 DOI: 10.1038/s41537-023-00381-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/20/2023] [Indexed: 09/16/2023]
Affiliation(s)
- Suriati Mohamed Saini
- Department of Psychiatry, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Cheras, Kuala Lumpur, Malaysia.
- Department of Psychiatry, Hospital Canselor Tuanku Muhriz, Jalan Yaacob Latif, Cheras, Kuala Lumpur, Malaysia.
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Medical Genetics, Psychiatry, and Physiology and Pharmacology, The University of Calgary, Calgary, AB, Canada
| | - Serafino G Mancuso
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University, Melbourne, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University, Melbourne, VIC, Australia
| | - Rhoshel K Lenroot
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Psychiatry and Behavioural Science, University of New Mexico, Albuquerque, NM, USA
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Neuroscience Research Australia, Randwick, NSW, Australia
- Schizophrenia Research Institute, Sydney, NSW, Australia
| | - Cynthia S Weickert
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, NY, USA
- Schizophrenia Research Laboratory, Neuroscience Research Australia, NSW, Australia
| | - Thomas W Weickert
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, NY, USA
| | - Suresh Sundram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
- Monash Medical Centre, Monash Health, Clayton, VIC, Australia
| | - Ian P Everall
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
- Western Centre for Health Research & Education, Sunshine Hospital, Western Health, St Albans, VIC, 3021, Australia
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7
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Gurvich C, Thomas N, Hudaib AR, Van Rheenen TE, Thomas EHX, Tan EJ, Neill E, Carruthers SP, Sumner PJ, Romano-Silva M, Bozaoglu K, Kulkarni J, Rossell SL. The relationship between cognitive clusters and telomere length in bipolar-schizophrenia spectrum disorders. Psychol Med 2023; 53:5119-5126. [PMID: 35920237 DOI: 10.1017/s0033291722002148] [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] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Schizophrenia and bipolar disorder are complex mental illnesses that are associated with cognitive deficits. There is considerable cognitive heterogeneity that exists within both disorders. Studies that cluster schizophrenia and bipolar patients into subgroups based on their cognitive profile increasingly demonstrate that, relative to healthy controls, there is a severely compromised subgroup and a relatively intact subgroup. There is emerging evidence that telomere shortening, a marker of cellular senescence, may be associated with cognitive impairments. The aim of this study was to explore the relationship between cognitive subgroups in bipolar-schizophrenia spectrum disorders and telomere length against a healthy control sample. METHODS Participants included a transdiagnostic group diagnosed with bipolar, schizophrenia or schizoaffective disorder (n = 73) and healthy controls (n = 113). Cognitive clusters within the transdiagnostic patient group, were determined using K-means cluster analysis based on current cognitive functioning (MATRICS Consensus Cognitive Battery scores). Telomere length was determined using quantitative PCRs genomic DNA extracted from whole blood. Emergent clusters were then compared to the healthy control group on telomere length. RESULTS Two clusters emerged within the patient group that were deemed to reflect a relatively intact cognitive group and a cognitively impaired subgroup. Telomere length was significantly shorter in the severely impaired cognitive subgroup compared to the healthy control group. CONCLUSIONS This study replicates previous findings of transdiagnostic cognitive subgroups and associates shorter telomere length with the severely impaired cognitive subgroup. These findings support emerging literature associating cognitive impairments in psychiatric disorders to accelerated cellular aging as indexed by telomere length.
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Affiliation(s)
- Caroline Gurvich
- Department of Psychiatry, Central Clinical School, Monash University and the Alfred Hospital, Melbourne, VIC, Australia
| | - Natalie Thomas
- Department of Biochemistry & Pharmacology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne VIC, Australia
| | - Abdul-Rahman Hudaib
- Department of Psychiatry, Central Clinical School, Monash University and the Alfred Hospital, Melbourne, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, VIC, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Elizabeth H X Thomas
- Department of Psychiatry, Central Clinical School, Monash University and the Alfred Hospital, Melbourne, VIC, Australia
| | - Eric J Tan
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, VIC, Australia
- Department of Mental Health, St Vincent's Hospital, Melbourne, VIC, Australia
| | - Erica Neill
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, VIC, Australia
- Department of Mental Health, St Vincent's Hospital, Melbourne, VIC, Australia
| | - Sean P Carruthers
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Philip J Sumner
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Marco Romano-Silva
- Department Saude Mental, Faculdade de Medicina, UFMG, Belo Horizonte, Brazil
| | - Kiymet Bozaoglu
- Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jayashri Kulkarni
- Department of Psychiatry, Central Clinical School, Monash University and the Alfred Hospital, Melbourne, VIC, Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, VIC, Australia
- Department of Mental Health, St Vincent's Hospital, Melbourne, VIC, Australia
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8
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Watson AJ, Giordano A, Suckling J, Barnes TRE, Husain N, Jones PB, Krynicki CR, Lawrie SM, Lewis S, Nikkheslat N, Pariante CM, Upthegrove R, Deakin B, Dazzan P, Joyce EM. Cognitive function in early-phase schizophrenia-spectrum disorder: IQ subtypes, brain volume and immune markers. Psychol Med 2023; 53:2842-2851. [PMID: 35177144 PMCID: PMC10244009 DOI: 10.1017/s0033291721004815] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [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: 02/12/2021] [Revised: 10/30/2021] [Accepted: 11/03/2021] [Indexed: 01/08/2023]
Abstract
BACKGROUND Evidence suggests that cognitive subtypes exist in schizophrenia that may reflect different neurobiological trajectories. We aimed to identify whether IQ-derived cognitive subtypes are present in early-phase schizophrenia-spectrum disorder and examine their relationship with brain structure and markers of neuroinflammation. METHOD 161 patients with recent-onset schizophrenia spectrum disorder (<5 years) were recruited. Estimated premorbid and current IQ were calculated using the Wechsler Test of Adult Reading and a 4-subtest WAIS-III. Cognitive subtypes were identified with k-means clustering. Freesurfer was used to analyse 3.0 T MRI. Blood samples were analysed for hs-CRP, IL-1RA, IL-6 and TNF-α. RESULTS Three subtypes were identified indicating preserved (PIQ), deteriorated (DIQ) and compromised (CIQ) IQ. Absolute total brain volume was significantly smaller in CIQ compared to PIQ and DIQ, and intracranial volume was smaller in CIQ than PIQ (F(2, 124) = 6.407, p = 0.002) indicative of premorbid smaller brain size in the CIQ group. CIQ had higher levels of hs-CRP than PIQ (F(2, 131) = 5.01, p = 0.008). PIQ showed differentially impaired processing speed and verbal learning compared to IQ-matched healthy controls. CONCLUSIONS The findings add validity of a neurodevelopmental subtype of schizophrenia identified by comparing estimated premorbid and current IQ and characterised by smaller premorbid brain volume and higher measures of low-grade inflammation (CRP).
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Affiliation(s)
- Andrew J. Watson
- The Department of Clinical and Motor Neuroscience, UCL Queen Square Institute of Neurology, London, UK
| | - Annalisa Giordano
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, Herchel Smith Building for Brain and Mind Sciences, University of Cambridge, Cambridge, UK
| | | | - Nusrat Husain
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
- MAHSC, The University of Manchester, Manchester, UK
- Lancashire & South Cumbria NHS Foundation Trust, Accrington, UK
| | - Peter B. Jones
- Brain Mapping Unit, Department of Psychiatry, Herchel Smith Building for Brain and Mind Sciences, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
| | - Carl R. Krynicki
- Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Stephen M. Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Shôn Lewis
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
- MAHSC, The University of Manchester, Manchester, UK
| | - Naghmeh Nikkheslat
- Stress, Psychiatry and Immunology Lab & Perinatal Psychiatry, The Maurice Wohl Clinical Neuroscience Institute, King's College London, London, UK
| | - Carmine M. Pariante
- Stress, Psychiatry and Immunology Lab & Perinatal Psychiatry, The Maurice Wohl Clinical Neuroscience Institute, King's College London, London, UK
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, UK
- Forward thinking Birmingham, Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Bill Deakin
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Eileen M. Joyce
- The Department of Clinical and Motor Neuroscience, UCL Queen Square Institute of Neurology, London, UK
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9
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Karantonis JA, Carruthers SP, Burdick KE, Pantelis C, Green M, Rossell SL, Hughes ME, Cropley V, Van Rheenen TE. Brain Morphological Characteristics of Cognitive Subgroups of Schizophrenia-Spectrum Disorders and Bipolar Disorder: A Systematic Review with Narrative Synthesis. Neuropsychol Rev 2023; 33:192-220. [PMID: 35194692 DOI: 10.1007/s11065-021-09533-0] [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] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 11/23/2021] [Indexed: 10/19/2022]
Abstract
Despite a growing body of research, there is yet to be a cohesive synthesis of studies examining differences in brain morphology according to patterns of cognitive function among both schizophrenia-spectrum disorder (SSD) and bipolar disorder (BD) individuals. We aimed to provide a systematic overview of the morphological differences-inclusive of grey and white matter volume, cortical thickness, and cortical surface area-between cognitive subgroups of these disorders and healthy controls, and between cognitive subgroups themselves. An initial search of PubMed and Scopus databases resulted in 1486 articles of which 20 met inclusion criteria and were reviewed in detail. The findings of this review do not provide strong evidence that cognitive subgroups of SSD or BD map to unique patterns of brain morphology. There is preliminary evidence to suggest that reductions in cortical thickness may be more strongly associated with cognitive impairment, whilst volumetric deficits may be largely tied to the presence of disease.
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10
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Valli I, De la Serna E, Segura AG, Pariente JC, Calvet-Mirabent A, Borras R, Ilzarbe D, Moreno D, Martín-Martínez N, Baeza I, Rosa-Justicia M, Garcia-Rizo C, Díaz-Caneja CM, Crossley NA, Young AH, Vieta E, Mas S, Castro-Fornieles J, Sugranyes G. Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder. J Am Acad Child Adolesc Psychiatry 2023; 62:74-83. [PMID: 35710081 DOI: 10.1016/j.jaac.2022.05.011] [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] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/21/2022] [Accepted: 06/06/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Cognitive impairment is an important feature of schizophrenia (SZ) and bipolar disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership. METHOD One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores. RESULTS Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area. CONCLUSION Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.
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Affiliation(s)
- Isabel Valli
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London.
| | - Elena De la Serna
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | | | - Jose C Pariente
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Roger Borras
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Daniel Ilzarbe
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Dolores Moreno
- Institute of Neuroscience, Hospital Clínic Barcelona, Spain; Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nuria Martín-Martínez
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Inmaculada Baeza
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Mireia Rosa-Justicia
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente Garcia-Rizo
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nicolas A Crossley
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Allan H Young
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, United Kingdom
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Sergi Mas
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; University of Barcelona, Spain
| | - Josefina Castro-Fornieles
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Gisela Sugranyes
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
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11
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Zhao Q, Cao H, Zhang W, Li S, Xiao Y, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Hill SK, Keedy SK, Ivleva EI, Lencer R, Sweeney JA, Gong Q, Lui S. A subtype of institutionalized patients with schizophrenia characterized by pronounced subcortical and cognitive deficits. Neuropsychopharmacology 2022; 47:2024-2032. [PMID: 35260788 PMCID: PMC9556672 DOI: 10.1038/s41386-022-01300-w] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 01/28/2022] [Accepted: 02/19/2022] [Indexed: 02/05/2023]
Abstract
Some patients with schizophrenia have severe cognitive impairment and functional deficits that require long-term institutional care. The patterns of brain-behavior alterations in these individuals, and their differences from patients living successfully in the community, remain poorly understood. Previous cognition-based studies for stratifying schizophrenia patients highlight the importance of subcortical structures in the context of illness heterogeneity. In the present study, subcortical volumes from 96 institutionalized patients with long-term schizophrenia were evaluated using cluster analysis to test for heterogeneity. These data were compared to those from two groups of community-dwelling individuals with schizophrenia for comparison purposes, including 68 long-term ill and 126 first-episode individuals. A total of 290 demographically matched healthy participants were included as normative references at a 1:1 ratio for each patient sample. A subtype of institutionalized patients was identified based on their pattern of subcortical alterations. Using a machine learning algorithm developed to discriminate the two groups of institutionalized patients, all three patient samples were found to have similar rates of patients assigned to the two subtypes (approximately 50% each). In institutionalized patients, only the subtype with the identified pattern of subcortical alterations had greater neocortical and cognitive abnormalities than those in the similarity classified community-dwelling patients with long-term illness. Thus, for the subtype of patients with a distinctive pattern of subcortical alterations, when the distinct pattern of subcortical alterations is present and particularly severe, it is associated with cognitive impairments that may contribute to persistent disability and institutionalization.
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Affiliation(s)
- Qiannan Zhao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Hengyi Cao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Wenjing Zhang
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Siyi Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Yuan Xiao
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University and Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Elliot S Gershon
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Scot Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
| | - Su Lui
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan Province, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
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12
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Shao T, Wang W, Hei G, Yang Y, Long Y, Wang X, Xiao J, Huang Y, Song X, Xu X, Gao S, Huang J, Wang Y, Zhao J, Wu R. Identifying and revealing different brain neural activities of cognitive subtypes in early course schizophrenia. Front Mol Neurosci 2022; 15:983995. [PMID: 36267704 PMCID: PMC9577612 DOI: 10.3389/fnmol.2022.983995] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/07/2022] [Indexed: 01/10/2023] Open
Abstract
Background Cognitive subtypes of schizophrenia may exhibit different neurobiological characteristics. This study aimed to reveal the underlying neurobiological features between cognitive subtypes in the early course of schizophrenia (ECS). According to prior studies, we hypothesized to identify 2–4 distinct cognitive subtypes. We further hypothesized that the subtype with relatively poorer cognitive function might have lower brain spontaneous neural activity than the subtype with relatively better cognitive function. Method Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Resting-state functional magnetic resonance imaging scanning was conducted for each individual. There were 155 ECS individuals and 97 healthy controls (HCs) included in the subsequent analysis. Latent profile analysis (LPA) was used to identify the cognitive subtypes in ECS individuals, and amplitude of low-frequency fluctuations (ALFFs) was used to measure brain spontaneous neural activity in ECS individuals and HCs. Results LPA identified two cognitive subtypes in ECS individuals, containing a severely impaired subtype (SI, n = 63) and a moderately impaired subtype (MI, n = 92). Compared to HCs, ECS individuals exhibited significantly increased ALFF in the left caudate and bilateral thalamus and decreased ALFF in the bilateral medial prefrontal cortex and bilateral posterior cingulate cortex/precuneus (PCC/PCu). In ECS cognitive subtypes, SI showed significantly higher ALFF in the left precentral gyrus (PreCG) and lower ALFF in the left PCC/PCu than MI. Furthermore, ALFFs of left PreCG were negatively correlated with several MCCB cognitive domains in ECS individuals, while ALFF of left PCC/PCu presented opposite correlations. Conclusion Our findings suggest that differences in the brain spontaneous neural activity of PreCG and PCC/PCu might be the potential neurobiological features of the cognitive subtypes in ECS, which may deepen our understanding of the role of PreCG and PCC/PCu in the pathogenesis of cognitive impairment in schizophrenia.
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Affiliation(s)
- Tiannan Shao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Weiyan Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Gangrui Hei
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ye Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yujun Long
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiaoyi Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jingmei Xiao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yuyan Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xueqin Song
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xijia Xu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Shuzhan Gao
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jing Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ying Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jingping Zhao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Renrong Wu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- *Correspondence: Renrong Wu
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13
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Ringin E, Cropley V, Zalesky A, Bruggemann J, Sundram S, Weickert CS, Weickert TW, Bousman CA, Pantelis C, Van Rheenen TE. The impact of smoking status on cognition and brain morphology in schizophrenia spectrum disorders. Psychol Med 2022; 52:3097-3115. [PMID: 33443010 DOI: 10.1017/s0033291720005152] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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: 01/09/2023]
Abstract
BACKGROUND Cigarette smoking is associated with worse cognition and decreased cortical volume and thickness in healthy cohorts. Chronic cigarette smoking is prevalent in schizophrenia spectrum disorders (SSD), but the effects of smoking status on the brain and cognition in SSD are not clear. This study aimed to understand whether cognitive performance and brain morphology differed between smoking and non-smoking individuals with SSD compared to healthy controls. METHODS Data were obtained from the Australian Schizophrenia Research Bank. Cognitive functioning was measured in 299 controls and 455 SSD patients. Cortical volume, thickness and surface area data were analysed from T1-weighted structural scans obtained in a subset of the sample (n = 82 controls, n = 201 SSD). Associations between smoking status (cigarette smoker/non-smoker), cognition and brain morphology were tested using analyses of covariance, including diagnosis as a moderator. RESULTS No smoking by diagnosis interactions were evident, and no significant differences were revealed between smokers and non-smokers across any of the variables measured, with the exception of a significantly thinner left posterior cingulate in smokers compared to non-smokers. Several main effects of smoking in the cognitive, volume and thickness analyses were initially significant but did not survive false discovery rate (FDR) correction. CONCLUSIONS Despite the general absence of significant FDR-corrected findings, trend-level effects suggest the possibility that subtle smoking-related effects exist but were not uncovered due to low statistical power. An investigation of this topic is encouraged to confirm and expand on our findings.
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Affiliation(s)
- Elysha Ringin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC, Australia
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Suresh Sundram
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, Australia
- Mental Health Program, Monash Health, Clayton, Victoria, Australia
| | - Cynthia Shannon Weickert
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
- Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, New York 13210, USA
| | - Thomas W Weickert
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
- Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, New York 13210, USA
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
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14
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Wortinger LA, Engen K, Barth C, Andreassen OA, Nordbø Jørgensen K, Agartz I. Asphyxia at birth affects brain structure in patients on the schizophrenia-bipolar disorder spectrum and healthy participants. Psychol Med 2022; 52:1050-1059. [PMID: 32772969 PMCID: PMC9069351 DOI: 10.1017/s0033291720002779] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 06/05/2020] [Accepted: 07/16/2020] [Indexed: 12/24/2022]
Abstract
BACKGROUND Uncertainty exists about what causes brain structure alterations associated with schizophrenia (SZ) and bipolar disorder (BD). Whether a history of asphyxia-related obstetric complication (ASP) - a common but harmful condition for neural tissue - contributes to variations in adult brain structure is unclear. We investigated ASP and its relationship to intracranial (ICV), global brain volumes and regional cortical and subcortical structures. METHODS A total of 311 patients on the SZ - BD spectrum and 218 healthy control (HC) participants underwent structural magnetic resonance imaging. They were evaluated for ASP using prospective information obtained from the Medical Birth Registry of Norway. RESULTS In all groups, ASP was related to smaller ICV, total brain, white and gray matter volumes and total surface area, but not to cortical thickness. Smaller cortical surface areas were found across frontal, parietal, occipital, temporal and insular regions. Smaller hippocampal, amygdala, thalamus, caudate and putamen volumes were reported for all ASP subgroups. ASP effects did not survive ICV correction, except in the caudate, which remained significantly smaller in both patient ASP subgroups, but not in the HC. CONCLUSIONS Since ASP was associated with smaller brain volumes in all groups, the genetic risk of developing a severe mental illness, alone, cannot easily explain the smaller ICV. Only the smaller caudate volumes of ASP patients specifically suggest that injury from ASP can be related to disease development. Our findings give support for the ICV as a marker of aberrant neurodevelopment and ASP in the etiology of brain development in BD and SZ.
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Affiliation(s)
- Laura Anne Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kristine Engen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Claudia Barth
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, NORMENT, Oslo University Hospital, Oslo, Norway
| | - Kjetil Nordbø Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institute, Stockholm, Sweden
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15
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Haining K, Gajwani R, Gross J, Gumley AI, Ince RAA, Lawrie SM, Schultze-Lutter F, Schwannauer M, Uhlhaas PJ. Characterising cognitive heterogeneity in individuals at clinical high-risk for psychosis: a cluster analysis with clinical and functional outcome prediction. Eur Arch Psychiatry Clin Neurosci 2022; 272:437-448. [PMID: 34401957 PMCID: PMC8938352 DOI: 10.1007/s00406-021-01315-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 07/26/2021] [Indexed: 12/24/2022]
Abstract
Schizophrenia is characterised by cognitive impairments that are already present during early stages, including in the clinical high-risk for psychosis (CHR-P) state and first-episode psychosis (FEP). Moreover, data suggest the presence of distinct cognitive subtypes during early-stage psychosis, with evidence for spared vs. impaired cognitive profiles that may be differentially associated with symptomatic and functional outcomes. Using cluster analysis, we sought to determine whether cognitive subgroups were associated with clinical and functional outcomes in CHR-P individuals. Data were available for 146 CHR-P participants of whom 122 completed a 6- and/or 12-month follow-up; 15 FEP participants; 47 participants not fulfilling CHR-P criteria (CHR-Ns); and 53 healthy controls (HCs). We performed hierarchical cluster analysis on principal components derived from neurocognitive and social cognitive measures. Within the CHR-P group, clusters were compared on clinical and functional variables and examined for associations with global functioning, persistent attenuated psychotic symptoms and transition to psychosis. Two discrete cognitive subgroups emerged across all participants: 45.9% of CHR-P individuals were cognitively impaired compared to 93.3% of FEP, 29.8% of CHR-N and 30.2% of HC participants. Cognitively impaired CHR-P participants also had significantly poorer functioning at baseline and follow-up than their cognitively spared counterparts. Specifically, cluster membership predicted functional but not clinical outcome. Our findings support the existence of distinct cognitive subgroups in CHR-P individuals that are associated with functional outcomes, with implications for early intervention and the understanding of underlying developmental processes.
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Affiliation(s)
- Kate Haining
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Ruchika Gajwani
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Andrew I Gumley
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Robin A A Ince
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Stephen M Lawrie
- Department of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Department of Psychology and Mental Health, Faculty of Psychology, Airlangga University, Surabaya, Indonesia
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany.
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16
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Oomen PP, Gangadin SS, Begemann MJH, Visser E, Mandl RCW, Sommer IEC. The neurobiological characterization of distinct cognitive subtypes in early-phase schizophrenia-spectrum disorders. Schizophr Res 2022; 241:228-237. [PMID: 35176721 DOI: 10.1016/j.schres.2022.02.006] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 01/28/2022] [Accepted: 02/04/2022] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Cognitive deficits are present in some, but not all patients with schizophrenia-spectrum disorders (SSD). We and others have demonstrated three cognitive clusters: cognitively intact patients, patients with deficits in a few domains and those with global cognitive deficits. This study aimed to identify cognitive subtypes of early-phase SSD with matched controls as a reference group, and evaluated cognitive subgroups regarding clinical and brain volumetric measures. METHODS Eighty-six early-phase SSD patients were included. Hierarchical cluster analysis was conducted using global performance on the Brief Assessment of Cognition in Schizophrenia (BACS). Cognitive subgroups were subsequently related to clinical and brain volumetric measures (cortical, subcortical and cortical thickness) using ANCOVA. RESULTS Three distinct cognitive clusters emerged: relative to controls we found one cluster of patients with preserved cognition (n = 25), one moderately impaired cluster (n = 38) and one severely impaired cluster (n = 23). Cognitive subgroups were characterized by differences in volume of the left postcentral gyrus, left middle caudal frontal gyrus and left insula, while differences in cortical thickness were predominantly found in fronto-parietal regions. No differences were demonstrated in subcortical brain volume. DISCUSSION Current results replicate the existence of three distinct cognitive subgroups including one relatively large group with preserved cognitive function. Cognitive subgroups were characterized by differences in cortical regional brain volume and cortical thickness, suggesting associations with cortical, but not subcortical development and cognitive functioning such as attention, executive functions and speed of processing.
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Affiliation(s)
- P P Oomen
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands.
| | - S S Gangadin
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - M J H Begemann
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - E Visser
- Department of Psychiatry, University Medical Center, Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - R C W Mandl
- Department of Psychiatry, University Medical Center, Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - I E C Sommer
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
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17
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Wei Q, Yan W, Zhang R, Yang X, Xie S. Aberrant cortical surface and cognition function in drug-naive first-episode schizophrenia. Ann Gen Psychiatry 2022; 21:4. [PMID: 35144626 PMCID: PMC8830089 DOI: 10.1186/s12991-022-00381-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [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: 06/22/2021] [Accepted: 01/23/2022] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE Impaired cognitive function is a central symptom of schizophrenia and is often correlated with inferior global functional outcomes. However, the role of some neurobiological factors such as cortical structure alterations in the underlying cognitive damages in schizophrenia remains unclear. The present study attempted to explore the neurobiomarkers of cognitive function in drug-naive, first-episode schizophrenia by using structural magnetic resonance imaging (MRI). METHODS The present study was conducted in patients with drug-naive, first-episode schizophrenia (SZ) and healthy controls (HCs). MRI T1 images were pre-processed using CAT12. Surface-based morphometry (SBM) was utilised to evaluate structural parameters such as cortical thickness and sulcus depth. The positive and negative syndrome scale (PANSS) and Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) consensus cognitive battery (MCCB) were employed to estimate the psychotic symptoms and cognition, respectively. RESULTS A total of 117 patients with drug-naive first-episode schizophrenia (SZ) and 98 healthy controls (HCs) were included. Both the cortical thickness and sulcus depth in the frontal lobe were lower in patients with SZ than in the HCs under family-wise error correction (p < 0.05). Attention and visual learning in MCCB were positively correlated with the right lateral orbitofrontal cortical thickness in the patients with SZ (p < 0.01). CONCLUSIONS The reduced surface value of multiple cortical structures, particularly the cortical thickness and sulcus depth in the frontal lobe, could be the potential biomarkers for cognitive impairment in SZ.
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Affiliation(s)
- Qianqian Wei
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Wei Yan
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Rongrong Zhang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Xuna Yang
- Medical Department, Suzhou Guangji Hospital, Suzhou, 215008, China.
| | - Shiping Xie
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China.
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18
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Haas SS, Ge R, Sanford N, Modabbernia A, Reichenberg A, Whalley HC, Kahn RS, Frangou S. Accelerated Global and Local Brain Aging Differentiate Cognitively Impaired From Cognitively Spared Patients With Schizophrenia. Front Psychiatry 2022; 13:913470. [PMID: 35815015 PMCID: PMC9257006 DOI: 10.3389/fpsyt.2022.913470] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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: 04/05/2022] [Accepted: 05/30/2022] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Accelerated aging has been proposed as a mechanism underlying the clinical and cognitive presentation of schizophrenia. The current study extends the field by examining both global and regional patterns of brain aging in schizophrenia, as inferred from brain structural data, and their association with cognitive and psychotic symptoms. METHODS Global and local brain-age-gap-estimates (G-brainAGE and L-brainAGE) were computed using a U-Net Model from T1-weighted structural neuroimaging data from 84 patients (aged 16-35 years) with early-stage schizophrenia (illness duration <5 years) and 1,169 healthy individuals (aged 16-37 years). Multidomain cognitive data from the patient sample were submitted to Heterogeneity through Discriminative Analysis (HYDRA) to identify cognitive clusters. RESULTS HYDRA classified patients into a cognitively impaired cluster (n = 69) and a cognitively spared cluster (n = 15). Compared to healthy individuals, G-brainAGE was significantly higher in the cognitively impaired cluster (+11.08 years) who also showed widespread elevation in L-brainAGE, with the highest deviance observed in frontal and temporal regions. The cognitively spared cluster showed a moderate increase in G-brainAGE (+8.94 years), and higher L-brainAGE localized in the anterior cingulate cortex. Psychotic symptom severity in both clusters showed a positive but non-significant association with G-brainAGE. DISCUSSION Accelerated aging in schizophrenia can be detected at the early disease stages and appears more closely associated with cognitive dysfunction rather than clinical symptoms. Future studies replicating our findings in multi-site cohorts with larger numbers of participants are warranted.
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Affiliation(s)
- Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Ruiyang Ge
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Nicole Sanford
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Amirhossein Modabbernia
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Abraham Reichenberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States.,Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
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19
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Carruthers SP, Van Rheenen TE, Karantonis JA, Rossell SL. Characterising Demographic, Clinical and Functional Features of Cognitive Subgroups in Schizophrenia Spectrum Disorders: A Systematic Review. Neuropsychol Rev 2021; 32:807-827. [PMID: 34694542 DOI: 10.1007/s11065-021-09525-0] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 08/02/2021] [Indexed: 11/24/2022]
Abstract
Considerable cognitive heterogeneity is present within the schizophrenia spectrum disorder (SSD) population. Several subgroups characterised by more homogenous cognitive profiles have been identified. It is not yet clear however, whether these subgroups represent different points along a continuum of cognitive symptom severity, or whether they reflect unique profiles of the disorder. One way to determine this is by comparing subgroups on their non-cognitive characteristics. The aim of the present review was to systematically summarise our current understanding of the non-cognitive features of the cognitive subgroups of schizophrenia spectrum disorder (SSD). Thirty-five relevant studies were identified from January 1980 to March 2020. Cognitive subgroups were consistently compared on age, sex, education, age of illness onset, illness duration, positive, negative and disorganised symptoms, depression and psychosocial functioning. It was revealed that subgroups were consistently distinguished by education, negative symptom severity and degree of functional impairment; with subgroups characterised by worse cognitive functioning performing/rated worse on these characteristics. The lack of consistent subgroup differences for the majority of the non-cognitive characteristics provides partial support for the notion that cognitive subgrouping in SSD is not simply reflecting a rehash of previously identified clinical subtypes. However, as subgroups were consistently distinguished by three characteristics known to be associated with cognition, our understanding of the extent to which the cognitive subgrouping approach is representing separate subtypes versus subdivisions along a continuum of symptom severity is still not definitive.
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Affiliation(s)
- Sean P Carruthers
- Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia.
| | - Tamsyn E Van Rheenen
- Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, 3053, Australia
| | - James A Karantonis
- Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, 3053, Australia
| | - Susan L Rossell
- Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia.,Department of Psychiatry, St Vincent's Hospital, Melbourne VIC, Australia
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20
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Jiang Y, Duan M, Li X, Huang H, Zhao G, Li X, Li S, Song X, He H, Yao D, Luo C. Function-structure coupling: White matter functional magnetic resonance imaging hyper-activation associates with structural integrity reductions in schizophrenia. Hum Brain Mapp 2021; 42:4022-4034. [PMID: 34110075 PMCID: PMC8288085 DOI: 10.1002/hbm.25536] [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] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 05/04/2021] [Accepted: 05/08/2021] [Indexed: 01/12/2023] Open
Abstract
White matter (WM) microstructure deficit may be an underlying factor in the brain dysconnectivity hypothesis of schizophrenia using diffusion tensor imaging (DTI). However, WM dysfunction is unclear in schizophrenia. This study aimed to investigate the association between structural deficits and functional disturbances in major WM tracts in schizophrenia. Using functional magnetic resonance imaging (fMRI) and DTI, we developed the skeleton-based WM functional analysis, which could achieve voxel-wise function-structure coupling by projecting the fMRI signals onto a skeleton in WM. We measured the fractional anisotropy (FA) and WM low-frequency oscillation (LFO) and their couplings in 93 schizophrenia patients and 122 healthy controls (HCs). An independent open database (62 schizophrenia patients and 71 HCs) was used to test the reproducibility. Finally, associations between WM LFO and five behaviour assessment categories (cognition, emotion, motor, personality and sensory) were examined. This study revealed a reversed pattern of structure and function in frontotemporal tracts, as follows. (a) WM hyper-LFO was associated with reduced FA in schizophrenia. (b) The function-structure association was positive in HCs but negative in schizophrenia patients. Furthermore, function-structure dissociation was exacerbated by long illness duration and severe negative symptoms. (c) WM activations were significantly related to cognition and emotion. This study indicated function-structure dys-coupling, with higher LFO and reduced structural integration in frontotemporal WM, which may reflect a potential mechanism in WM neuropathologic processing of schizophrenia.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Psychiatry, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xiangkui Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Guocheng Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Radiology, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Shicai Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Psychiatry, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xufeng Song
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Psychiatry, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical SciencesChengduPeople's Republic of China
- Department of NeurologyThe First Affiliated Hospital of Hainan Medical UniversityHaikouPeople's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical SciencesChengduPeople's Republic of China
- Department of NeurologyThe First Affiliated Hospital of Hainan Medical UniversityHaikouPeople's Republic of China
- Radiation Oncology Key Laboratory of Sichuan ProvinceSichuan Cancer HospitalChengduPeople's Republic of China
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21
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Wenzel J, Haas SS, Dwyer DB, Ruef A, Oeztuerk OF, Antonucci LA, von Saldern S, Bonivento C, Garzitto M, Ferro A, Paolini M, Blautzik J, Borgwardt S, Brambilla P, Meisenzahl E, Salokangas RKR, Upthegrove R, Wood SJ, Kambeitz J, Koutsouleris N, Kambeitz-Ilankovic L; PRONIA consortium. Cognitive subtypes in recent onset psychosis: distinct neurobiological fingerprints? Neuropsychopharmacology 2021; 46:1475-83. [PMID: 33723384 DOI: 10.1038/s41386-021-00963-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [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: 09/25/2020] [Revised: 12/16/2020] [Accepted: 01/05/2021] [Indexed: 01/31/2023]
Abstract
In schizophrenia, neurocognitive subtypes can be distinguished based on cognitive performance and they are associated with neuroanatomical alterations. We investigated the existence of cognitive subtypes in shortly medicated recent onset psychosis patients, their underlying gray matter volume patterns and clinical characteristics. We used a K-means algorithm to cluster 108 psychosis patients from the multi-site EU PRONIA (Prognostic tools for early psychosis management) study based on cognitive performance and validated the solution independently (N = 53). Cognitive subgroups and healthy controls (HC; n = 195) were classified based on gray matter volume (GMV) using Support Vector Machine classification. A cognitively spared (N = 67) and impaired (N = 41) subgroup were revealed and partially independently validated (Nspared = 40, Nimpaired = 13). Impaired patients showed significantly increased negative symptomatology (pfdr = 0.003), reduced cognitive performance (pfdr < 0.001) and general functioning (pfdr < 0.035) in comparison to spared patients. Neurocognitive deficits of the impaired subgroup persist in both discovery and validation sample across several domains, including verbal memory and processing speed. A GMV pattern (balanced accuracy = 60.1%, p = 0.01) separating impaired patients from HC revealed increases and decreases across several fronto-temporal-parietal brain areas, including basal ganglia and cerebellum. Cognitive and functional disturbances alongside brain morphological changes in the impaired subgroup are consistent with a neurodevelopmental origin of psychosis. Our findings emphasize the relevance of tailored intervention early in the course of psychosis for patients suffering from the likely stronger neurodevelopmental character of the disease.
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22
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Buonocore M, Inguscio E, Bosinelli F, Bechi M, Agostoni G, Spangaro M, Martini F, Bianchi L, Cocchi F, Guglielmino C, Repaci F, Bosia M, Cavallaro R. Disentangling Cognitive Heterogeneity in Psychotic Spectrum Disorders. Asian J Psychiatr 2021; 60:102651. [PMID: 33865160 DOI: 10.1016/j.ajp.2021.102651] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 03/25/2021] [Accepted: 04/05/2021] [Indexed: 11/18/2022]
Abstract
Neuropsychological impairments represent a central feature of psychosis-spectrum disorders. It is characterized by a great both within- and between-subjects variability (i.e. cognitive heterogeneity), which needs to be better disentangled. The present study aimed to describe the distribution of performance on the Brief Assessment of Cognition in Schizophrenia (BACS) by using the Equivalent Scores, in order to balance statistical methodological problems. To do so, cognitive performance groups were branded, identifying the main factors contributing to cognitive heterogeneity. A sample of 583 patients with a diagnosis of Schizophrenia or Psychotic Disorder Not Otherwise Specified was enrolled and assessed for neurocognition and intellectual level. K-means cluster analysis was performed based on BACS Equivalent Scores. Differences among clusters were analyzed throughout Analysis of Variance and Discriminant Function Analysis in order to identify the most significant predictors of cluster membership. For each cognitive task, roughly 40% of patients displayed poor performance, while up to 63% displayed a symbol-coding deficit. K-means cluster analysis depicted three profiles characterized by "near-normal" cognition, widespread impairment, and "borderline" profile. Discriminant analysis selected Verbal IQ and diagnosis as predictors of cluster membership. Our findings support the usefulness of Equivalent Scores and cluster analysis to explain cognitive heterogeneity, and tailor better interventions.
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Affiliation(s)
- Mariachiara Buonocore
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy.
| | - Emanuela Inguscio
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy
| | | | - Margherita Bechi
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giulia Agostoni
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Spangaro
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesca Martini
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Laura Bianchi
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Cocchi
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Carmelo Guglielmino
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Repaci
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy
| | - Marta Bosia
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberto Cavallaro
- Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
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North HF, Bruggemann J, Cropley V, Swaminathan V, Sundram S, Lenroot R, Pereira AM, Zalesky A, Bousman C, Pantelis C, Weickert TW, Shannon Weickert C. Increased peripheral inflammation in schizophrenia is associated with worse cognitive performance and related cortical thickness reductions. Eur Arch Psychiatry Clin Neurosci 2021; 271:595-607. [PMID: 33760971 DOI: 10.1007/s00406-021-01237-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [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: 10/11/2020] [Accepted: 02/03/2021] [Indexed: 12/16/2022]
Abstract
While the biological substrates of brain and behavioural changes in persons with schizophrenia remain unclear, increasing evidence implicates that inflammation is involved. In schizophrenia, including first-episode psychosis and anti-psychotic naïve patients, there are numerous reports of increased peripheral inflammation, cognitive deficits and neuropathologies such as cortical thinning. Research defining the relationship between inflammation and schizophrenia symptomatology and neuropathology is needed. Therefore, we analysed the level of C-reactive protein (CRP), a peripheral inflammation marker, and its relationship with cognitive functioning in a cohort of 644 controls and 499 schizophrenia patients. In a subset of individuals who underwent MRI scanning (99 controls and 194 schizophrenia cases), we tested if serum CRP was associated with cortical thickness. CRP was significantly increased in schizophrenia patients compared to controls, co-varying for age, sex, overweight/obesity and diabetes (p < 0.006E-10). In schizophrenia, increased CRP was mildly associated with worse performance in attention, controlling for age, sex and education (R =- 0.15, p = 0.001). Further, increased CRP was associated with reduced cortical thickness in three regions related to attention: the caudal middle frontal, the pars opercularis and the posterior cingulate cortices, which remained significant after controlling for multiple comparisons (all p < 0.05). Together, these findings indicate that increased peripheral inflammation is associated with deficits in cognitive function and brain structure in schizophrenia, especially reduced attention and reduced cortical thickness in associated brain regions. Using CRP as a biomarker of peripheral inflammation in persons with schizophrenia may help to identify vulnerable patients and those that may benefit from adjunctive anti-inflammatory treatments.
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Li S, Song J, Ke P, Kong L, Lei B, Zhou J, Huang Y, Li H, Li G, Chen J, Li X, Xiang Z, Ning Y, Wu F, Wu K. The gut microbiome is associated with brain structure and function in schizophrenia. Sci Rep 2021; 11:9743. [PMID: 33963227 DOI: 10.1038/s41598-021-89166-8] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 04/20/2021] [Indexed: 12/11/2022] Open
Abstract
The effect of the gut microbiome on the central nervous system and its possible role in mental disorders have received increasing attention. However, knowledge about the relationship between the gut microbiome and brain structure and function is still very limited. Here, we used 16S rRNA sequencing with structural magnetic resonance imaging (sMRI) and resting-state functional (rs-fMRI) to investigate differences in fecal microbiota between 38 patients with schizophrenia (SZ) and 38 demographically matched normal controls (NCs) and explored whether such differences were associated with brain structure and function. At the genus level, we found that the relative abundance of Ruminococcus and Roseburia was significantly lower, whereas the abundance of Veillonella was significantly higher in SZ patients than in NCs. Additionally, the analysis of MRI data revealed that several brain regions showed significantly lower gray matter volume (GMV) and regional homogeneity (ReHo) but significantly higher amplitude of low-frequency fluctuation in SZ patients than in NCs. Moreover, the alpha diversity of the gut microbiota showed a strong linear relationship with the values of both GMV and ReHo. In SZ patients, the ReHo indexes in the right STC (r = − 0.35, p = 0.031, FDR corrected p = 0.039), the left cuneus (r = − 0.33, p = 0.044, FDR corrected p = 0.053) and the right MTC (r = − 0.34, p = 0.03, FDR corrected p = 0.052) were negatively correlated with the abundance of the genus Roseburia. Our results suggest that the potential role of the gut microbiome in SZ is related to alterations in brain structure and function. This study provides insights into the underlying neuropathology of SZ.
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Schaeken W, Van de Weyer L, De Hert M, Wampers M. The Role of Working Memory in the Processing of Scalar Implicatures of Patients With Schizophrenia Spectrum and Other Psychotic Disorders. Front Psychol 2021; 12:635724. [PMID: 34025508 PMCID: PMC8134522 DOI: 10.3389/fpsyg.2021.635724] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [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: 11/30/2020] [Accepted: 04/06/2021] [Indexed: 01/29/2023] Open
Abstract
A number of studies have demonstrated pragmatic language difficulties in people with Schizophrenia Spectrum and Other Psychotic Disorders. However, research about how people with schizophrenia spectrum and other psychotic disorders understand scalar implicatures (SIs) is surprisingly rare, since SIs have generated much of the most recent literature. Scalar implicatures are pragmatic inferences, based on linguistic expressions like some, must, or, which are part of a scale of informativeness (e.g., some/many/all). Logically, the less informative expressions imply the more informative ones, but pragmatically people usually infer that the presence of a less informative term implies that the more informative term was not applicable. In one of the few existing studies with people with schizophrenia spectrum and other psychotic disorders, Wampers et al. (2018) observed that in general, people with schizophrenia spectrum and other psychotic disorders were less likely to derive SIs than controls. The current study has three main aims. First, we want to replicate the original finding with the scalar terms some-all. Second, we want to investigate how these patients deal with different scalar terms, that is, we want to investigate if scalar diversity is also observed in this clinical group. Third, we investigate the role of working memory, often seen as another important mechanism to enable inferring SIs. Twenty-one individuals with a psychotic disorder and 21 matched controls answered 54 under-informative statements, in which seven different pairs of scalar terms were used. In addition, working memory capacity was measured. Patients with schizophrenia spectrum and other psychotic disorders did not make more logical interpretations when processing quantifiers, disconfirming Wampers et al. (2018). However, certain scalar scales elicited more pragmatic interpretations than others, which is in line with the scalar diversity hypothesis. Additionally, we observed only partial evidence for the role of working memory. Only for the scalar scale and-or, a significant effect of working memory was observed. The implications of these results for patients with schizophrenia spectrum and other psychotic disorders are discussed, but also the role of working memory for pragmatic inferences, as well as the place of SIs in experimental pragmatics.
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Affiliation(s)
- Walter Schaeken
- Brain and Cognition, Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Linde Van de Weyer
- Brain and Cognition, Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Marc De Hert
- University Psychiatric Center KU Leuven, Leuven, Belgium.,Center for Clinical Psychiatry, Department of Neurosciences Antwerp Health Law and Ethics Chair, University of Antwerp, Antwerp, Belgium
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Karantonis JA, Rossell SL, Carruthers SP, Sumner P, Hughes M, Green MJ, Pantelis C, Burdick KE, Cropley V, Van Rheenen TE. Brain morphology does not clearly map to cognition in individuals on the bipolar-schizophrenia-spectrum: a cross-diagnostic study of cognitive subgroups. J Affect Disord 2021; 281:776-85. [PMID: 33246649 DOI: 10.1016/j.jad.2020.11.064] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [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: 06/14/2020] [Accepted: 11/08/2020] [Indexed: 01/11/2023]
Abstract
BACKGROUND Characterisation of brain morphological features common to cognitively similar individuals with bipolar disorder (BD) and schizophrenia spectrum disorders (SSD) may be key to understanding their shared neurobiological deficits. In the current study we examined whether three previously characterised cross-diagnostic cognitive subgroups differed among themselves and in comparison to healthy controls across measures of brain morphology. METHOD T1-weighted structural magnetic resonance imaging scans were obtained for 143 individuals; 65 healthy controls and 78 patients (SSD, n = 40; BD I, n = 38) classified into three cross-diagnostic cognitive subgroups: Globally Impaired (n = 24), Selectively Impaired (n = 32), and Superior/Near-Normal (n = 22). Cognitive subgroups were compared to each other and healthy controls on three separate analyses investigating (1) global, (2) regional, and (3) vertex-wise comparisons of brain volume, thickness, and surface area. RESULTS No significant subgroup differences were evident in global measures of brain morphology. In region of interest analyses, the Selectively Impaired subgroup had greater right accumbens volume than those Superior/Near-Normal subgroup and healthy controls, and the Superior/Near-Normal subgroup had reduced volume of the left entorhinal region compared to all other groups. In vertex-wise comparisons, the Globally Impaired subgroup had greater right precentral volume than the Selectively Impaired subgroup, and thicker cortex in the postcentral region relative to the Superior/Near-Normal subgroup. LIMITATIONS Exploration of medication effects was limited in our data. CONCLUSIONS Although some differences were evident in this sample, generally cross-diagnostic cognitive subgroups of individuals with SSD and BD did not appear to be clearly distinguished by patterns in brain morphology.
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Sun T, Zhao P, Jiang X, Zhou Y, Li C, Jia L, Tang Y. Distinct Associations of Cognitive Impairments and Reduced Gray Matter Volumes in Remitted Patients with Schizophrenia and Bipolar Disorder. Neural Plast 2020; 2020:8859388. [PMID: 33381163 DOI: 10.1155/2020/8859388] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 11/04/2020] [Accepted: 11/30/2020] [Indexed: 12/12/2022] Open
Abstract
Background Cognitive impairments are documented in schizophrenia (SZ) and bipolar disorder (BD) and may be related to gray matter volumes (GMVs). Thus, this study is aimed at exploring whether the association between cognitive impairments and GMV alterations is similar in patients with SZ and BD and understanding the underlying neurobiological mechanisms. Methods A total of 137 adult subjects (46 with SZ, 35 with BD, and 56 age-, sex-, and education-matched healthy controls (HC)) completed the MATRICS Consensus Cognitive Battery (MCCB) and structural magnetic resonance imaging scanning. We performed group comparisons of the cognitive impairments, the GMV alterations, and the association between them. Results Compared with HC, the patients with SZ and BD showed shared deficits in 4 cognitive domains (i.e., processing speed, working memory, problem solving, and social cognition) and the composite. SZ and BD had commonly decreased GMVs, mainly in the insula, superior temporal pole, amygdala, anterior cingulate, and frontal cortices (superior, middle, opercular inferior, and orbital frontal gyrus). No correlation between MCCB scores and GMVs was detected in SZ. However, for BD, working memory was relevant to the right hemisphere (i.e., right insula, amygdala, superior temporal pole, and medial and dorsolateral superior frontal gyrus). Limitations. The major limitations were that not all patients were the first-episode status and no medication. Conclusions The association was mainly limited to the BD group. Thus, the underlying pathophysiology of the cognitive deficits, in terms of GMV alterations, may be diverse between two disorders.
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Vaskinn A, Haatveit B, Melle I, Andreassen OA, Ueland T, Sundet K. Cognitive Heterogeneity across Schizophrenia and Bipolar Disorder: A Cluster Analysis of Intellectual Trajectories. J Int Neuropsychol Soc 2020; 26:860-72. [PMID: 32423506 DOI: 10.1017/S1355617720000442] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [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] [Indexed: 01/31/2023]
Abstract
OBJECTIVE Cognitive dysfunction cut across diagnostic categories and is present in both schizophrenia and bipolar disorder, although with considerable heterogeneity in both disorders. This study examined if distinct cognitive subgroups could be identified across schizophrenia and bipolar disorder based on the intellectual trajectory from the premorbid phase to after illness onset. METHOD Three hundred and ninety-eight individuals with schizophrenia (n = 223) or bipolar I disorder (n = 175) underwent clinical and neuropsychological assessment. Hierarchical and k-means cluster analyses using premorbid (National Adult Reading Test) and current IQ (Wechsler Abbreviated Scale of Intelligence) estimates were performed for each diagnostic category, and the whole sample collapsed. Resulting clusters were compared on neuropsychological, functional, and clinical variables. Healthy controls (n = 476) were included for analyses of neuropsychological performance. RESULTS Cluster analyses consistently yielded three clusters: a relatively intact group (36% of whole sample), an intermediate group with mild cognitive impairment (44%), and an impaired group with global deficits (20%). The clusters were validated by multinomial logistic regression and differed significantly for neuropsychological, functional, and clinical measures. The relatively intact group (32% of the schizophrenia sample and 42% of the bipolar sample) performed below healthy controls for speeded neuropsychological tests. CONCLUSIONS Three cognitive clusters were identified across schizophrenia and bipolar disorder using premorbid and current IQ estimates. Groups differed for clinical, functional, and neuropsychological variables, implying their meaningfulness. One-third of the schizophrenia sample belonged to the relatively intact group, highlighting that neuropsychological assessment is needed for the precise characterization of the individual.
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29
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Van Rheenen TE, Cropley V, Fagerlund B, Wannan C, Bruggemann J, Lenroot RK, Sundram S, Weickert CS, Weickert TW, Zalesky A, Bousman CA, Pantelis C. Cognitive reserve attenuates age-related cognitive decline in the context of putatively accelerated brain ageing in schizophrenia-spectrum disorders. Psychol Med 2020; 50:1475-1489. [PMID: 31274065 DOI: 10.1017/s0033291719001417] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [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: 01/01/2023]
Abstract
BACKGROUND In schizophrenia, relative stability in the magnitude of cognitive deficits across age and illness duration is inconsistent with the evidence of accelerated deterioration in brain regions known to support these functions. These discrepant brain-cognition outcomes may be explained by variability in cognitive reserve (CR), which in neurological disorders has been shown to buffer against brain pathology and minimize its impact on cognitive or clinical indicators of illness. METHODS Age-related change in fluid reasoning, working memory and frontal brain volume, area and thickness were mapped using regression analysis in 214 individuals with schizophrenia or schizoaffective disorder and 168 healthy controls. In patients, these changes were modelled as a function of CR. RESULTS Patients showed exaggerated age-related decline in brain structure, but not fluid reasoning compared to controls. In the patient group, no moderation of age-related brain structural change by CR was evident. However, age-related cognitive change was moderated by CR, such that only patients with low CR showed evidence of exaggerated fluid reasoning decline that paralleled the exaggerated age-related deterioration of underpinning brain structures seen in all patients. CONCLUSIONS In schizophrenia-spectrum illness, CR may negate ageing effects on fluid reasoning by buffering against pathologically exaggerated structural brain deterioration through some form of compensation. CR may represent an important modifier that could explain inconsistencies in brain structure - cognition outcomes in the extant literature.
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Affiliation(s)
- Tamsyn E Van Rheenen
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center, Glostrup, Denmark
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Cassandra Wannan
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Rhoshel K Lenroot
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Suresh Sundram
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, Australia
- Mental Health Program, Monash Health, Clayton, Victoria, Australia
| | - Cynthia Shannon Weickert
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
- Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, New York13210, USA
| | - Thomas W Weickert
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Andrew Zalesky
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia
| | - Chad A Bousman
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Christos Pantelis
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia
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Ho NF, Lee BJH, Tng JXJ, Lam MZY, Chen G, Wang M, Zhou J, Keefe RSE, Sim K. Corticolimbic brain anomalies are associated with cognitive subtypes in psychosis: A longitudinal study. Eur Psychiatry 2020; 63:e40. [PMID: 32336305 PMCID: PMC7355174 DOI: 10.1192/j.eurpsy.2020.36] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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] [Indexed: 12/31/2022] Open
Abstract
Background. Earlier studies examining structural brain abnormalities associated with cognitively derived subgroups were mainly cross-sectional in design and had mixed findings. Thus, we obtained cross-sectional and longitudinal data to characterize the extent and trajectory of brain structure abnormalities underlying distinct cognitive subtypes (“preserved,” “deteriorated,” and “compromised”) seen in psychotic spectrum disorders. Methods. Data from 364 subjects (225 patients with psychotic conditions and 139 healthy controls) were first used to determine the relationship of cognitive subtypes with cross-sectional measures of subcortical volume and cortical thickness. To probe neurodevelopmental abnormalities, brain structure laterality was examined. To examine whether neuroprogressive abnormalities persist, longitudinal brain structural changes over 5 years were examined within a subset of 101 subjects. Subsequent discriminant analysis using the identified brain measures was performed on an independent subject group. Results. Cross-sectional comparisons showed that cortical thinning and limbic volume reductions were most widespread in “deteriorated” cognitive subtype. Laterality comparisons showed more rightward amygdala lateralization in “compromised” than “preserved” subtype. Longitudinal comparisons revealed progressive hippocampal shrinkage in “deteriorated” compared with healthy controls and “preserved” subtype, which correlated with worse negative symptoms, cognitive and psychosocial functioning. Post-hoc discrimination analysis on an independent group of 52 subjects using the identified brain structures found an overall accuracy of 71% for classification of cognitive subtypes. Conclusion. These findings point toward distinct extent and trajectory of corticolimbic abnormalities associated with cognitive subtypes in psychosis, which can allow further understanding of the biological course of cognitive functioning over illness course and with treatment.
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Affiliation(s)
- New Fei Ho
- Institute of Mental Health, Singapore, Singapore.,Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Benjamin J H Lee
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | | | - Max Z Y Lam
- Institute of Mental Health, Singapore, Singapore
| | - Guoyang Chen
- Institute of Mental Health, Singapore, Singapore
| | | | - Juan Zhou
- Duke-National University of Singapore Medical School, Singapore, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Richard S E Keefe
- Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States of America
| | - Kang Sim
- Institute of Mental Health, Singapore, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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31
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Karantonis JA, Rossell SL, Carruthers SP, Sumner P, Hughes M, Green MJ, Pantelis C, Burdick KE, Cropley V, Van Rheenen TE. Cognitive validation of cross-diagnostic cognitive subgroups on the schizophrenia-bipolar spectrum. J Affect Disord 2020; 266:710-721. [PMID: 32056949 DOI: 10.1016/j.jad.2020.01.123] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [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: 10/05/2019] [Revised: 12/03/2019] [Accepted: 01/20/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs. METHOD Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline. RESULTS A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups. LIMITATIONS For clustering analysis, sample size was relatively small. CONCLUSIONS The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.
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Affiliation(s)
- James A Karantonis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; St Vincent's Mental Health, St Vincent's Hospital, VIC, Australia
| | - Sean P Carruthers
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Matthew Hughes
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Melissa J Green
- School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW, Australia; Neuroscience Research Australia, Randwick, NSW, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia; Centre for Neuropsychiatric Schizophrenia Research (CNSR) and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Centre Glostrup, Glostrup, Denmark
| | - Katherine E Burdick
- Harvard Medical School, Department of Psychiatry, Boston, MA, United States; Brigham and Women's Hospital, Boston, MA, United States
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia.
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32
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Affiliation(s)
- Kathryn E Lewandowski
- Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, Mass.; and Department of Psychiatry, Harvard Medical School, Boston
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33
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Pan Y, Pu W, Chen X, Huang X, Cai Y, Tao H, Xue Z, Mackinley M, Limongi R, Liu Z, Palaniyappan L. Morphological Profiling of Schizophrenia: Cluster Analysis of MRI-Based Cortical Thickness Data. Schizophr Bull 2020; 46:623-632. [PMID: 31901940 PMCID: PMC7147597 DOI: 10.1093/schbul/sbz112] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [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] [Indexed: 11/13/2022]
Abstract
The diagnosis of schizophrenia is thought to embrace several distinct subgroups. The manifold entities in a single clinical patient group increase the variance of biological measures, deflate the group-level estimates of causal factors, and mask the presence of treatment effects. However, reliable neurobiological boundaries to differentiate these subgroups remain elusive. Since cortical thinning is a well-established feature in schizophrenia, we investigated if individuals (patients and healthy controls) with similar patterns of regional cortical thickness form naturally occurring morphological subtypes. K-means algorithm clustering was applied to regional cortical thickness values obtained from 256 structural MRI scans (179 patients with schizophrenia and 77 healthy controls [HCs]). GAP statistics revealed three clusters with distinct regional thickness patterns. The specific patterns of cortical thinning, clinical characteristics, and cognitive function of each clustered subgroup were assessed. The three clusters based on thickness patterns comprised of a morphologically impoverished subgroup (25% patients, 1% HCs), an intermediate subgroup (47% patients, 46% HCs), and an intact subgroup (28% patients, 53% HCs). The differences of clinical features among three clusters pertained to age-of-onset, N-back performance, duration exposure to treatment, total burden of positive symptoms, and severity of delusions. Particularly, the morphologically impoverished group had deficits in N-back performance and less severe positive symptom burden. The data-driven neuroimaging approach illustrates the occurrence of morphologically separable subgroups in schizophrenia, with distinct clinical characteristics. We infer that the anatomical heterogeneity of schizophrenia arises from both pathological deviance and physiological variance. We advocate using MRI-guided stratification for clinical trials as well as case-control investigations in schizophrenia.
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Affiliation(s)
- Yunzhi Pan
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China,Robarts Research Institution, University of Western Ontario, London, Canada
| | - Weidan Pu
- Medical Psychological Institute, Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xudong Chen
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiaojun Huang
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Yan Cai
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China,The Second People’s Hospital of Hunan Province, Changsha, Hunan, PR China
| | - Haojuan Tao
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Zhiming Xue
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Michael Mackinley
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada
| | - Roberto Limongi
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada,Pontificia Universidad Católica de Valparaíso, Región de Valparaíso, Chile
| | - Zhening Liu
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China,To whom correspondence should be addressed; Mental Health Institute, Second Xiangya Hospital of Central South University, Changsha, 410011 PR China, e-mail:
| | - Lena Palaniyappan
- Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha, PR China,Medical Psychological Institute, Second Xiangya Hospital, Central South University, Changsha, PR China,Department of Psychiatry, University of Western Ontario, London, Ontario, Canada,Lawson Health Research Institute, London, Ontario, Canada
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Abstract
Psychotic disorders are severe, debilitating, and even fatal. The development of targeted and effective interventions for psychosis depends upon on clear understanding of the timing and nature of disease progression to target processes amenable to intervention. Strong evidence suggests early and ongoing neuroprogressive changes, but timing and inflection points remain unclear and likely differ across cognitive, clinical, and brain measures. Additionally, granular evidence across modalities is particularly sparse in the "bridging years" between first episode and established illness-years that may be especially critical for improving outcomes and during which interventions may be maximally effective. Our objective is the systematic, multimodal characterization of neuroprogression through the early course of illness in a cross-diagnostic sample of patients with psychosis. We aim to (1) interrogate neurocognition, structural brain measures, and network connectivity at multiple assessments over the first eight years of illness to map neuroprogressive trajectories, and (2) examine trajectories as predictors of clinical and functional outcomes. We will recruit 192 patients with psychosis and 36 healthy controls. Assessments will occur at baseline and 8- and 16-month follow ups using clinical, cognitive, and imaging measures. We will employ an accelerated longitudinal design (ALD), which permits ascertainment of data across a longer timeframe and at more frequent intervals than would be possible in a single cohort longitudinal study. Results from this study are expected to hasten identification of actionable treatment targets that are closely associated with clinical outcomes, and identify subgroups who share common neuroprogressive trajectories toward the development of individualized treatments.
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Van Rheenen TE, Lewandowski KE, Bauer IE, Kapczinski F, Miskowiak K, Burdick KE, Balanzá-Martínez V. Current understandings of the trajectory and emerging correlates of cognitive impairment in bipolar disorder: An overview of evidence. Bipolar Disord 2020; 22:13-27. [PMID: 31408230 DOI: 10.1111/bdi.12821] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [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] [Indexed: 12/21/2022]
Abstract
OBJECTIVES Cognitive dysfunction affects a significant proportion of people with bipolar disorder (BD), but the cause, trajectory and correlates of such dysfunction remains unclear. Increased understanding of these factors is required to progress treatment development for this symptom dimension. METHODS This paper provides a critical overview of the literature concerning the trajectories and emerging correlates of cognitive functioning in BD. It is a narrative review in which we provide a qualitative synthesis of current evidence concerning clinical, molecular, neural and lifestyle correlates of cognitive impairment in BD across the lifespan (in premorbid, prodromal, early onset, post-onset, elderly cohorts). RESULTS There is emerging evidence of empirical links between cognitive impairment and an increased inflammatory state, brain structural abnormalities and reduced neuroprotection in BD. However, evidence regarding the progressive nature of cognitive impairment is mixed, since consensus between different cross-sectional data is lacking and does not align to the outcomes of the limited longitudinal studies available. Increased recognition of cognitive heterogeneity in BD may help to explain some inconsistencies in the extant literature. CONCLUSIONS Large, longitudinally focussed studies of cognition and its covariation alongside biological and lifestyle factors are required to better define cognitive trajectories in BD, and eventually pave the way for the application of a precision medicine approach for individual patients in clinical practice.
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Affiliation(s)
- Tamsyn E Van Rheenen
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia.,Faculty of Health, Arts and Design, School of Health Sciences, Centre for Mental Health, Swinburne University, Melbourne, Australia
| | - Kathryn E Lewandowski
- Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA.,Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Isabelle E Bauer
- Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Flavio Kapczinski
- Department of Psychiatry and Behavioral Neurosciences, McMaster University Faculty of Health Sciences, Hamilton, ON, Canada.,Department of Psychiatry, Universidade Federal do Rio Grande do Sul, UFRGS, Porto Alegre, Brazil
| | - Kamilla Miskowiak
- Neurocognition and Emotion in Affective Disorders Group, Copenhagen Affective Disorder Research Centre, Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Katherine E Burdick
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.,Brigham and Women's Hospital, Boston, MA, USA.,James J Peters VA Medical Center, Bronx, NY, USA
| | - Vicent Balanzá-Martínez
- Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, CIBERSAM, Valencia, Spain
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Green MJ, Girshkin L, Kremerskothen K, Watkeys O, Quidé Y. A Systematic Review of Studies Reporting Data-Driven Cognitive Subtypes across the Psychosis Spectrum. Neuropsychol Rev 2020; 30:446-60. [PMID: 31853717 DOI: 10.1007/s11065-019-09422-7] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 12/02/2019] [Indexed: 10/25/2022]
Abstract
The delineation of cognitive subtypes of schizophrenia and bipolar disorder may offer a means of determining shared genetic markers and neuropathology among individuals with these conditions. We systematically reviewed the evidence from published studies reporting the use of data-driven (i.e., unsupervised) clustering methods to delineate cognitive subtypes among adults diagnosed with schizophrenia, schizoaffective disorder, or bipolar disorder. We reviewed 24 studies in total, contributing data to 13 analyses of schizophrenia spectrum patients, 8 analyses of bipolar disorder, and 5 analyses of mixed samples of schizophrenia and bipolar disorder participants. Studies of bipolar disorder most consistently revealed a 3-cluster solution, comprising a subgroup with 'near-normal' (cognitively spared) cognition and two other subgroups demonstrating graded deficits across cognitive domains. In contrast, there was no clear consensus regarding the number of cognitive subtypes among studies of cognitive subtypes in schizophrenia, while four of the five studies of mixed diagnostic groups reported a 4-cluster solution. Common to all cluster solutions was a severe cognitive deficit subtype with cognitive impairments of moderate to large effect size relative to healthy controls. Our review highlights several key factors (e.g., symptom profile, sample size, statistical procedures, and cognitive domains examined) that may influence the results of data-driven clustering methods, and which were largely inconsistent across the studies reviewed. This synthesis of findings suggests caution should be exercised when interpreting the utility of particular cognitive subtypes for biological investigation, and demonstrates much heterogeneity among studies using unsupervised clustering approaches to cognitive subtyping within and across the psychosis spectrum.
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Carruthers SP, Van Rheenen TE, Gurvich C, Sumner PJ, Rossell SL. Characterising the structure of cognitive heterogeneity in schizophrenia spectrum disorders. A systematic review and narrative synthesis. Neurosci Biobehav Rev 2019; 107:252-278. [PMID: 31505202 DOI: 10.1016/j.neubiorev.2019.09.006] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 08/19/2019] [Accepted: 09/02/2019] [Indexed: 12/13/2022]
Abstract
The aim of the present review was to systematically summarise our current understanding of the structure of the cognitive heterogeneity that exists within schizophrenia spectrum disorder (SSD). Fifty-two relevant studies were identified from January 1980 to March 2019 that investigated cognitive subgroups within SSD. Twenty-five studies employed classification criteria based on current neuropsychological function, 14 studies employed various data-driven subgrouping methodologies and 13 studies investigated putative cognitive symptom trajectories. Despite considerable methodological variability, three distinct cognitive subgroups reliability emerged; a relatively intact cognitive subgroup characterised by high cognitive performance, an intermediate cognitive subgroup defined by mixed or moderate levels of cognitive function/dysfunction and a globally impaired subgroup characterised by severe cognitive deficits. Whilst preliminary evidence suggests that these subgroups may have further investigative relevance in and of themselves, additional research is required and discussed. A set of reporting guidelines are also presented to overcome the methodological inconsistencies identified in the reviewed literature.
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Affiliation(s)
- Sean P Carruthers
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Victoria, 3122, Australia.
| | - Tamsyn E Van Rheenen
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Victoria, 3122, Australia; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, 3053, Australia
| | - Caroline Gurvich
- Monash Alfred Psychiatry Research Centre (MAPrc), Monash University Central Clinical School and The Alfred Hospital, Melbourne, 3004, Australia
| | - Philip J Sumner
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Victoria, 3122, Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, Swinburne University of Technology, Victoria, 3122, Australia; St Vincent's Hospital, Melbourne, Victoria, 3065, Australia
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Carruthers SP, Gurvich CT, Meyer D, Bousman C, Everall IP, Neill E, Pantelis C, Sumner PJ, Tan EJ, Thomas EHX, Van Rheenen TE, Rossell SL; Australian Schizophrenia Research Bank. Exploring Heterogeneity on the Wisconsin Card Sorting Test in Schizophrenia Spectrum Disorders: A Cluster Analytical Investigation. J Int Neuropsychol Soc 2019; 25:750-60. [PMID: 31104647 DOI: 10.1017/S1355617719000420] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [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] [Indexed: 12/17/2022]
Abstract
OBJECTIVES The Wisconsin Card Sorting Test (WCST) is a complex measure of executive function that is frequently employed to investigate the schizophrenia spectrum. The successful completion of the task requires the interaction of multiple intact executive processes, including attention, inhibition, cognitive flexibility, and concept formation. Considerable cognitive heterogeneity exists among the schizophrenia spectrum population, with substantive evidence to support the existence of distinct cognitive phenotypes. The within-group performance heterogeneity of individuals with schizophrenia spectrum disorder (SSD) on the WCST has yet to be investigated. A data-driven cluster analysis was performed to characterise WCST performance heterogeneity. METHODS Hierarchical cluster analysis with k-means optimisation was employed to identify homogenous subgroups in a sample of 210 schizophrenia spectrum participants. Emergent clusters were then compared to each other and a group of 194 healthy controls (HC) on WCST performance and demographic/clinical variables. RESULTS Three clusters emerged and were validated via altered design iterations. Clusters were deemed to reflect a relatively intact patient subgroup, a moderately impaired patient subgroup, and a severely impaired patient subgroup. CONCLUSIONS Considerable within-group heterogeneity exists on the WCST. Identification of subgroups of patients who exhibit homogenous performance on measures of executive functioning may assist in optimising cognitive interventions. Previous associations found using the WCST among schizophrenia spectrum participants should be reappraised. (JINS, 2019, 25, 750-760).
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Lewandowski KE, McCarthy JM, Öngür D, Norris LA, Liu GZ, Juelich RJ, Baker JT. Functional connectivity in distinct cognitive subtypes in psychosis. Schizophr Res 2019; 204:120-126. [PMID: 30126818 PMCID: PMC6378132 DOI: 10.1016/j.schres.2018.08.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [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: 02/26/2018] [Revised: 07/20/2018] [Accepted: 08/11/2018] [Indexed: 02/02/2023]
Abstract
BACKGROUND Cognitive dysfunction is common in psychotic disorders, and may reflect underlying pathophysiology. However, substantial cognitive heterogeneity exists both within and between diagnostic categories, creating challenges for studying the neurobiology of cognitive dysfunction in patients. The aim of this study was to identify patients with psychosis with intact versus impaired cognitive profiles, and to examine resting state functional connectivity between patient groups and compared to healthy controls to determine the extent to which patterns of connectivity are overlapping or distinct. METHODS Participants with affective or non-affective psychosis (n=120) and healthy controls (n=31) were administered the MATRICS Consensus Cognitive Battery, clinical and community functioning assessments, and an fMRI scan to measure resting state functional connectivity (RSFC). Cognitive composite scores were used to identify groups of patients with and without cognitive dysfunction. RSFC was compared between groups of patients and healthy controls, controlling for demographic and clinical variables. RESULTS Both cognitively intact and cognitively impaired patients showed decreased intrinsic connectivity compared to controls in frontoparietal control (FPN) and motor networks. Patients with cognitive impairment showed additional reductions in FPN connectivity compared to patients with intact cognition, particularly in subnetwork A. CONCLUSIONS We leveraged the heterogeneity in cognitive ability among patients with psychosis to disentangle the relative contributions of cognitive dysfunction and presence of an underlying psychotic illness using resting state functional connectivity. These findings suggest at least partially separable effects of presence of a psychotic disorder and neurocognitive impairment contributing to network dysconnectivity in psychosis.
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Affiliation(s)
- Kathryn E. Lewandowski
- McLean Hospital, Schizophrenia and Bipolar Disorder Program,Harvard Medical School, Department of Psychiatry
| | - Julie M. McCarthy
- McLean Hospital, Schizophrenia and Bipolar Disorder Program,Harvard Medical School, Department of Psychiatry
| | - Dost Öngür
- McLean Hospital, Schizophrenia and Bipolar Disorder Program,Harvard Medical School, Department of Psychiatry
| | | | - Geoffrey Z. Liu
- McLean Hospital, Schizophrenia and Bipolar Disorder Program,Massachusetts General Hospital, Department of Psychiatry
| | | | - Justin T. Baker
- McLean Hospital, Schizophrenia and Bipolar Disorder Program,Harvard Medical School, Department of Psychiatry
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40
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Mostaid MS, Dimitrakopoulos S, Wannan C, Cropley V, Weickert CS, Everall IP, Pantelis C, Bousman CA. An Interleukin-1 beta (IL1B) haplotype linked with psychosis transition is associated with IL1B gene expression and brain structure. Schizophr Res 2019; 204:201-205. [PMID: 30220520 DOI: 10.1016/j.schres.2018.09.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [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: 03/05/2018] [Revised: 07/09/2018] [Accepted: 09/09/2018] [Indexed: 10/28/2022]
Abstract
We investigated IL1B genetic variation previously associated with risk for transition to psychosis for its association with gene expression in human post-mortem dorsolateral prefrontal cortex (DLPFC) from 74 (37 schizophrenia, 37 control) individuals and brain structure in 92 (44 schizophrenia, 48 control) living individuals. The IL1B A-G-T 'risk for psychosis transition' haplotype (rs16944|rs4848306|rs12621220) was associated with upregulation of IL1B mRNA expression in the DLPFC as well as reduced total grey matter and left middle frontal volumes and enlarged left lateral ventricular volume. Our results suggest IL1B genetic variation may confer psychosis risk via elevated mRNA expression and/or brain structure abnormalities.
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Affiliation(s)
- Md Shaki Mostaid
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia; The Cooperative Research Centre (CRC) for Mental Health, VIC, Australia
| | - Stefanos Dimitrakopoulos
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia; The Cooperative Research Centre (CRC) for Mental Health, VIC, Australia; 1st Department of Psychiatry, Athens University Medical School, Eginition Hospital, Athens, Greece
| | - Cassandra Wannan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia; The Cooperative Research Centre (CRC) for Mental Health, VIC, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia
| | - Cynthia Shannon Weickert
- Schizophrenia Research Laboratory, Neuroscience Research Australia, Barker Street, Sydney, Australia; School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia; Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, New York 13210, USA
| | - Ian P Everall
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia; The Cooperative Research Centre (CRC) for Mental Health, VIC, Australia; Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia; Centre for Neural Engineering, The University of Melbourne, Carlton, VIC, Australia; NorthWestern Mental Health, Melbourne, Victoria, Australia; Institute of Psychiatry, Psychology, and Neuroscience, King's College London, UK
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia; The Cooperative Research Centre (CRC) for Mental Health, VIC, Australia; Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia; Centre for Neural Engineering, The University of Melbourne, Carlton, VIC, Australia; NorthWestern Mental Health, Melbourne, Victoria, Australia
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia; The Cooperative Research Centre (CRC) for Mental Health, VIC, Australia; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Departments of Medical Genetics, Psychiatry, and Physiology and Pharmacology, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada.
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Alameda L, Fournier M, Khadimallah I, Griffa A, Cleusix M, Jenni R, Ferrari C, Klauser P, Baumann PS, Cuenod M, Hagmann P, Conus P, Do KQ. Redox dysregulation as a link between childhood trauma and psychopathological and neurocognitive profile in patients with early psychosis. Proc Natl Acad Sci U S A 2018; 115:12495-500. [PMID: 30455310 DOI: 10.1073/pnas.1812821115] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Early traumatic experiences interact with redox regulation and oxidative stress. Blood glutathione peroxidase (GPx) activity, involved in reducing peroxides, may reflect the oxidation status of the organism, thus allowing for the stratification of patients. Traumatized patients with psychosis who have a high blood oxidation status (high-GPx) have smaller hippocampal volumes (but not a smaller amygdala or intracranial volume), and this is associated with more severe clinical symptoms, while those with a lower oxidation status (low-GPx) showed better cognition and a correlated activation of the antioxidant thioredoxin/peroxiredoxin system. Thus, in patients with psychosis, traumatic experiences during childhood may interact with various redox systems, leading to long-term neuroanatomical and clinical defects. This redox profile may represent important biomarkers for patient stratification, defining treatment strategies at early stages of psychosis. Exposure to childhood trauma (CT) increases the risk for psychosis and affects the development of brain structures, possibly through oxidative stress. As oxidative stress is also linked to psychosis, it may interact with CT, leading to a more severe clinical phenotype. In 133 patients with early psychosis (EPP), we explored the relationships between CT and hippocampal, amygdala, and intracranial volume (ICV); blood antioxidant defenses [glutathione peroxidase (GPx) and thioredoxin/peroxiredoxin (Trx/Prx)]; psychopathological results; and neuropsychological results. Nonadjusted hippocampal volume correlated negatively with GPx activity in patients with CT, but not in patients without CT. In patients with CT with high GPx activity (high-GPx+CT), hippocampal volume was decreased compared with that in patients with low-GPx+CT and patients without CT, who had similar hippocampal volumes. Patients with high-GPx+CT had more severe positive and disorganized symptoms than other patients. Interestingly, Trx and oxidized Prx levels correlated negatively with GPx only in patients with low-GPx+CT. Moreover, patients with low-GPx+CT performed better than other patients on cognitive tasks. Discriminant analysis combining redox markers, hippocampal volume, clinical scores, and cognitive scores allowed for stratification of the patients into subgroups. In conclusion, traumatized EPP with high peripheral oxidation status (high-GPx activity) had smaller hippocampal volumes and more severe symptoms, while those with lower oxidation status (low-GPx activity) showed better cognition and regulation of GPx and Trx/Prx systems. These results suggest that maintained regulation of various antioxidant systems allowed for compensatory mechanisms preventing long-term neuroanatomical and clinical impacts. The redox marker profile may thus represent important biomarkers for defining treatment strategies in patients with psychosis.
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Jessen K, Mandl RCW, Fagerlund B, Bojesen KB, Raghava JM, Obaid HG, Jensen MB, Johansen LB, Nielsen MØ, Pantelis C, Rostrup E, Glenthøj BY, Ebdrup BH. Patterns of Cortical Structures and Cognition in Antipsychotic-Naïve Patients With First-Episode Schizophrenia: A Partial Least Squares Correlation Analysis. Biol Psychiatry Cogn Neurosci Neuroimaging 2018; 4:444-453. [PMID: 30420252 DOI: 10.1016/j.bpsc.2018.09.006] [Citation(s) in RCA: 4] [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] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 08/09/2018] [Accepted: 09/01/2018] [Indexed: 12/26/2022]
Abstract
BACKGROUND Schizophrenia is associated with alterations in cortical structures and cognitive impairments, but antipsychotic medication may affect these measures. We investigated patterns of relationships between cortical structures and cognitive domains in antipsychotic-naïve patients with first-episode schizophrenia. METHODS T1-weighted 3T magnetic resonance imaging was performed in 105 patients and 136 healthy control subjects. Using FreeSurfer, we obtained measurements of cortical thickness, surface area, and mean curvature. Using an extensive neurocognitive battery including the Danish Adult Reading Test and subtests from the Cambridge Neuropsychological Test Automated Battery, we obtained estimates of premorbid intelligence, spatial working memory, spatial planning, intra-extradimensional set shifting, and reaction and movement times. With univariate analyses, we tested group differences between cortical structures and cognition. With partial least squares correlation analyses, we investigated patterns of associations between cortical structures and cognition. RESULTS Patients had significantly higher mean curvature and were impaired on 7 of 11 cognitive parameters. The between-group partial least squares correlation analysis revealed two cortical thickness/cognition patterns that differentiated patients and healthy control subjects (omnibus test, p = .011). Most cortical regions contributed reliably to these patterns. In patients, spatial working memory, spatial planning, reaction and movement times, and premorbid intelligence contributed reliably to the pattern; in healthy control subjects, spatial planning and intra-extradimensional set shifting contributed reliably. CONCLUSIONS Antipsychotic-naïve patients with first-episode schizophrenia displayed a higher mean curvature, but no significant difference in other gray matter indices was found. Nevertheless, the pattern of associations between global cortical thickness and cognitive functions was markedly different between groups. These multivariate analyses reveal a novel linkage between regional cortical brain structure and cognitive deficits at the earliest, never-medicated illness stage.
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Affiliation(s)
- Kasper Jessen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Rene C W Mandl
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Kirsten B Bojesen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jayachandra M Raghava
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet-Glostrup, Glostrup, Denmark
| | - Hayder G Obaid
- Department of Radiology, Copenhagen University Hospital Herlev Gentofte, Herlev, Denmark
| | - Marie B Jensen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Louise B Johansen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Hvidovre, Denmark
| | - Mette Ø Nielsen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christos Pantelis
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Birte Y Glenthøj
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bjørn H Ebdrup
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Silverstein SM, Demmin DL, Bednar JA. Computational Modeling of Contrast Sensitivity and Orientation Tuning in First-Episode and Chronic Schizophrenia. Comput Psychiatr 2017; 1:102-131. [PMID: 30090855 PMCID: PMC6067832 DOI: 10.1162/cpsy_a_00005] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 05/16/2017] [Indexed: 12/11/2022]
Abstract
Computational modeling is a useful method for generating hypotheses about the contributions of impaired neurobiological mechanisms, and their interactions, to psychopathology. Modeling is being increasingly used to further our understanding of schizophrenia, but to date, it has not been applied to questions regarding the common perceptual disturbances in the disorder. In this article, we model aspects of low-level visual processing and demonstrate how this can lead to testable hypotheses about both the nature of visual abnormalities in schizophrenia and the relationships between the mechanisms underlying these disturbances and psychotic symptoms. Using a model that incorporates retinal, lateral geniculate nucleus (LGN), and V1 activity, as well as gain control in the LGN, homeostatic adaptation in V1, lateral excitation and inhibition in V1, and self-organization of synaptic weights based on Hebbian learning and divisive normalization, we show that (a) prior data indicating increased contrast sensitivity for low-spatial-frequency stimuli in first-episode schizophrenia can be successfully modeled as a function of reduced retinal and LGN efferent activity, leading to overamplification at the cortical level, and (b) prior data on reduced contrast sensitivity and broadened orientation tuning in chronic schizophrenia can be successfully modeled by a combination of reduced V1 lateral inhibition and an increase in the Hebbian learning rate at V1 synapses for LGN input. These models are consistent with many current findings, and they predict several relationships that have not yet been demonstrated. They also have implications for understanding changes in brain and visual function from the first psychotic episode to the chronic stage of illness.
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Affiliation(s)
- Steven M. Silverstein
- Rutgers University Behavioral Health Care, Piscataway, New Jersey, USA
- Robert Wood Johnson Medical School Department of Psychiatry, Rutgers University, Piscataway, New Jersey, USA
| | - Docia L. Demmin
- Rutgers University Behavioral Health Care, Piscataway, New Jersey, USA
- Department of Psychology, Rutgers University, Piscataway, New Jersey, USA
| | - James A. Bednar
- School of Informatics, University of Edinburgh, Edinburgh, Scotland
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