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Valizadeh A, Mbwogge M, Rasouli Yazdi A, Hedayati Amlashi N, Haadi A, Shayestefar M, Moassefi M. The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis. Front Psychiatry 2022; 13:884828. [PMID: 36213922 PMCID: PMC9532849 DOI: 10.3389/fpsyt.2022.884828] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 08/16/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Mirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients. METHODS We included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual. RESULTS We included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect. DISCUSSION This finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism. SYSTEMATIC REVIEW REGISTRATION PROSPERO identifier: CRD42021236453.
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Affiliation(s)
- Amir Valizadeh
- Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | | | | | - Ainaaz Haadi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Monir Shayestefar
- Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mana Moassefi
- Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
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Reis-de-Oliveira G, Smith BJ, Martins-de-Souza D. Postmortem Brains: What Can Proteomics Tell us About the Sources of Schizophrenia? ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1400:1-13. [DOI: 10.1007/978-3-030-97182-3_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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53
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Stȩpień-Wyrobiec O, Nowak M, Wyrobiec G, Morawiec E, Wierzbik-Strońska M, Staszkiewicz R, Grabarek BO. Crossroad between current knowledge and new perspective of diagnostic and therapy of late-onset schizophrenia and very late-onset schizophrenia-like psychosis: An update. Front Psychiatry 2022; 13:1025414. [PMID: 36387009 PMCID: PMC9643586 DOI: 10.3389/fpsyt.2022.1025414] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 10/11/2022] [Indexed: 11/23/2022] Open
Abstract
Schizophrenia is a chronic, highly individualized disease with many symptoms that can occur with varying severity in different patients. Schizophrenia affects 1% of the population, but occurs in almost 20% of patients after 40 years of age. It should be noted that the next peak in the incidence of schizophrenia occurs at the age of 60 years, affects mostly females, and is closely associated with a high risk of developing memory disorders. Therefore, postadolescent schizophrenia includes two distinct groups of patients: those whose symptoms onset at the age of 45 or 60. The purposes of this literature review were as follows: (1) synthetically characterize the clinical manifestations of schizophrenia; (2) discuss difficulties in the diagnosis of schizophrenia, especially in patients over 40 years of age; (3) discuss the clinical utility of different classes of marker in diagnostic and differentiating schizophrenia from neurodegenerative diseases in elderly people; (4) discuss therapeutic options for schizophrenia, pharmacotherapy, and psychotherapy, emphasizing the role of caregivers of people with psychosis in therapy, in preadolescence and postadolescence schizophrenia. We have tried to primarily discuss the findings of original articles from the last 10 years with an indication of their clinical implications with the issues discussed in the various subsections. Moreover, despite many years of research, no specific, precise algorithm has been developed that can be used in clinical practice during the diagnosis of schizophrenia. For this reason, the diagnosis of schizophrenia is primarily based on an interview with the patient and his family, as well as on the experience of a psychiatrist. It also seems that schizophrenia treatment should be carried out holistically, including pharmacotherapy, psychotherapy, and the support of caregivers of patients who have this psychosis, which increases the achievement of therapeutic success. Finally, we must be aware of the difficulties in diagnosing schizophrenia in the elderly and the need to modify pharmacological treatment. Currently, no guidelines have been developed for the differentiation of negative symptoms in elderly patients with schizophrenia from amotivation/avolition/apathy symptoms in elderly patients with neurodegenerative disorders.
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Affiliation(s)
- Olga Stȩpień-Wyrobiec
- Department of Geriatrics, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, Zabrze, Poland.,EMC Hospitals, John Paul II Geriatric Hospital in Katowice, Katowice, Poland
| | - Marta Nowak
- Department of Histology and Cell Pathology, Faculty of Medicine in Zabrze, Medical University of Silesia in Katowice, Zabrze, Poland
| | - Grzegorz Wyrobiec
- Department of Histology and Cell Pathology, Faculty of Medicine in Zabrze, Medical University of Silesia in Katowice, Zabrze, Poland
| | - Emilia Morawiec
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, University of Technology, Zabrze, Poland.,Department of Microbiology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, Zabrze, Poland.,Gyncentrum, Laboratory of Molecular Biology and Virology, Katowice, Poland
| | | | - Rafał Staszkiewicz
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, University of Technology, Zabrze, Poland.,5th Military Clinical Hospital with Polyclinic - Independent Public Health Care Facility in Krakow, Kraków, Poland
| | - Beniamin Oskar Grabarek
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, University of Technology, Zabrze, Poland.,Gyncentrum, Laboratory of Molecular Biology and Virology, Katowice, Poland.,Department of Gynecology and Obstetrics, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, Zabrze, Poland
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54
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Joo SW, Kim H, Jo YT, Ahn S, Choi YJ, Park S, Kang Y, Lee J. White matter impairments in patients with schizophrenia: A multisite diffusion MRI study. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110381. [PMID: 34111494 DOI: 10.1016/j.pnpbp.2021.110381] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 05/31/2021] [Accepted: 06/04/2021] [Indexed: 10/21/2022]
Abstract
There is a lack of convincing and replicative findings regarding white matter abnormalities in schizophrenia. Several multisite diffusion magnetic resonance imaging (dMRI) studies have been conducted to increase statistical power and reveal subtle white matter changes. Data pooling methods are crucial in joint analysis to compensate for the use of different scanners and image acquisition parameters. A harmonization method using raw dMRI data was developed to overcome the limited generalizability of previous data pooling methods. We obtained dMRI data of 242 healthy controls and 190 patients with schizophrenia from four different study sites. After applying the harmonization method to the raw dMRI data, a two-tensor whole-brain tractography was performed, and diffusion measures were compared between the two groups. The correlation of fractional anisotropy (FA) with the positive and negative symptoms was evaluated, and the interaction effect of diagnosis-by-age, age-squared, and sex was examined. The following white matter tracts showed significant group differences in the FA: the right superior longitudinal fascicle (SLF), the left-to-right lateral orbitofrontal commissural tract, pars orbitalis (pOr-pOr) commissural tract, and pars triangularis (pTr-pTr) commissural tract. The FA of the right SLF and pTr-pTr commissural tract were significantly associated with the Positive and Negative Syndrome Scale (PANSS) positive and negative scores. No significant interaction effect was observed. These findings add to the evidence on structural brain abnormalities in schizophrenia and can aid in obtaining a better understanding of the biological foundations of schizophrenia.
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Affiliation(s)
- Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Harin Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Soojin Ahn
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Jae Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Soyeon Park
- Department of Psychiatry, Medical Foundation Yongin Mental Hospital, Yongin, Republic of Korea
| | - Yuree Kang
- Department of Psychiatry, Medical Foundation Yongin Mental Hospital, Yongin, Republic of Korea
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
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55
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Yang B, Zhang W, Lencer R, Tao B, Tang B, Yang J, Li S, Zeng J, Cao H, Sweeney JA, Gong Q, Lui S. Grey matter connectome abnormalities and age-related effects in antipsychotic-naive schizophrenia. EBioMedicine 2021; 74:103749. [PMID: 34906839 PMCID: PMC8671864 DOI: 10.1016/j.ebiom.2021.103749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/12/2021] [Accepted: 11/29/2021] [Indexed: 02/05/2023] Open
Abstract
Background Convergent evidence is increasing to indicate progressive brain abnormalities in schizophrenia. Knowing the brain network features over the illness course in schizophrenia, independent of effects of antipsychotic medications, would extend our sight on this question. Methods We recruited 237 antipsychotic-naive patients with schizophrenia range from 16 to 73 years old, and 254 healthy controls. High-resolution T1 weighted images were obtained with a 3.0T MR scanner. Grey matter networks were constructed individually based on the similarities of regional grey matter measurements. Network metrics were compared between patient groups and healthy controls, and regression analyses with age were conducted to determine potential differential rate of age-related changes between them. Findings Nodal centrality abnormalities were observed in patients with untreated schizophrenia, particularly in the central executive, default mode and salience networks. Accelerated age-related declines and illness duration-related declines were observed in global assortativity, and in nodal metrics of left superior temporal pole in schizophrenia patients. Although no significant intergroup differences in age-related regression were observed, the pattern of network metric alternation of left thalamus indicated higher nodal properties in early course patients, which decreased in long-term ill patients. Interpretations Global and nodal alterations in the grey matter connectome related to age and duration of illness in antipsychotic-naive patients, indicating potentially progressive network organizations mainly involving temporal regions and thalamus in schizophrenia independent from medication effects. Funding The National Natural Science Foundation of China, Sichuan Science and Technology Program, the Fundamental Research Funds for the Central Universities, Post-Doctor Research Project, West China Hospital, Sichuan University , the Science and Technology Project of the Health Planning Committee of Sichuan, Postdoctoral Interdisciplinary Research Project of Sichuan University and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.
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Affiliation(s)
- Beisheng Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Muenster, Germany
| | - Bo Tao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Biqiu Tang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jing Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Siyi Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jiaxin Zeng
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Hengyi Cao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, United States
| | - John A Sweeney
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
| | - Su Lui
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
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56
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Di Biase MA, Cetin-Karayumak S, Lyall AE, Zalesky A, Cho KIK, Zhang F, Kubicki M, Rathi Y, Lyons MG, Bouix S, Billah T, Anticevic A, Schleifer C, Adkinson BD, Ji JL, Tamayo Z, Addington J, Bearden CE, Cornblatt BA, Keshavan MS, Mathalon DH, McGlashan TH, Perkins DO, Cadenhead KS, Tsuang MT, Woods SW, Stone WS, Shenton ME, Cannon TD, Pasternak O. White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis. Mol Psychiatry 2021; 26:6833-6844. [PMID: 34024906 PMCID: PMC8611104 DOI: 10.1038/s41380-021-01128-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 04/14/2021] [Indexed: 02/04/2023]
Abstract
Subtle alterations in white matter microstructure are observed in youth at clinical high risk (CHR) for psychosis. However, the timing of these changes and their relationships to the emergence of psychosis remain unclear. Here, we track the evolution of white matter abnormalities in a large, longitudinal cohort of CHR individuals comprising the North American Prodrome Longitudinal Study (NAPLS-3). Multi-shell diffusion magnetic resonance imaging data were collected across multiple timepoints (1-5 over 1 year) in 286 subjects (aged 12-32 years): 25 CHR individuals who transitioned to psychosis (CHR-P; 61 scans), 205 CHR subjects with unknown transition outcome after the 1-year follow-up period (CHR-U; 596 scans), and 56 healthy controls (195 scans). Linear mixed effects models were fitted to infer the impact of age and illness-onset on variation in the fractional anisotropy of cellular tissue (FAT) and the volume fraction of extracellular free water (FW). Baseline measures of white matter microstructure did not differentiate between HC, CHR-U and CHR-P individuals. However, age trajectories differed between the three groups in line with a developmental effect: CHR-P and CHR-U groups displayed higher FAT in adolescence, and 4% lower FAT by 30 years of age compared to controls. Furthermore, older CHR-P subjects (20+ years) displayed 4% higher FW in the forceps major (p < 0.05). Prospective analysis in CHR-P did not reveal a significant impact of illness onset on regional FAT or FW, suggesting that transition to psychosis is not marked by dramatic change in white matter microstructure. Instead, clinical high risk for psychosis-regardless of transition outcome-is characterized by subtle age-related white matter changes that occur in tandem with development.
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Affiliation(s)
- Maria A Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Kang Ik Kevin Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Monica G Lyons
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tashrif Billah
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alan Anticevic
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | | | - Brendan D Adkinson
- Yale Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
| | - Jie Lisa Ji
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Zailyn Tamayo
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Jean Addington
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior and Department of Psychology, University of California-Los Angeles, Los Angeles, CA, USA
| | - Barbara A Cornblatt
- Department of Psychiatry and Psychology, The Feinstein Institute for Medical Research, Manhasset, NY, USA
- Department of Psychology, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
- The Zucker Hillside Hospital, New York, NY, USA
| | - Matcheri S Keshavan
- Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniel H Mathalon
- University of California, San Francisco, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Thomas H McGlashan
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Diana O Perkins
- Department of Psychology, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
- University of North Carolina (UNC), Chapel Hill, NC, USA
| | - Kristen S Cadenhead
- Department of Psychiatry, University of California San Diego (UCSD), La Jolla, CA, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego (UCSD), La Jolla, CA, USA
| | - Scott W Woods
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - William S Stone
- Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tyrone D Cannon
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Bohaterewicz B, Sobczak AM, Krześniak A, Mętel D, Adamczyk P. On the relation of gyrification and cortical thickness alterations to the suicidal risk and mental pain in chronic schizophrenia outpatients. Psychiatry Res Neuroimaging 2021; 316:111343. [PMID: 34399285 DOI: 10.1016/j.pscychresns.2021.111343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 05/28/2021] [Accepted: 06/10/2021] [Indexed: 11/21/2022]
Affiliation(s)
- Bartosz Bohaterewicz
- Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Krakow, Poland; Department of Psychology of Individual Differences, Psychological Diagnosis, and Psychometrics, Institute of Psychology, University of Social Sciences and Humanities, Warsaw, Poland.
| | - Anna Maria Sobczak
- Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Krakow, Poland
| | - Alicja Krześniak
- Institute of Psychology, Jagiellonian University, Krakow, Poland; Laboratory of Brain Imaging, Nencki Institute of Experimental Biology, Warsaw, Poland
| | - Dagmara Mętel
- Department of Community Psychiatry, Chair of Psychiatry, Medical College, Jagiellonian University, Krakow, Poland
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Xiao Y, Liao W, Long Z, Tao B, Zhao Q, Luo C, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, Gershon ES, Ivleva EI, Keedy SK, Biswal BB, Mechelli A, Lencer R, Sweeney JA, Lui S, Gong Q. Subtyping Schizophrenia Patients Based on Patterns of Structural Brain Alterations. Schizophr Bull 2021; 48:241-250. [PMID: 34508358 PMCID: PMC8781382 DOI: 10.1093/schbul/sbab110] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a complex and heterogeneous syndrome. Whether quantitative imaging biomarkers can identify discrete subgroups of patients as might be used to foster personalized medicine approaches for patient care remains unclear. Cross-sectional structural MR images of 163 never-treated first-episode schizophrenia patients (FES) and 133 chronically ill patients with midcourse schizophrenia from the Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium and a total of 403 healthy controls were recruited. Morphometric measures (cortical thickness, surface area, and subcortical structures) were extracted for each subject and then the optimized subtyping results were obtained with nonsupervised cluster analysis. Three subgroups of patients defined by distinct patterns of regional cortical and subcortical morphometric features were identified in FES. A similar three subgroup pattern was identified in the independent dataset of patients from the multi-site B-SNIP consortium. Similarities of classification patterns across these two patient cohorts suggest that the 3-group typology is relatively stable over the course of illness. Cognitive functions were worse in subgroup 1 with midcourse schizophrenia than those in subgroup 3. These findings provide novel insight into distinct subgroups of patients with schizophrenia based on structural brain features. Findings of different cognitive functions among the subgroups support clinical differences in the MRI-defined illness subtypes. Regardless of clinical presentation and stage of illness, anatomic MR subgrouping biomarkers can separate neurobiologically distinct subgroups of schizophrenia patients, which represent an important and meaningful step forward in differentiating subtypes of patients for studies of illness neurobiology and potentially for clinical trials.
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Affiliation(s)
- Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry, University of Münster, Münster, Germany
| | - Wei Liao
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Zhiliang Long
- Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, Sichuan, China
| | - Bo Tao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiannan Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Chunyan Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, 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
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL, USA
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Rebekka Lencer
- Department of Psychiatry, University of Münster, Münster, Germany
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China,To whom correspondence should be addressed; #37 GuoXue Xiang, Chengdu 610041, China; Tel: 86-28-85423960, Fax: 86-28-85423503; e-mail:
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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Uranova NA, Vikhreva OV, Rakhmanova VI. Abnormal microglial reactivity in gray matter of the prefrontal cortex in schizophrenia. Asian J Psychiatr 2021; 63:102752. [PMID: 34274629 DOI: 10.1016/j.ajp.2021.102752] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 07/02/2021] [Accepted: 07/07/2021] [Indexed: 12/13/2022]
Abstract
Microglial activation has been proposed to contribute to the pathogenesis of schizophrenia. The present study addressed the questions of whether microglial reactivity is involved in the course of schizophrenia and is associated with aging. Transmission electron microscopy and morphometry were applied to estimate microglial density and ultrastructural parameters in layer 5 of the prefrontal cortex (BA10) in postmortem 21 chronic schizophrenia and 20 healthy control cases. A significant increase in microglial density was found in the schizophrenia group (+20 %), in young group (≤50 y.o.), in shorter duration of disease (≤26 yrs.) group, in early age at onset of disease (≤ 21 y.o.) group as compared to controls (p < 0.05) and in young schizophrenia group as compared to both young and elderly (>50 y.o.) controls (p < 0.05). Volume fraction (Vv) of mitochondria was significantly lower and area of lipofuscin granules was significantly higher in young and elderly schizophrenia groups as compared to young and elderly controls. Vv of lipofuscin granules strongly positively correlated with age and duration of disease in the schizophrenia group. Vv and the number (N) of lipofuscin granules were higher in longer duration (>26 yrs.) group as compared to shorter duration group (p < 0.01). Vv and N of vacuoles were increased in longer duration group as compared to controls (p < 0.01). The study provides evidence for microgliosis associated with age, duration of disease and age at onset of disease, progressive dystrophy and accelerated aging of microglia in gray matter of the prefrontal cortex in schizophrenia.
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Affiliation(s)
- N A Uranova
- Laboratory of Clinical Neuropathology, Mental Health Research Centre, Moscow, Russia.
| | - O V Vikhreva
- Laboratory of Clinical Neuropathology, Mental Health Research Centre, Moscow, Russia
| | - V I Rakhmanova
- Laboratory of Clinical Neuropathology, Mental Health Research Centre, Moscow, Russia
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60
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Kraguljac NV, Anthony T, Morgan CJ, Jindal RD, Burger MS, Lahti AC. White matter integrity, duration of untreated psychosis, and antipsychotic treatment response in medication-naïve first-episode psychosis patients. Mol Psychiatry 2021; 26:5347-5356. [PMID: 32398721 PMCID: PMC7658031 DOI: 10.1038/s41380-020-0765-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 04/24/2020] [Accepted: 04/27/2020] [Indexed: 01/10/2023]
Abstract
It is becoming increasingly clear that longer duration of untreated psychosis (DUP) is associated with adverse clinical outcomes in patients with psychosis spectrum disorders. Because this association is often cited when justifying early intervention efforts, it is imperative to better understand underlying biological mechanisms. We enrolled 66 antipsychotic-naïve first-episode psychosis (FEP) patients and 45 matched healthy controls in this trial. At baseline, we used a human connectome style diffusion-weighted imaging (DWI) sequence to quantify white matter integrity in both groups. Patients then received 16 weeks of treatment with risperidone, 51 FEP completed the trial. We compared whole-brain fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD), and radial diffusivity between groups. To test if structural white matter integrity mediates the relationship between longer DUP and poorer treatment response, we fit a mediator model and estimated indirect effects. We found decreased whole-brain FA and AD in medication-naive FEP compared with controls. In patients, lower FA was correlated with longer DUP (r = -0.32; p = 0.03) and poorer subsequent response to antipsychotic treatment (r = 0.40; p = 0.01). Importantly, we found a significant mediation effect for FA (indirect effect: -2.70; p = 0.03), indicating that DUP exerts its effects on treatment response through affecting white matter integrity. Our data provide empirical support to the idea the DUP may have fundamental pathogenic effects on the natural history of psychosis, suggest a biological mechanism underlying this phenomenon, and underscore the importance of early intervention efforts in this disabling neuropsychiatric syndrome.
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Affiliation(s)
- Nina Vanessa Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA.
| | - Thomas Anthony
- Department of Electrical and Computer Engineering/ IT Research Computing, University of Alabama at Birmingham
| | | | - Ripu Daman Jindal
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham,Department of Neurology, Birmingham VA Medical Center
| | - Mark Steven Burger
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham
| | - Adrienne Carol Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham
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61
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McKenna F, Babb J, Miles L, Goff D, Lazar M. Reduced Microstructural Lateralization in Males with Chronic Schizophrenia: A Diffusional Kurtosis Imaging Study. Cereb Cortex 2021; 30:2281-2294. [PMID: 31819950 DOI: 10.1093/cercor/bhz239] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Decreased brain lateralization is considered a trait marker of schizophrenia. Whereas reductions in both functional and macrostructural gray matter laterality in schizophrenia are well established, the investigation of gray matter microstructural lateralization has so far been limited to a small number of ex vivo studies, which limits the understanding of neurobiological substrates involved and development of adequate treatments. The aim of the current study was to assess in vivo gray matter microstructure lateralization patterns in schizophrenia by employing the diffusion kurtosis imaging (DKI)-derived mean kurtosis (MK) metric. MK was calculated for 18 right-handed males with chronic schizophrenia and 19 age-matched healthy control participants in 46 bilateral gray matter regions of interest (ROI). Microstructural laterality indexes (μLIs) were calculated for each subject and ROI, and group comparisons were conducted across regions. The relationship between μLI values and performance on the Wisconsin Card Sorting Test (WCST) was also evaluated. We found that compared with healthy controls, males with chronic schizophrenia had significantly decreased μLI across cortical and subcortical gray matter regions, which was correlated with poorer performance on the WCST. Our results suggest the ability of DKI-derived MK to capture gray matter microstructural lateralization pathology in vivo.
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Affiliation(s)
- Faye McKenna
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA.,Sackler Institute of Graduate Biomedical Sciences New York University School of Medicine, New York, NY 10016, USA
| | - James Babb
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA
| | - Laura Miles
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA
| | - Donald Goff
- Department of Psychiatry, New York University School of Medicine, New York, NY 10016, USA
| | - Mariana Lazar
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA.,Sackler Institute of Graduate Biomedical Sciences New York University School of Medicine, New York, NY 10016, USA
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Sui YV, Bertisch H, Lee HH, Storey P, Babb JS, Goff DC, Samsonov A, Lazar M. Quantitative Macromolecular Proton Fraction Mapping Reveals Altered Cortical Myelin Profile in Schizophrenia Spectrum Disorders. Cereb Cortex Commun 2021; 2:tgab015. [PMID: 34296161 PMCID: PMC8271044 DOI: 10.1093/texcom/tgab015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 02/15/2021] [Accepted: 02/19/2021] [Indexed: 01/12/2023] Open
Abstract
Myelin abnormalities have been reported in schizophrenia spectrum disorders (SSD) in white matter. However, in vivo examinations of cortical myeloarchitecture in SSD, especially those using quantitative measures, are limited. Here, we employed macromolecular proton fraction (MPF) obtained from quantitative magnetization transfer imaging to characterize intracortical myelin organization in 30 SSD patients versus 34 healthy control (HC) participants. We constructed cortical myelin profiles by extracting MPF values at various cortical depths and quantified their shape using a nonlinearity index (NLI). To delineate the association of illness duration with myelin changes, SSD patients were further divided into 3 duration groups. Between-group comparisons revealed reduced NLI in the SSD group with the longest illness duration (>5.5 years) compared with HC predominantly in bilateral prefrontal areas. Within the SSD group, cortical NLI decreased with disease duration and was positively associated with a measure of spatial working memory capacity as well as with cortical thickness (CT). Layer-specific analyses suggested that NLI decreases in the long-duration SSD group may arise in part from significantly increased MPF values in the midcortical layers. The current study reveals cortical myelin profile changes in SSD with illness progression, which may reflect an abnormal compensatory mechanism of the disorder.
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Affiliation(s)
- Yu Veronica Sui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Hilary Bertisch
- Department of Rehabilitation Medicine, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Hong-Hsi Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Pippa Storey
- Department of Radiology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - James S Babb
- Department of Radiology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Donald C Goff
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Alexey Samsonov
- Department of Radiology, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Mariana Lazar
- Department of Radiology, NYU Grossman School of Medicine, New York, NY 10016, USA
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Ye H, Zalesky A, Lv J, Loi SM, Cetin-Karayumak S, Rathi Y, Tian Y, Pantelis C, Di Biase MA. Network Analysis of Symptom Comorbidity in Schizophrenia: Relationship to Illness Course and Brain White Matter Microstructure. Schizophr Bull 2021; 47:1156-1167. [PMID: 33693887 PMCID: PMC8266579 DOI: 10.1093/schbul/sbab015] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
INTRODUCTION Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia. METHODS A symptom comorbidity network was mapped for a broad constellation of symptoms measured in 642 individuals with a schizophrenia-spectrum disorder. Centrality analyses were used to identify hub symptoms. The extent to which each patient's symptoms formed clusters in the comorbidity network was quantified with cluster analysis and used to predict (1) clinical features, including illness duration and psychosis (positive symptom) severity and (2) brain white matter microstructure, indexed by the fractional anisotropy (FA), in a subset (n = 296) of individuals with diffusion-weighted imaging (DWI) data. RESULTS Global functioning, substance use, and blunted affect were the most central symptoms within the symptom comorbidity network. Symptom profiles for some patients formed highly interconnected clusters, whereas other patients displayed unrelated and disconnected symptoms. Stronger clustering among an individual's symptoms was significantly associated with shorter illness duration (t = 2.7; P = .0074), greater psychosis severity (ie, positive symptoms expression) (t = -5.5; P < 0.0001) and lower fractional anisotropy in fibers traversing the cortico-cerebellar-thalamic-cortical circuit (r = .59, P < 0.05). CONCLUSION Symptom network structure varies over the course of schizophrenia: symptom interactions weaken with increasing illness duration and strengthen during periods of high positive symptom expression. Reduced white matter coherence relates to stronger symptom clustering, and thus, may underlie symptom cascades and global symptomatic burden in individuals with schizophrenia.
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Affiliation(s)
- Hua Ye
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia
| | - Jinglei Lv
- School of Biomedical Engineering & Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia
| | - Samantha M Loi
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | | | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Ye Tian
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - Maria A Di Biase
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
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Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort. Mol Psychiatry 2021; 26:3512-3523. [PMID: 32963336 PMCID: PMC8329928 DOI: 10.1038/s41380-020-00882-5] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Revised: 08/21/2020] [Accepted: 09/04/2020] [Indexed: 12/12/2022]
Abstract
The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. For each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n = 195). Individuals with schizophrenia (n = 322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. Compared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region. Furthermore, 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59 ± 2%, p < 0.001). Thus, while infra-normal deviations were common among patients, their anatomical loci were highly inconsistent between individuals. Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r = -0.17, p = 0.006). We conclude that anatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.
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Siagian JM, Loebis B, Camellia V, Effendy E. Factors Associated with Cognitive Score in People with Schizophrenia at Prof. Dr. M. Ildrem Mental Hospital Medan. Open Access Maced J Med Sci 2021. [DOI: 10.3889/oamjms.2021.6303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND: Schizophrenia is characterized by being a condition with complex symptomatic dimensions. Its prognosis is poor due to the impairment of multiple cognitive functions, which handicaps the adequate social, academic, or employment reintegration of the patient. Cognitive impairment refers to the loss of cognitive functions, specifically memory, attention, and speed of information processing. A wide range of cognitive functions is affected, particularly memory, attention, motor skills, executive function, and intelligence.
METHODS: This study is a multivariate predictive conceptual framework study with a cross-sectional approach to 120 subjects at the Prof. Dr. M Ildrem Mental Hospital Medan in May 2020–July 2020 using a sample that is a consecutive sampling. The test conducted in this study consisted of a bivariate test and a multivariate linear regression test to determine the factors that were associated with the cognitive score. The measuring instrument used is the Montreal Cognitive Assessment (MoCA) Ina.
RESULTS: In the bivariate test, in gender variable (p = 0.644) and age variable (p = 0.255) were not statistically significant, so the variables were not included in the multivariate test. In marital status variable (p = 0.0001), type of antipsychotic (p = 0.193), income/month (p = 0.0001), length of education (p = 0.0001), length of illness (p = 0.0001), frequency hospital admission (p = 0.0001), duration of untreated psychosis (DUP) (p = 0.0001), positive and negative syndrome scale (PANSS) scale (p = 0.141), and negative PANSS scale (p = 0.0001) were found statistically significant for the total MoCA Ina score on the bivariate test. After multivariate linear regression testing, the statistically significant variables on the total MoCA Ina score were negative PANSS scale (p = 0.001), income/month (p = 0.0001), length of education (p = 0.001), length of illness (p = 0.0001), DUP (p = 0.028), and marital status (p = 0.0001).
CONCLUSION: By knowing the factors related to the total score of MoCA Ina, it is expected that clinicians can be more careful in giving treatment interventions for people with schizophrenia who are at risk for cognitive impairment.
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Kraguljac NV, McDonald WM, Widge AS, Rodriguez CI, Tohen M, Nemeroff CB. Neuroimaging Biomarkers in Schizophrenia. Am J Psychiatry 2021; 178:509-521. [PMID: 33397140 PMCID: PMC8222104 DOI: 10.1176/appi.ajp.2020.20030340] [Citation(s) in RCA: 119] [Impact Index Per Article: 39.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Schizophrenia is a complex neuropsychiatric syndrome with a heterogeneous genetic, neurobiological, and phenotypic profile. Currently, no objective biological measures-that is, biomarkers-are available to inform diagnostic or treatment decisions. Neuroimaging is well positioned for biomarker development in schizophrenia, as it may capture phenotypic variations in molecular and cellular disease targets, or in brain circuits. These mechanistically based biomarkers may represent a direct measure of the pathophysiological underpinnings of the disease process and thus could serve as true intermediate or surrogate endpoints. Effective biomarkers could validate new treatment targets or pathways, predict response, aid in selection of patients for therapy, determine treatment regimens, and provide a rationale for personalized treatments. In this review, the authors discuss a range of mechanistically plausible neuroimaging biomarker candidates, including dopamine hyperactivity, N-methyl-d-aspartate receptor hypofunction, hippocampal hyperactivity, immune dysregulation, dysconnectivity, and cortical gray matter volume loss. They then focus on the putative neuroimaging biomarkers for disease risk, diagnosis, target engagement, and treatment response in schizophrenia. Finally, they highlight areas of unmet need and discuss strategies to advance biomarker development.
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Affiliation(s)
- Nina V. Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL,Corresponding Author: Nina Vanessa Kraguljac, MD, Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, SC 501, 1720 7th Ave S, Birmingham, AL 35294-0017, 205-996-7171,
| | - William M. McDonald
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine
| | - Alik S. Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Carolyn I. Rodriguez
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA,Veterans Affairs Palo Alto Health Care System, Palo Alto, CA
| | - Mauricio Tohen
- Department of Psychiatry and Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Charles B. Nemeroff
- Department of Psychiatry, University of Texas Dell Medical School, Austin, TX
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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] [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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Raju VB, Shukla A, Jacob A, Bharath RD, Kumar VK, Varambally S, Venkatasubramanian G, Rao NP. The frontal pole and cognitive insight in schizophrenia. Psychiatry Res Neuroimaging 2021; 308:111236. [PMID: 33340961 DOI: 10.1016/j.pscychresns.2020.111236] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 11/23/2020] [Accepted: 12/11/2020] [Indexed: 12/22/2022]
Abstract
Absence of insight owing to impaired self-reflection and lack of touch with reality is a hallmark of schizophrenia. Functional imaging studies in healthy individuals have implicated the frontal pole (FP), sub-division of the prefrontal cortex in self-reflective processes. Despite the significance of self-referential processing in the pathogenesis of schizophrenia, the relationship between FP volume and cognitive insight in this disorder is underexplored. We examined the relationship between cognitive insight and volume of FP using precise manual morphometry of high resolution magnetic resonance images in 19 schizophrenia patients (SCZ) and 21 healthy-volunteers (HV). The manual morphometry technique was replicated from a previous study based on a cytoarchitectonically and functionally valid definition of FP and cognitive insight was measured using Beck's cognitive insight scale. Left frontal pole volume was a significant predictor of self-reflection sub-score of Beck's cognitive insight scale (β=0.68; t = 2.86; p = 0.01). A significant inverse relationship between age and bilateral FP volumes was noted in HV (left FP - r=-0.45; p = 0.04; right FP - r=-0.57; p = 0.008) but not in SCZ (p>0.05). Our findings provide anatomical substrates to devise intervention strategies targeting cognitive insight, thereby improving treatment adherence and functional outcomes.
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Affiliation(s)
- Vikas B Raju
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Ayushi Shukla
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Arpitha Jacob
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Rose Dawn Bharath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Vijay Kg Kumar
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Shivarama Varambally
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | | | - Naren P Rao
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India.
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69
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Curtis MT, Coffman BA, Salisbury DF. Pitch and Duration Mismatch Negativity are Associated With Distinct Auditory Cortex and Inferior Frontal Cortex Volumes in the First-Episode Schizophrenia Spectrum. ACTA ACUST UNITED AC 2021; 2:sgab005. [PMID: 33738454 PMCID: PMC7953127 DOI: 10.1093/schizbullopen/sgab005] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Background Pitch and duration mismatch negativity (pMMN/dMMN) are related to left Heschl's gyrus gray matter volumes in first-episode schizophrenia (FESz). Previous methods were unable to delineate functional subregions within and outside Heschl's gyrus. The Human Connectome Project multimodal parcellation (HCP-MMP) atlas overcomes this limitation by parcellating these functional subregions. Further, MMN has generators in inferior frontal cortex, and therefore, may be associated with inferior frontal cortex pathology. With the novel use of the HCP-MMP to precisely parcellate auditory and inferior frontal cortex, we investigated relationships between gray matter and pMMN and dMMN in FESz. Methods pMMN and dMMN were measured at Fz from 27 FESz and 27 matched healthy controls. T1-weighted MRI scans were acquired. The HCP-MMP atlas was applied to individuals, and gray matter volumes were calculated for bilateral auditory and inferior frontal cortex parcels and correlated with MMN. FDR correction was used for multiple comparisons. Results In FESz only, pMMN was negatively correlated with left medial belt in auditory cortex and area 47L in inferior frontal cortex. Duration MMN negatively correlated with the following auditory parcels: left medial belt, lateral belt, parabelt, TA2, and right A5. Further, dMMN was associated with left area 47L, right area 44, and right area 47L in inferior frontal cortex. Conclusions The novel approach revealed overlapping and distinct gray matter associations for pMMN and dMMN in auditory and inferior frontal cortex in FESz. Thus, pMMN and dMMN may serve as biomarkers of underlying pathological deficits in both similar and slightly different cortical areas.
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Affiliation(s)
- Mark T Curtis
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh, School of Medicine, Pittsburgh, PA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh, School of Medicine, Pittsburgh, PA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh, School of Medicine, Pittsburgh, PA
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Masuda Y, Okada G, Takamura M, Shibasaki C, Yoshino A, Yokoyama S, Ichikawa N, Okuhata S, Kobayashi T, Yamawaki S, Okamoto Y. Age-related white matter changes revealed by a whole-brain fiber-tracking method in bipolar disorder compared to major depressive disorder and healthy controls. Psychiatry Clin Neurosci 2021; 75:46-56. [PMID: 33090632 PMCID: PMC7894167 DOI: 10.1111/pcn.13166] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 09/23/2020] [Accepted: 10/15/2020] [Indexed: 02/01/2023]
Abstract
AIM Several studies have reported altered age-associated changes in white matter integrity in bipolar disorder (BD). However, little is known as to whether these age-related changes are illness-specific. We assessed disease-specific effects by controlling for age and investigated age-associated changes and Group × Age interactions in white matter integrity among major depressive disorder (MDD) patients, BD patients, and healthy controls. METHODS Healthy controls (n = 96; age range, 20-77 years), MDD patients (n = 101; age range, 25-78 years), and BD patients (n = 58; age range, 22-76 years) participated in this study. Fractional anisotropy (FA) derived from diffusion tensor imaging in 54 white matter tracts were compared after controlling for the linear and quadratic effect of age using a generalized linear model. Age-related effects and Age × Group interactions were also assessed in the model. RESULTS The main effect of group was significant in the left column and body of the fornix after controlling for both linear and quadratic effects of age, and in the left body of the corpus callosum after controlling for the quadratic effect of age. BD patients exhibited significantly lower FA relative to other groups. There was no Age × Group interaction in the tracts. CONCLUSION Significant FA reductions were found in BD patients after controlling for age, indicating that abnormal white matter integrity in BD may occur at a younger age rather than developing progressively with age.
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Affiliation(s)
- Yoshikazu Masuda
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Masahiro Takamura
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Chiyo Shibasaki
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Atsuo Yoshino
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Satoshi Yokoyama
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Naho Ichikawa
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Shiho Okuhata
- Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | | | - Shigeto Yamawaki
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
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71
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Abstract
OBJECTIVES The primary objective was to conduct a meta-analysis of studies comparing the GABA levels of schizophrenia patients (SZP) and healthy controls (HC) using proton magnetic resonance spectroscopy (1H-MRS) in the frontal cortex (FC) and its sub-regions. METHODS We included studies published in English language that used 1H-MRS from MRI scanners having at-least 3 Tesla (3 T) magnetic field strength to measure GABA levels in SZP (n = 699) and HC (n = 718) in FC and its sub-regions. The outcome measures were the means and standard deviations of GABA levels and outcome measure was calculated using a random-effect model. RESULTS In FC, medial prefrontal cortex (MPFC) and dorsolateral prefrontal cortex (DLPFC), there were no significant group differences. On excluding the outlier studies, the GABA levels were lower in patients with schizophrenia compared to healthy controls in FC (Hedges' g = -0.2; p = 0.02). In ACC, significant group difference was noted in GABA levels (Hedges' g = -0.25; p = 0.03) with patients values being lower that is more pronounced in the first episode schizophrenia patients (Hedges' g: -0.41; p = 0.003). CONCLUSIONS The available 1H-MRS studies suggest hypo-GABA ergia specifically in ACC and hint towards possible hypo GABA-ergic state in the FC. However, limitations of the analysis should be considered while interpreting the results.
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Affiliation(s)
- Vijay Kumar
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Bhavika Vajawat
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Naren P Rao
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
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Correll CU, Kim E, Sliwa JK, Hamm W, Gopal S, Mathews M, Venkatasubramanian R, Saklad SR. Pharmacokinetic Characteristics of Long-Acting Injectable Antipsychotics for Schizophrenia: An Overview. CNS Drugs 2021; 35:39-59. [PMID: 33507525 PMCID: PMC7873121 DOI: 10.1007/s40263-020-00779-5] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/23/2020] [Indexed: 12/13/2022]
Abstract
The availability of long-acting injectable (LAI) antipsychotics for the treatment of schizophrenia provides clinicians with options that deliver continuous drug exposure and may improve adherence compared with daily oral antipsychotics. However, all LAI antipsychotics have unique formulations and pharmacokinetic characteristics that have implications for medication selection, administration interval, and injection site. This review outlines key differences in drug formulations and pharmacokinetics among LAI antipsychotics. A systematic search of the PubMed database was conducted to identify physical and formulation properties and pharmacokinetic data of commercially available LAI antipsychotics, including flupentixol decanoate, fluphenazine decanoate, haloperidol decanoate, zuclopenthixol decanoate, aripiprazole monohydrate, aripiprazole lauroxil, olanzapine pamoate, paliperidone palmitate, risperidone microspheres, and risperidone polymeric microspheres. Additional information was obtained from package inserts and product monographs. Relevant data on drug properties, administration details, pharmacokinetic parameters, and oral dose equivalencies of LAI antipsychotics are summarized. Based on our analysis, formulation characteristics (e.g., vehicle medium) and administration characteristics (e.g., injection site) can affect rate of absorption and adverse effects and may factor into whether oral supplementation or an additional injection is needed. Dose adjustments may be necessary based on potential drug-drug interactions, and approximate dose equivalence with oral formulations can help inform titration when switching from oral to LAI formulations. Clinicians administering LAI antipsychotics should consider these formulation and pharmacokinetic factors to maximize clinical impact and to adjust to an individual patient's needs and treatment goals.
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Affiliation(s)
- Christoph U Correll
- Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Division of Psychiatric Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Edward Kim
- Janssen Scientific Affairs, LLC, Titusville, NJ, USA
| | | | - Wayne Hamm
- Janssen Scientific Affairs, LLC, Spring Hill, TN, USA
| | - Srihari Gopal
- Janssen Research and Development, LLC, Titusville, NJ, USA
| | - Maju Mathews
- Janssen Research and Development, LLC, Titusville, NJ, USA
| | | | - Stephen R Saklad
- College of Pharmacy, Pharmacotherapy Division, The University of Texas at Austin, 7703 Floyd Curl Drive, MC 6220, San Antonio, TX, 78229-3900, USA.
- Long School of Medicine, Pharmacotherapy Education and Research Center, UT Health San Antonio, San Antonio, TX, 78229-3900, USA.
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73
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Sun Z, Zhao L, Bo Q, Mao Z, He Y, Jiang T, Li Y, Wang C, Li R. Brain-Specific Oxysterols and Risk of Schizophrenia in Clinical High-Risk Subjects and Patients With Schizophrenia. Front Psychiatry 2021; 12:711734. [PMID: 34408685 PMCID: PMC8367079 DOI: 10.3389/fpsyt.2021.711734] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 07/05/2021] [Indexed: 01/19/2023] Open
Abstract
Accumulating evidence from clinical, genetic, and epidemiologic studies suggest that schizophrenia might be a neuronal development disorder. While oxysterols are important factors in neurodevelopment, it is unknown whether oxysterols might be involved in development of schizophrenia. The present study investigated the relationship between tissue-specifically originated oxysterols and risk of schizophrenia. A total of 216 individuals were recruited in this study, including 76 schizophrenia patients, 39 clinical high-risk (CHR) subjects, and 101 healthy controls (HC). We investigated the circulating levels of brain-specific oxysterol 24(S)-hydroxycholesterol (24OHC) and peripheral oxysterol 27-hydroxycholesterol (27OHC) in all participants and analyzed the potential links between the oxysterols and specific clinical symptoms in schizophrenic patients and CHR. Our data showed an elevation of 24OHC in both schizophrenia patients and CHR than that in HC, while a lower level of 27OHC in the schizophrenia group only. The ratio of 24OHC to 27OHC was only increased in the schizophrenic group compared with CHR and HC. For the schizophrenic patients, the circulating 24OHC levels are significantly associated with disease duration, positively correlated with the positive and negative syndrome total scores, while the 27OHC levels were inversely correlated with the positive symptom scores. Together, our data demonstrated the disruption of tissue-specifically originated cholesterol metabolism in schizophrenia and CHR, suggesting the circulating 24OHC or 24OHC/27OHC ratio might not only be a potential indicator for risk for schizophrenia but also be biomarkers for functional abnormalities in neuropathology of schizophrenia.
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Affiliation(s)
- Zuoli Sun
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Lei Zhao
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Qijing Bo
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Zhen Mao
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Yi He
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Tao Jiang
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Yuhong Li
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Chuanyue Wang
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Rena Li
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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74
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Feng R, Womer FY, Edmiston EK, Chen Y, Wang Y, Chang M, Yin Z, Wei Y, Duan J, Ren S, Li C, Liu Z, Jiang X, Wei S, Li S, Zhang X, Zuo XN, Tang Y, Wang F. Antipsychotic Effects on Cortical Morphology in Schizophrenia and Bipolar Disorders. Front Neurosci 2020; 14:579139. [PMID: 33362453 PMCID: PMC7758211 DOI: 10.3389/fnins.2020.579139] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 11/10/2020] [Indexed: 11/30/2022] Open
Abstract
Background: Previous studies of atypical antipsychotic effects on cortical structures in schizophrenia (SZ) and bipolar disorder (BD) have findings that vary between the short and long term. In particular, there has not been a study exploring the effects of atypical antipsychotics on age-related cortical structural changes in SZ and BD. This study aimed to determine whether mid- to long-term atypical antipsychotic treatment (mean duration = 20 months) is associated with cortical structural changes and whether age-related cortical structural changes are affected by atypical antipsychotics. Methods: Structural magnetic resonance imaging images were obtained from 445 participants consisting of 88 medicated patients (67 with SZ, 21 with BD), 84 unmedicated patients (50 with SZ, 34 with BD), and 273 healthy controls (HC). Surface-based analyses were employed to detect differences in thickness and area among the three groups. We examined the age-related effects of atypical antipsychotics after excluding the potential effects of illness duration. Results: Significant differences in cortical thickness were observed in the frontal, temporal, parietal, and insular areas and the isthmus of the cingulate gyrus. The medicated group showed greater cortical thinning in these regions than the unmediated group and HC; furthermore, there were age-related differences in the effects of atypical antipsychotics, and these effects did not relate to illness duration. Moreover, cortical thinning was significantly correlated with lower symptom scores and Wisconsin Card Sorting Test (WCST) deficits in patients. After false discovery rate correction, cortical thinning in the right middle temporal gyrus in patients was significantly positively correlated with lower HAMD scores. The unmedicated group showed only greater frontotemporal thickness than the HC group. Conclusion: Mid- to long-term atypical antipsychotic use may adversely affect cortical thickness over the course of treatment and ageing and may also result in worsening cognitive function.
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Affiliation(s)
- Ruiqi Feng
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fay Y. Womer
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - E. Kale Edmiston
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yifan Chen
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yinshan Wang
- CAS Key Laboratory of Behavioral Science and Research Center for Lifespan Development of Mind and Brain (CLIMB), Institute of Psychology, Beijing, China
| | - Miao Chang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zhiyang Yin
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yange Wei
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jia Duan
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Sihua Ren
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Chao Li
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zhuang Liu
- School of Public Health, China Medical University, Shenyang, China
| | - Xiaowei Jiang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Shengnan Wei
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Songbai Li
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Xi-Nian Zuo
- Key Laboratory of Brain and Education Sciences, School of Education Sciences, Nanning Normal University, Nanning, China
| | - Yanqing Tang
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
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75
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Cetin-Karayumak S, Di Biase MA, Chunga N, Reid B, Somes N, Lyall AE, Kelly S, Solgun B, Pasternak O, Vangel M, Pearlson G, Tamminga C, Sweeney JA, Clementz B, Schretlen D, Viher PV, Stegmayer K, Walther S, Lee J, Crow T, James A, Voineskos A, Buchanan RW, Szeszko PR, Malhotra AK, Hegde R, McCarley R, Keshavan M, Shenton M, Rathi Y, Kubicki M. White matter abnormalities across the lifespan of schizophrenia: a harmonized multi-site diffusion MRI study. Mol Psychiatry 2020; 25:3208-3219. [PMID: 31511636 PMCID: PMC7147982 DOI: 10.1038/s41380-019-0509-y] [Citation(s) in RCA: 100] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 05/05/2019] [Accepted: 06/10/2019] [Indexed: 02/07/2023]
Abstract
Several prominent theories of schizophrenia suggest that structural white matter pathologies may follow a developmental, maturational, and/or degenerative process. However, a lack of lifespan studies has precluded verification of these theories. Here, we analyze the largest sample of carefully harmonized diffusion MRI data to comprehensively characterize age-related white matter trajectories, as measured by fractional anisotropy (FA), across the course of schizophrenia. Our analysis comprises diffusion scans of 600 schizophrenia patients and 492 healthy controls at different illness stages and ages (14-65 years), which were gathered from 13 sites. We determined the pattern of age-related FA changes by cross-sectionally assessing the timing of the structural neuropathology associated with schizophrenia. Quadratic curves were used to model between-group FA differences across whole-brain white matter and fiber tracts at each age; fiber tracts were then clustered according to both the effect-sizes and pattern of lifespan white matter FA differences. In whole-brain white matter, FA was significantly lower across the lifespan (up to 7%; p < 0.0033) and reached peak maturation younger in patients (27 years) compared to controls (33 years). Additionally, three distinct patterns of neuropathology emerged when investigating white matter fiber tracts in patients: (1) developmental abnormalities in limbic fibers, (2) accelerated aging and abnormal maturation in long-range association fibers, (3) severe developmental abnormalities and accelerated aging in callosal fibers. Our findings strongly suggest that white matter in schizophrenia is affected across entire stages of the disease. Perhaps most strikingly, we show that white matter changes in schizophrenia involve dynamic interactions between neuropathological processes in a tract-specific manner.
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Affiliation(s)
- Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA.
| | - Maria A Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
| | - Natalia Chunga
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- Department of Neurology, University of Rochester Medical Center, NY, Rochester, USA
| | - Benjamin Reid
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
| | - Nathaniel Somes
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- MGH Institute of Health Professions, MA, Charlestown, USA
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sinead Kelly
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | | | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Vangel
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Carol Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Brett Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, USA
| | - David Schretlen
- Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, USA
| | - Petra Verena Viher
- University of Bern, University Hospital of Psychiatry, Bern, Switzerland
| | | | - Sebastian Walther
- University of Bern, University Hospital of Psychiatry, Bern, Switzerland
| | - Jungsun Lee
- Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Tim Crow
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Anthony James
- Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK
| | - Aristotle Voineskos
- Centre for Addiction and Mental Health; Department of Psychiatry, University of Toronto, Toronto, Canada
| | | | - Philip R Szeszko
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai; Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center, New York, USA
| | - Anil K Malhotra
- The Feinstein Institute for Medical Research and Zucker Hillside Hospital, Manhasset, USA
| | - Rachal Hegde
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | | | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA, USA
| | - Martha Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Harvard Medical School, Boston, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, Boston, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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76
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Yamamoto M, Bagarinao E, Kushima I, Takahashi T, Sasabayashi D, Inada T, Suzuki M, Iidaka T, Ozaki N. Support vector machine-based classification of schizophrenia patients and healthy controls using structural magnetic resonance imaging from two independent sites. PLoS One 2020; 15:e0239615. [PMID: 33232334 PMCID: PMC7685428 DOI: 10.1371/journal.pone.0239615] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 09/10/2020] [Indexed: 12/17/2022] Open
Abstract
Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support vector machines can classify patients and healthy controls by detecting subtle and spatially distributed patterns of structural alterations. We aimed to use a support vector machine to distinguish patients with schizophrenia from control participants on the basis of structural magnetic resonance imaging data and delineate the patterns of structural alterations that significantly contributed to the classification performance. We used independent datasets from different sites with different magnetic resonance imaging scanners, protocols and clinical characteristics of the patient group to achieve a more accurate estimate of the classification performance of support vector machines. We developed a support vector machine classifier using the dataset from one site (101 participants) and evaluated the performance of the trained support vector machine using a dataset from the other site (97 participants) and vice versa. We assessed the performance of the trained support vector machines in each support vector machine classifier. Both support vector machine classifiers attained a classification accuracy of >70% with two independent datasets indicating a consistently high performance of support vector machines even when used to classify data from different sites, scanners and different acquisition protocols. The regions contributing to the classification accuracy included the bilateral medial frontal cortex, superior temporal cortex, insula, occipital cortex, cerebellum, and thalamus, which have been reported to be related to the pathogenesis of schizophrenia. These results indicated that the support vector machine could detect subtle structural brain alterations and might aid our understanding of the pathophysiology of these changes in schizophrenia, which could be one of the diagnostic findings of schizophrenia.
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Affiliation(s)
- Maeri Yamamoto
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
| | | | - Itaru Kushima
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
- Medical Genomics Center, Nagoya University Hospital, Nagoya, Aichi, Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Toyama, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Toyama, Japan
| | - Toshiya Inada
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Toyama, Japan
| | - Tetsuya Iidaka
- Brain & Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
- * E-mail:
| | - Norio Ozaki
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
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77
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Curtis MT, Coffman BA, Salisbury DF. Parahippocampal area three gray matter is reduced in first-episode schizophrenia spectrum: Discovery and replication samples. Hum Brain Mapp 2020; 42:724-736. [PMID: 33219733 PMCID: PMC7814759 DOI: 10.1002/hbm.25256] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 09/02/2020] [Accepted: 10/07/2020] [Indexed: 12/27/2022] Open
Abstract
Early course schizophrenia is associated with reduced gray matter. The specific structures affected first and how deficits impact symptoms and cognition remain unresolved. We used the Human Connectome Project multimodal parcellation (HCP‐MMP) to precisely identify cortical areas and investigate thickness abnormalities in discovery and replication samples of first‐episode schizophrenia spectrum individuals (FESz). In the discovery sample, T1w scans were acquired from 31 FESz and 31 matched healthy controls (HC). Thickness was calculated for 360 regions in Freesurfer. In the replication sample, high‐resolution T1w, T2w, and BOLD‐rest scans were acquired from 23 FESz and 32 HC and processed with HCP protocols. Thickness was calculated for regions significant in the discovery sample. After FDR correction (q < .05), left and right parahippocampal area 3 (PHA3) were significantly thinner in FESz. In the replication sample, bilateral PHA3 were again thinner in FESz (q < .05). Exploratory correlation analyses revealed left PHA3 was positively associated with hallucinations and right PHA3 was positively associated with processing speed, working memory, and verbal learning. The novel use of the HCP‐MMP in two independent FESz samples revealed thinner bilateral PHA3, suggesting this byway between cortical and limbic processing is a critical site of pathology near the emergence of psychosis.
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Affiliation(s)
- Mark T Curtis
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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Assessment of brain cholesterol metabolism biomarker 24S-hydroxycholesterol in schizophrenia. NPJ SCHIZOPHRENIA 2020; 6:34. [PMID: 33219208 PMCID: PMC7680117 DOI: 10.1038/s41537-020-00121-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 09/03/2020] [Indexed: 11/08/2022]
Abstract
Plasma 24S-hydroxycholesterol mostly originates in brain tissue and likely reflects the turnover of cholesterol in the central nervous system. As cholesterol is disproportionally enriched in many key brain structures, 24S-hydroxycholesterol is a promising biomarker for psychiatric and neurologic disorders that impact brain structure. We hypothesized that, as schizophrenia patients have widely reported gray and white matter deficits, they would have abnormal levels of plasma 24S-hydroxycholesterol, and that plasma levels of 24S-hydroxycholesterol would be associated with brain structural and functional biomarkers for schizophrenia. Plasma levels of 24S-hydroxycholesterol were measured in 226 individuals with schizophrenia and 204 healthy controls. The results showed that levels of 24S-hydroxycholesterol were not significantly different between patients and controls. Age was significantly and negatively correlated with 24S-hydroxycholesterol in both groups, and in both groups, females had significantly higher levels of 24S-hydroxycholesterol compared to males. Levels of 24S-hydroxycholesterol were not related to average fractional anisotropy of white matter or cortical thickness, or to cognitive deficits in schizophrenia. Based on these results from a large sample and using multiple brain biomarkers, we conclude there is little to no value of plasma 24S-hydroxycholesterol as a brain metabolite biomarker for schizophrenia.
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79
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Air Pollution-Related Brain Metal Dyshomeostasis as a Potential Risk Factor for Neurodevelopmental Disorders and Neurodegenerative Diseases. ATMOSPHERE 2020. [DOI: 10.3390/atmos11101098] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Increasing evidence links air pollution (AP) exposure to effects on the central nervous system structure and function. Particulate matter AP, especially the ultrafine (nanoparticle) components, can carry numerous metal and trace element contaminants that can reach the brain in utero and after birth. Excess brain exposure to either essential or non-essential elements can result in brain dyshomeostasis, which has been implicated in both neurodevelopmental disorders (NDDs; autism spectrum disorder, schizophrenia, and attention deficit hyperactivity disorder) and neurodegenerative diseases (NDGDs; Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis). This review summarizes the current understanding of the extent to which the inhalational or intranasal instillation of metals reproduces in vivo the shared features of NDDs and NDGDs, including enlarged lateral ventricles, alterations in myelination, glutamatergic dysfunction, neuronal cell death, inflammation, microglial activation, oxidative stress, mitochondrial dysfunction, altered social behaviors, cognitive dysfunction, and impulsivity. Although evidence is limited to date, neuronal cell death, oxidative stress, and mitochondrial dysfunction are reproduced by numerous metals. Understanding the specific contribution of metals/trace elements to this neurotoxicity can guide the development of more realistic animal exposure models of human AP exposure and consequently lead to a more meaningful approach to mechanistic studies, potential intervention strategies, and regulatory requirements.
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80
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Ammirati E, Moroni F, Magnoni M, Rocca MA, Messina R, Anzalone N, De Filippis C, Scotti I, Besana F, Spagnolo P, Rimoldi OE, Chiesa R, Falini A, Filippi M, Camici PG. Extent and characteristics of carotid plaques and brain parenchymal loss in asymptomatic patients with no indication for revascularization. IJC HEART & VASCULATURE 2020; 30:100619. [PMID: 32904369 PMCID: PMC7452655 DOI: 10.1016/j.ijcha.2020.100619] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 08/01/2020] [Accepted: 08/10/2020] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Extent of subclinical atherosclerosis has been associated with brain parenchymal loss in community-dwelling aged subjects. Identification of patient-related and plaque-related markers could identify subjects at higher risk of brain atrophy, independent of cerebrovascular accidents. Aim of the study was to investigate the relation between extent and characteristics of carotid plaques and brain atrophy in asymptomatic patients with no indication for revascularization. METHODS AND RESULTS Sixty-four patients (aged 69 ± 8 years, 45% females) with carotid stenosis <70% based on Doppler flow velocity were enrolled in the study. Potential causes of cerebral damage other than atherosclerosis, including history of atrial fibrillation, heart failure, previous cardiac or neurosurgery and neurological disorders were excluded. All subjects underwent carotid computed tomography angiography, contrast enhanced ultrasound for assessment of plaque neovascularization and brain magnetic resonance imaging for measuring brain volumes. On multivariate regression analysis, age and fibrocalcific plaques were independently associated with lower total brain volumes (β = -3.13 and β = -30.7, both p < 0.05). Fibrocalcific plaques were also independently associated with lower gray matter (GM) volumes (β = -28.6, p = 0.003). On the other hand, age and extent of carotid atherosclerosis were independent predictors of lower white matter (WM) volumes. CONCLUSIONS WM and GM have different susceptibility to processes involved in parenchymal loss. Contrary to common belief, our results show that presence of fibrocalcific plaques is associated with brain atrophy.
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Affiliation(s)
- Enrico Ammirati
- Vita-Salute University and San Raffaele Hospital, Milan, Italy
- De Gasperis Cardio Center, Niguarda Ca’ Granda Hospital, Milan, Italy
| | | | - Marco Magnoni
- Vita-Salute University and San Raffaele Hospital, Milan, Italy
| | - Maria A Rocca
- Vita-Salute University and Neuroimaging Research Unit, Institute of Experimental Neurology, and Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Roberta Messina
- Vita-Salute University and Neuroimaging Research Unit, Institute of Experimental Neurology, and Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Nicoletta Anzalone
- Vita-Salute University and Department of Neuroradiology, San Raffaele Scientific Institute, Milan, Italy
| | - Costantino De Filippis
- Vita-Salute University and Department of Neuroradiology, San Raffaele Scientific Institute, Milan, Italy
| | - Isabella Scotti
- Department of Rheumatology, Istituto Ortopedico Gaetano Pini, Milan, Italy
| | - Francesca Besana
- Cardiovascular Prevention Center, San Raffaele Institute, Milan, Italy
| | - Pietro Spagnolo
- Cardiovascular Prevention Center, San Raffaele Institute, Milan, Italy
- Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy
| | | | - Roberto Chiesa
- Vita-Salute University and San Raffaele Hospital, Milan, Italy
| | - Andrea Falini
- Vita-Salute University and Department of Neuroradiology, San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Vita-Salute University and Neuroimaging Research Unit, Institute of Experimental Neurology, and Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Paolo G Camici
- Vita-Salute University and San Raffaele Hospital, Milan, Italy
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81
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Salisbury DF, Wang Y, Yeh FC, Coffman BA. White Matter Microstructural Abnormalities in the Broca's-Wernicke's-Putamen "Hoffman Hallucination Circuit" and Auditory Transcallosal Fibers in First-Episode Psychosis With Auditory Hallucinations. Schizophr Bull 2020; 47:149-159. [PMID: 32766733 PMCID: PMC7825092 DOI: 10.1093/schbul/sbaa105] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
BACKGROUND Functional connectivity abnormalities between Broca's and Wernicke's areas and the putamen revealed by functional magnetic resonance imaging (fMRI) are related to auditory hallucinations (AH). In long-term schizophrenia, reduced white matter structural integrity revealed by diffusion imaging in left arcuate fasciculus (connecting Broca's and Wernicke's areas) is likely related to AH. The structural integrity of connections with putamen and their relation to AH are unknown. Little is known about this relationship in first-episode psychosis (FEP), although auditory transcallosal connections were reported to play a role. White matter in the Broca's-Wernicke's-putamen language-related circuit and auditory transcallosal fibers was examined to investigate associations with AH in FEP. METHODS White matter connectivity was measured in 40 FEP and 32 matched HC using generalized fractional anisotropy (gFA) derived from diffusion spectrum imaging (DSI). RESULTS FEP and HC did not differ in gFA in any fiber bundle. In FEP, AH severity was significantly inversely related to gFA in auditory transcallosal fibers and left arcuate fasciculus. Although the right hemisphere arcuate fasciculus-AH association did not attain significance, the left and right arcuate fasciculus associations were not significantly different. CONCLUSIONS Despite overall normal gFA in FEP, AH severity was significantly related to gFA in transcallosal auditory fibers and the left hemisphere connection between Broca's and Wernicke's areas. Other bilateral tracts' gFA were weakly associated with AH. At the first psychotic episode, AH are more robustly associated with left hemisphere arcuate fasciculus and interhemispheric auditory fibers microstructural deficits, likely reflecting mistiming of information flow between language-related cortical centers.
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Affiliation(s)
- Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA,To whom correspondence should be addressed; Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, 3501 Forbes Ave, Pittsburgh, PA 15213; tel: 412-246-5123, fax: 412-246-6636, e-mail:
| | - Yiming Wang
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA
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Regional, cellular and species difference of two key neuroinflammatory genes implicated in schizophrenia. Brain Behav Immun 2020; 88:826-839. [PMID: 32450195 DOI: 10.1016/j.bbi.2020.05.055] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 05/20/2020] [Accepted: 05/20/2020] [Indexed: 02/07/2023] Open
Abstract
The transcription factor nuclear factor kappa B (NF-κB) regulates the expression of many inflammatory genes that are overexpressed in a subset of people with schizophrenia. Transcriptional reduction in one NF-κB inhibitor, Human Immunodeficiency Virus Enhancer Binding Protein 2 (HIVEP2), is found in the brain of patients, aligning with evidence of NF-κB over-activity. Cellular co-expression of HIVEP2 and cytokine transcripts is a prerequisite for a direct effect of HIVEP2 on pro-inflammatory transcription, and we do not know if changes in HIVEP2 and markers of neuroinflammation are occurring in the same brain cell type. We performed in situ hybridisation on postmortem dorsolateral prefrontal cortex tissue to map and compare the expression of HIVEP2 and Serpin Family A Member 3 (SERPINA3), one of the most consistently increased inflammatory genes in schizophrenia, between schizophrenia patients and controls. We find that HIVEP2 expression is neuronal and is decreased in almost all grey matter cortical layers in schizophrenia patients with neuroinflammation, and that SERPINA3 is increased in the dorsolateral prefrontal cortex grey matter and white matter in the same group of patients. We are the first to map the upregulation of SERPINA3 to astrocytes and to some neurons, and find evidence to suggest that blood vessel-associated astrocytes are the main cellular source of SERPINA3 in the schizophrenia cortex. We show that a lack of HIVEP2 in mice does not cause astrocytic upregulation of Serpina3n but does induce its transcription in neurons. We speculate that HIVEP2 downregulation is not a direct cause of astrocytic pro-inflammatory cytokine synthesis in schizophrenia but may contribute to neuronally-mediated neuroinflammation.
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83
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Alemán-Gómez Y, Najdenovska E, Roine T, Fartaria MJ, Canales-Rodríguez EJ, Rovó Z, Hagmann P, Conus P, Do KQ, Klauser P, Steullet P, Baumann PS, Bach Cuadra M. Partial-volume modeling reveals reduced gray matter in specific thalamic nuclei early in the time course of psychosis and chronic schizophrenia. Hum Brain Mapp 2020; 41:4041-4061. [PMID: 33448519 PMCID: PMC7469814 DOI: 10.1002/hbm.25108] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/22/2020] [Accepted: 06/14/2020] [Indexed: 12/20/2022] Open
Abstract
The structural complexity of the thalamus, due to its mixed composition of gray and white matter, make it challenging to disjoint and quantify each tissue contribution to the thalamic anatomy. This work promotes the use of partial‐volume‐based over probabilistic‐based tissue segmentation approaches to better capture thalamic gray matter differences between patients at different stages of psychosis (early and chronic) and healthy controls. The study was performed on a cohort of 23 patients with schizophrenia, 41 with early psychosis and 69 age and sex‐matched healthy subjects. Six tissue segmentation approaches were employed to obtain the gray matter concentration/probability images. The statistical tests were applied at three different anatomical scales: whole thalamus, thalamic subregions and voxel‐wise. The results suggest that the partial volume model estimation of gray matter is more sensitive to detect atrophies within the thalamus of patients with psychosis. However all the methods detected gray matter deficit in the pulvinar, particularly in early stages of psychosis. This study demonstrates also that the gray matter decrease varies nonlinearly with age and between nuclei. While a gray matter loss was found in the pulvinar of patients in both stages of psychosis, reduced gray matter in the mediodorsal was only observed in early psychosis subjects. Finally, our analyses point to alterations in a sub‐region comprising the lateral posterior and ventral posterior nuclei. The obtained results reinforce the hypothesis that thalamic gray matter assessment is more reliable when the tissues segmentation method takes into account the partial volume effect.
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Affiliation(s)
- Yasser Alemán-Gómez
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Switzerland
| | - Elena Najdenovska
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Timo Roine
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Switzerland
| | - Mário João Fartaria
- Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Erick J Canales-Rodríguez
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,FIDMAG Germanes Hospitalàries Research Foundation, Sant Boi de Llobregat, Barcelona, Spain
| | - Zita Rovó
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Philippe Conus
- Service of General Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Kim Q Do
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Pascal Steullet
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Philipp S Baumann
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Service of General Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Meritxell Bach Cuadra
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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84
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Tønnesen S, Kaufmann T, de Lange AMG, Richard G, Doan NT, Alnæs D, van der Meer D, Rokicki J, Moberget T, Maximov II, Agartz I, Aminoff SR, Beck D, Barch DM, Beresniewicz J, Cervenka S, Fatouros-Bergman H, Craven AR, Flyckt L, Gurholt TP, Haukvik UK, Hugdahl K, Johnsen E, Jönsson EG, Kolskår KK, Kroken RA, Lagerberg TV, Løberg EM, Nordvik JE, Sanders AM, Ulrichsen K, Andreassen OA, Westlye LT. Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder: A Multisample Diffusion Tensor Imaging Study. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 5:1095-1103. [PMID: 32859549 DOI: 10.1016/j.bpsc.2020.06.014] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 06/15/2020] [Accepted: 06/26/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND Schizophrenia (SZ) and bipolar disorder (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, patients with BD, and healthy control (HC) subjects across 10 cohorts. METHODS We trained 6 cross-validated models using different combinations of DTI data from 927 HC subjects (18-94 years of age) and applied the models to the test sets including 648 patients with SZ (18-66 years of age), 185 patients with BD (18-64 years of age), and 990 HC subjects (17-68 years of age), estimating the brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results. RESULTS Tenfold cross-validation revealed high accuracy for all models. Compared with HC subjects, the model including all feature sets significantly overestimated the age of patients with SZ (Cohen's d = -0.29) and patients with BD (Cohen's d = 0.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy-based models showed larger group differences than the models based on other DTI-derived metrics. CONCLUSIONS Brain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.
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Affiliation(s)
- Siren Tønnesen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ann-Marie G de Lange
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United Kingdom
| | - Geneviève Richard
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Nhat Trung Doan
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Bjørknes University College, Oslo, Norway
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Jaroslav Rokicki
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Torgeir Moberget
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ivan I Maximov
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm Region, Stockholm, Sweden; Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Sofie R Aminoff
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Early Intervention in Psychosis Advisory Unit for South East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dani Beck
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Deanna M Barch
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri; Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri; Department of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Justyna Beresniewicz
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT, Haukeland University Hospital, Bergen, Norway
| | - Simon Cervenka
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm Region, Stockholm, Sweden; Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Helena Fatouros-Bergman
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm Region, Stockholm, Sweden; Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT, Haukeland University Hospital, Bergen, Norway; Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Lena Flyckt
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm Region, Stockholm, Sweden; Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Unn K Haukvik
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Adult Psychiatry Unit, Department of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kenneth Hugdahl
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT, Haukeland University Hospital, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Erik Johnsen
- Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway
| | - Erik G Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm Region, Stockholm, Sweden; Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | | | - Knut K Kolskår
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Sunnaas Rehabilitation Hospital HF, Nesodden, Norway
| | - Rune Andreas Kroken
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT, Haukeland University Hospital, Bergen, Norway
| | - Trine V Lagerberg
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Else-Marie Løberg
- Department of Clinical Psychology, University of Bergen, Bergen, Norway; NORMENT, Haukeland University Hospital, Bergen, Norway; Department of Addiction Medicine, Haukeland University Hospital, Bergen, Norway
| | | | - Anne-Marthe Sanders
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Sunnaas Rehabilitation Hospital HF, Nesodden, Norway
| | - Kristine Ulrichsen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Sunnaas Rehabilitation Hospital HF, Nesodden, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
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Tsai SY, Sajatovic M, Hsu JL, Chung KH, Chen PH, Huang YJ. Body mass index, residual psychotic symptoms, and inflammation associated with brain volume reduction in older patients with schizophrenia. Int J Geriatr Psychiatry 2020; 35:728-736. [PMID: 32128879 DOI: 10.1002/gps.5291] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 02/02/2020] [Accepted: 02/25/2020] [Indexed: 11/06/2022]
Abstract
UNLABELLED Obesity, aging, and pathophysiology of schizophrenia (SCZ) may collectively contribute to the gray matter loss in brain regions of SCZ. We attempted to examine the association between volumes of specific brain regions, body mass index (BMI), inflammatory markers, and clinical features in older SCZ patients. METHOD Clinically stable outpatients with schizophrenia (DSM-IV) aged ≥50 years were recruited to undergo whole-brain magnetic resonance imaging. We measured patients' plasma levels of soluble tumor necrosis factor receptor-1, soluble interleukin (IL)-2 receptor (sIL-2R), IL-1β, and IL-1 receptor antagonist (IL-1Ra). Clinical data were obtained from medical records and interviewing patients along with their reliable others. RESULTS There were 32 patients with mean age 58.8 years in this study. Multivariate regression analysis found only higher BMI significantly associated with lower volume of total gray matter, bilateral orbitofrontal and prefrontal cortexes, and the right hippocampal and frontal cortexes. Increased intensity of residual symptoms (higher Positive and Negative Syndrome Scale scores) was related to lower volumes of frontal lobe, prefrontal cortex, insula, hippocampus, left hemisphere amygdala, and total white matter. The lower volume of left anterior cingulum was associated with older age and higher sIL-2R plasma level; and higher IL-1Ra level was associated with greater right anterior cingulate volume. Older age at illness onset was significantly associated with the smaller right insula volume. CONCLUSIONS Higher BMI, more residual symptoms, and inflammatory activity in IL-2 and IL-1 systems may play a role in gray matter loss in various brain regions of schizophrenia across the life span.
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Affiliation(s)
- Shang-Ying Tsai
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Psychiatry and Psychiatric Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Martha Sajatovic
- Department of Psychiatry, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Jung-Lung Hsu
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center and College of Medicine, Chang-Gung University, Taoyuan, Taiwan
| | - Kuo-Hsuan Chung
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Psychiatry and Psychiatric Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Pao-Huan Chen
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Psychiatry and Psychiatric Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Yu-Jui Huang
- Department of Psychiatry and Psychiatric Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
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86
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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] [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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87
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Impact of ageing on the brain regions of the schizophrenia patients: an fMRI study using evolutionary approach. MULTIMEDIA TOOLS AND APPLICATIONS 2020. [DOI: 10.1007/s11042-020-09183-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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88
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Kuo CY, Lee PL, Hung SC, Liu LK, Lee WJ, Chung CP, Yang AC, Tsai SJ, Wang PN, Chen LK, Chou KH, Lin CP. Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker. Cereb Cortex 2020; 30:5844-5862. [PMID: 32572452 DOI: 10.1093/cercor/bhaa161] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/05/2020] [Accepted: 05/21/2020] [Indexed: 12/31/2022] Open
Abstract
The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging profiles into a single, quantitative index that could serve as a biomarker both for characterizing individual brain health and for identifying neurodegenerative and neuropsychiatric diseases. Using a large-scale structural covariance network (SCN)-based framework with machine learning algorithms, we demonstrate this framework's ability to predict individual brain age in a large sample of middle-to-late age adults, and highlight its clinical specificity for several disease populations from a network perspective. A proposed estimator with 40 SCNs could predict individual brain age, balancing between model complexity and prediction accuracy. Notably, we found that the most significant SCN for predicting brain age included the caudate nucleus, putamen, hippocampus, amygdala, and cerebellar regions. Furthermore, our data indicate a larger brain age disparity in patients with schizophrenia and Alzheimer's disease than in healthy controls, while this metric did not differ significantly in patients with major depressive disorder. These findings provide empirical evidence supporting the estimation of brain age from a brain network perspective, and demonstrate the clinical feasibility of evaluating neurological diseases hypothesized to be associated with accelerated brain aging.
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Affiliation(s)
- Chen-Yuan Kuo
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming University, Taipei 11221, Taiwan
| | - Pei-Lin Lee
- Institute of Neuroscience, National Yang Ming University, Taipei 11221, Taiwan
| | - Sheng-Che Hung
- Department of Radiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Li-Kuo Liu
- Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Wei-Ju Lee
- Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Department of Family Medicine, Yuanshan Branch, Taipei Veterans General Hospital, Yi-Lan 264, Taiwan
| | - Chih-Ping Chung
- Department of Neurology, School of Medicine, National Yang Ming University, Taipei 11221, Taiwan.,Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Albert C Yang
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, School of Medicine, National Yang Ming University, Taipei 11221, Taiwan.,Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan.,Brain Research Center, National Yang Ming University, Taipei 11221, Taiwan
| | - Liang-Kung Chen
- Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Kun-Hsien Chou
- Institute of Neuroscience, National Yang Ming University, Taipei 11221, Taiwan.,Brain Research Center, National Yang Ming University, Taipei 11221, Taiwan
| | - Ching-Po Lin
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming University, Taipei 11221, Taiwan.,Institute of Neuroscience, National Yang Ming University, Taipei 11221, Taiwan.,Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Brain Research Center, National Yang Ming University, Taipei 11221, Taiwan
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89
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Silverstein SM, Demmin DL, Schallek JB, Fradkin SI. Measures of Retinal Structure and Function as Biomarkers in Neurology and Psychiatry. Biomark Neuropsychiatry 2020. [DOI: 10.1016/j.bionps.2020.100018] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
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90
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Nelson EA, Kraguljac NV, White DM, Jindal RD, Shin AL, Lahti AC. A Prospective Longitudinal Investigation of Cortical Thickness and Gyrification in Schizophrenia. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2020; 65:381-391. [PMID: 32022594 PMCID: PMC7265602 DOI: 10.1177/0706743720904598] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Cortical thickness (CT) and gyrification are complementary indices that assess different aspects of gray matter structural integrity. Both neurodevelopment insults and acute tissue response to antipsychotic medication could underlie the known heterogeneity of treatment response and are well-suited for interrogation into the relationship between gray matter morphometry and clinical outcomes in schizophrenia (SZ). METHODS Using a prospective design, we enrolled 34 unmedicated patients with SZ and 23 healthy controls. Patients were scanned at baseline and after a 6-week trial with risperidone. CT and local gyrification index (LGI) values were quantified from structural MRI scans using FreeSurfer 5.3. RESULTS We found reduced CT and LGI in patients compared to controls. Vertex-wise analyses demonstrated that hypogyrification was most prominent in the inferior frontal cortex, temporal cortex, insula, pre/postcentral gyri, temporoparietal junction, and the supramarginal gyrus. Baseline CT was predictive of subsequent response to antipsychotic treatment, and increase in CT after 6 weeks was correlated with greater symptom reductions. CONCLUSIONS In summary, we report evidence of reduced CT and LGI in unmedicated patients compared to controls, suggesting involvement of different aspects of gray matter morphometry in the pathophysiology of SZ. Importantly, we found that lower CT at baseline and greater increase of CT following 6 weeks of treatment with risperidone were associated with better clinical response. Our results suggest that cortical thinning may normalize as a result of a good response to antipsychotic medication, possibly by alleviating potential neurotoxic processes underlying gray matter deterioration.
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Affiliation(s)
- Eric A. Nelson
- Department of Psychology, University of Alabama at Birmingham, AL, USA
| | - Nina V. Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
| | - David M. White
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
| | - Ripu D. Jindal
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
- Birmingham Veteran Affairs Medical Center, AL, USA
| | - Ah L. Shin
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
| | - Adrienne C. Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, AL, USA
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91
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Sarwar T, Seguin C, Ramamohanarao K, Zalesky A. Towards deep learning for connectome mapping: A block decomposition framework. Neuroimage 2020; 212:116654. [PMID: 32068163 DOI: 10.1016/j.neuroimage.2020.116654] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 02/09/2020] [Accepted: 02/13/2020] [Indexed: 12/13/2022] Open
Abstract
We propose a new framework to map structural connectomes using deep learning and diffusion MRI. We show that our framework not only enables connectome mapping with a convolutional neural network (CNN), but can also be straightforwardly incorporated into conventional connectome mapping pipelines to enhance accuracy. Our framework involves decomposing the entire brain volume into overlapping blocks. Blocks are sufficiently small to ensure that a CNN can be efficiently trained to predict each block's internal connectivity architecture. We develop a block stitching algorithm to rebuild the full brain volume from these blocks and thereby map end-to-end connectivity matrices. To evaluate our block decomposition and stitching (BDS) framework independent of CNN performance, we first map each block's internal connectivity using conventional streamline tractography. Performance is evaluated using simulated diffusion MRI data generated from numerical connectome phantoms with known ground truth connectivity. Due to the redundancy achieved by allowing blocks to overlap, we find that our block decomposition and stitching steps per se can enhance the accuracy of probabilistic and deterministic tractography algorithms by up to 20-30%. Moreover, we demonstrate that our framework can improve the strength of structure-function coupling between in vivo diffusion and functional MRI data. We find that structural brain networks mapped with deep learning correlate more strongly with functional brain networks (r = 0.45) than those mapped with conventional tractography (r = 0.36). In conclusion, our BDS framework not only enables connectome mapping with deep learning, but its two constituent steps can be straightforwardly incorporated as part of conventional connectome mapping pipelines to enhance accuracy.
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Affiliation(s)
- Tabinda Sarwar
- Department of Computing and Information Systems, The University of Melbourne, Victoria, 3010, Australia.
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Victoria, 3010, Australia
| | - Kotagiri Ramamohanarao
- Department of Computing and Information Systems, The University of Melbourne, Victoria, 3010, Australia
| | - Andrew Zalesky
- Department of Biomedical Engineering, The University of Melbourne, Victoria, 3010, Australia; Melbourne Neuropsychiatry Centre, The University of Melbourne, Victoria, 3010, Australia.
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92
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The effects of age and sex on cognitive impairment in schizophrenia: Findings from the Consortium on the Genetics of Schizophrenia (COGS) study. PLoS One 2020; 15:e0232855. [PMID: 32401791 PMCID: PMC7219730 DOI: 10.1371/journal.pone.0232855] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 04/22/2020] [Indexed: 01/05/2023] Open
Abstract
Recently emerging evidence indicates accelerated age-related changes in the structure and function of the brain in schizophrenia, raising a question about its potential consequences on cognitive function. Using a large sample of schizophrenia patients and controls and a battery of tasks across multiple cognitive domains, we examined whether patients show accelerated age-related decline in cognition and whether an age-related effect differ between females and males. We utilized data of 1,415 schizophrenia patients and 1,062 healthy community collected by the second phase of the Consortium on the Genetics of Schizophrenia (COGS-2). A battery of cognitive tasks included the Letter-Number Span Task, two forms of the Continuous Performance Test, the California Verbal Learning Test, Second Edition, the Penn Emotion Identification Test and the Penn Facial Memory Test. The effect of age and gender on cognitive performance was examined with a general linear model. We observed age-related changes on most cognitive measures, which was similar between males and females. Compared to controls, patients showed greater deterioration in performance on attention/vigilance and greater slowness of processing social information with increasing age. However, controls showed greater age-related changes in working memory and verbal memory compared to patients. Age-related changes (η2p of 0.001 to .008) were much smaller than between-group differences (η2p of 0.005 to .037). This study found that patients showed continued decline of cognition on some domains but stable impairment or even less decline on other domains with increasing age. These findings indicate that age-related changes in cognition in schizophrenia are subtle and not uniform across multiple cognitive domains.
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93
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Language in schizophrenia: relation with diagnosis, symptomatology and white matter tracts. NPJ SCHIZOPHRENIA 2020; 6:10. [PMID: 32313047 PMCID: PMC7171150 DOI: 10.1038/s41537-020-0099-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 02/28/2020] [Indexed: 01/04/2023]
Abstract
Language deviations are a core symptom of schizophrenia. With the advances in computational linguistics, language can be easily assessed in exact and reproducible measures. This study investigated how language characteristics relate to schizophrenia diagnosis, symptom, severity and integrity of the white matter language tracts in patients with schizophrenia and healthy controls. Spontaneous speech was recorded and diffusion tensor imaging was performed in 26 schizophrenia patients and 22 controls. We were able to classify both groups with a sensitivity of 89% and a specificity of 82%, based on mean length of utterance and clauses per utterance. Language disturbances were associated with negative symptom severity. Computational language measures predicted language tract integrity in patients (adjusted R2 = 0.467) and controls (adjusted R2 = 0.483). Quantitative language analyses have both clinical and biological validity, offer a simple, helpful marker of both severity and underlying pathology, and provide a promising tool for schizophrenia research and clinical practice.
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94
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Shafiei G, Markello RD, Makowski C, Talpalaru A, Kirschner M, Devenyi GA, Guma E, Hagmann P, Cashman NR, Lepage M, Chakravarty MM, Dagher A, Mišić B. Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture. Biol Psychiatry 2020; 87:727-735. [PMID: 31837746 DOI: 10.1016/j.biopsych.2019.09.031] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 09/04/2019] [Accepted: 09/30/2019] [Indexed: 12/25/2022]
Abstract
BACKGROUND There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown. METHODS Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 ± 12.9 years) and 113 control subjects (64 women, mean age 23.5 ± 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging. RESULTS We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex. CONCLUSIONS Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation.
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Affiliation(s)
- Golia Shafiei
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Carolina Makowski
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Alexandra Talpalaru
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Matthias Kirschner
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Gabriel A Devenyi
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Elisa Guma
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Neil R Cashman
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Martin Lepage
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - M Mallar Chakravarty
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
| | - Bratislav Mišić
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
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95
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Oxidative-Antioxidant Imbalance and Impaired Glucose Metabolism in Schizophrenia. Biomolecules 2020; 10:biom10030384. [PMID: 32121669 PMCID: PMC7175146 DOI: 10.3390/biom10030384] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 02/24/2020] [Accepted: 02/26/2020] [Indexed: 02/07/2023] Open
Abstract
Schizophrenia is a neurodevelopmental disorder featuring chronic, complex neuropsychiatric features. The etiology and pathogenesis of schizophrenia are not fully understood. Oxidative-antioxidant imbalance is a potential determinant of schizophrenia. Oxidative, nitrosative, or sulfuric damage to enzymes of glycolysis and tricarboxylic acid cycle, as well as calcium transport and ATP biosynthesis might cause impaired bioenergetics function in the brain. This could explain the initial symptoms, such as the first psychotic episode and mild cognitive impairment. Another concept of the etiopathogenesis of schizophrenia is associated with impaired glucose metabolism and insulin resistance with the activation of the mTOR mitochondrial pathway, which may contribute to impaired neuronal development. Consequently, cognitive processes requiring ATP are compromised and dysfunctions in synaptic transmission lead to neuronal death, preceding changes in key brain areas. This review summarizes the role and mutual interactions of oxidative damage and impaired glucose metabolism as key factors affecting metabolic complications in schizophrenia. These observations may be a premise for novel potential therapeutic targets that will delay not only the onset of first symptoms but also the progression of schizophrenia and its complications.
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96
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Di Biase MA, Zhang F, Lyall A, Kubicki M, Mandl RCW, Sommer IE, Pasternak O. Neuroimaging auditory verbal hallucinations in schizophrenia patient and healthy populations. Psychol Med 2020; 50:403-412. [PMID: 30782233 PMCID: PMC6702102 DOI: 10.1017/s0033291719000205] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Auditory verbal hallucinations (AVH) are a cardinal feature of schizophrenia, but they can also appear in otherwise healthy individuals. Imaging studies implicate language networks in the generation of AVH; however, it remains unclear if alterations reflect biologic substrates of AVH, irrespective of diagnostic status, age, or illness-related factors. We applied multimodal imaging to identify AVH-specific pathology, evidenced by overlapping gray or white matter deficits between schizophrenia patients and healthy voice-hearers. METHODS Diffusion-weighted and T1-weighted magnetic resonance images were acquired in 35 schizophrenia patients with AVH (SCZ-AVH), 32 healthy voice-hearers (H-AVH), and 40 age- and sex-matched controls without AVH. White matter fractional anisotropy (FA) and gray matter thickness (GMT) were computed for each region comprising ICBM-DTI and Desikan-Killiany atlases, respectively. Regions were tested for significant alterations affecting both SCZ-AVH and H-AVH groups, relative to controls. RESULTS Compared with controls, the SCZ-AVH showed widespread FA and GMT reductions; but no significant differences emerged between H-AVH and control groups. While no overlapping pathology appeared in the overall study groups, younger (<40 years) H-AVH and SCZ-AVH subjects displayed overlapping FA deficits across four regions (p < 0.05): the genu and splenium of the corpus callosum, as well as the anterior limbs of the internal capsule. Analyzing these regions with free-water imaging ascribed overlapping FA abnormalities to tissue-specific anisotropy changes. CONCLUSIONS We identified white matter pathology associated with the presence of AVH, independent of diagnostic status. However, commonalities were constrained to younger and more homogenous groups, after reducing pathologic variance associated with advancing age and chronicity effects.
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Affiliation(s)
- Maria Angelique Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Amanda Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - René C W Mandl
- Department of Psychiatry, UMC Utrecht Brain Center, Utrecht, The Netherlands
- CNSR, Mental Health Center Glostrup, Glostrup, Denmark
| | - Iris E Sommer
- Department of Neuroscience, Rijksuniversiteit Groningen (RUG), University Medical Center Groningen, Antonie Deusinglaan 2 Groningen, The Netherlands
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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97
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Using Two- and Three-Dimensional Human iPSC Culture Systems to Model Psychiatric Disorders. ADVANCES IN NEUROBIOLOGY 2020; 25:237-257. [PMID: 32578150 DOI: 10.1007/978-3-030-45493-7_9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Psychiatric disorders are among the most challenging human diseases to understand at a mechanistic level due to the heterogeneity of symptoms within established diagnostic categories, the general absence of focal pathology, and the genetic complexity inherent in these mostly polygenic disorders. Each of these features presents unique challenges to disease modeling for biological discovery, drug development, or improved diagnostics. In addition, live human neural tissue has been largely inaccessible to experimentation, leaving gaps in our knowledge derived from animal models that cannot fully recapitulate the features of the disease, indirect measures of brain function in human patients, and from analyses of postmortem tissue that can be confounded by comorbid conditions and medication history.
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98
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Koelkebeck K, Dannlowski U, Ohrmann P, Suslow T, Murai T, Bauer J, Pedersen A, Matsukawa N, Son S, Haidl T, Miyata J. Gray matter volume reductions in patients with schizophrenia: A replication study across two cultural backgrounds. Psychiatry Res Neuroimaging 2019; 292:32-40. [PMID: 31499256 DOI: 10.1016/j.pscychresns.2019.08.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 08/21/2019] [Accepted: 08/30/2019] [Indexed: 01/14/2023]
Abstract
Structural gray matter (GM) volume reductions in patients with schizophrenia have rarely been replicated across two different sites, the impact of culture and clinical characteristics remains unresolved. Hence, we assessed GM volume reductions in patients with schizophrenia using 3 T magnetic resonace imaging to replicate results across two independent and culturally different backgrounds (Germany, Japan), and to investigate the impact of brain volume reductions on clinical characteristics. In total, 163 German (80 patients) and 203 Japanese (83 patients) participants were included in the analysis. Voxel-based morphometry (VBM) was used to investigate structural differences between the groups and across the two sites, comparing local GM volumes. Clinical variables were used to analyze effects unrelated to the socio-cultural background. Across both data sets, widespread GM reductions in frontal and temporal cortical parts were found between patients and controls, indicating strong effects of diagnosis and only small effects of site. The investigation of clinical characteristics revealed the strongest effects for chlorpromazine equivalents on GM volume reductions primarily in the Japanese sample. Although the effects of site are small, several brain regions do not overlap between the two groups. Thus, GM may be affected differently at the two sites in patients with schizophrenia.
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Affiliation(s)
- Katja Koelkebeck
- Department of Psychiatry and Psychotherapy, University of Muenster, School of Medicine, Albert-Schweitzer-Campus 1, Building A9, 48149 Muenster, Germany.
| | - Udo Dannlowski
- Department of Psychiatry and Psychotherapy, University of Muenster, School of Medicine, Albert-Schweitzer-Campus 1, Building A9, 48149 Muenster, Germany
| | - Patricia Ohrmann
- Department of Psychiatry and Psychotherapy, University of Muenster, School of Medicine, Albert-Schweitzer-Campus 1, Building A9, 48149 Muenster, Germany
| | - Thomas Suslow
- University of Leipzig, Department of Psychosomatic Medicine and Psychotherapy, Semmelweisstrasse 10, 04103 Leipzig, Germany
| | - Toshiya Murai
- Department of Psychiatry, University of Kyoto, School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Jochen Bauer
- Institute of Clinical Radiology, Medical Faculty - University of Muenster - and University Hospital Muenster, Albert-Schweitzer-Campus 1, Building A1, 48149 Muenster, Germany
| | - Anya Pedersen
- Clinical Psychology and Psychotherapy, University of Kiel, Olshausenstrasse 62, 24118 Kiel, Germany
| | - Noriko Matsukawa
- Department of Psychiatry, University of Kyoto, School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Shuraku Son
- Department of Psychiatry, University of Kyoto, School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Theresa Haidl
- Department of Psychiatry and Psychotherapy, University of Cologne, Kerpener Strasse 62, 50934 Cologne, Germany
| | - Jun Miyata
- Department of Psychiatry, University of Kyoto, School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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99
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Functional brain networks in never-treated and treated long-term Ill schizophrenia patients. Neuropsychopharmacology 2019; 44:1940-1947. [PMID: 31163450 PMCID: PMC6784906 DOI: 10.1038/s41386-019-0428-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 05/19/2019] [Accepted: 05/23/2019] [Indexed: 02/05/2023]
Abstract
This study compared the topological organization of brain function in never-treated and treated long-term schizophrenia patients. In a cross-sectional study, 21 never-treated schizophrenia patients with illness duration over 5 years, 26 illness duration-matched antipsychotic-treated patients and 24 demographically-matched healthy controls underwent a resting-state functional magnetic resonance imaging (MRI) scan. The topological properties of brain functional networks were compared across groups, and then we tested for differential age-related effects in regions with significant group differences. Both never-treated and antipsychotic-treated schizophrenia patient groups showed altered nodal centralities in left pre-/postcentral gyri relative to controls. Never-treated patients demonstrated reduced global efficacy, decreased nodal centralities in right amygdala/hippocampus and bilateral putamen/caudate relative to antipsychotic-treated patients and controls. No significant relationships of age and altered functional metrics were seen in either patient group, and no alterations were greater in the treated group. These findings provide insight into brain function deficits over the longer-term course of schizophrenia independent from potential effects of antipsychotic medication. The presence of greater alterations in never-treated than treated patients suggests that long-term antipsychotic treatment may partially protect or enhance brain global and nodal topological function over the course of schizophrenia, notably involving the amygdala, hippocampus, and striatum that have long been associated with the disorder.
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100
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Madigand J, Tréhout M, Delcroix N, Dollfus S, Leroux E. Corpus callosum microstructural and macrostructural abnormalities in schizophrenia according to the stage of disease. Psychiatry Res Neuroimaging 2019; 291:63-70. [PMID: 31401547 DOI: 10.1016/j.pscychresns.2019.08.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 08/05/2019] [Accepted: 08/05/2019] [Indexed: 12/17/2022]
Abstract
Corpus callosum (CC) volume and surface (macrostructural) studies remain controversial and have not considered the illness duration (ID) systematically. Regardless of ID, some CC macrostructural studies have shown no difference between SZ patients and healthy controls (HC), whereas others have reported macrostructural abnormalities in SZ. Conversely, CC microstructural studies are more in agreement with alterations in CC integrity regardless of the patients' ID, but the direction and degree of these abnormalities over time remain unknown. Moreover, no study has explored both the micro- and macrostructure of the CC in SZ by considering the stage of disease. Both CC micro- and macrostructural data were investigated in 43 SZ patients and compared between two patient groups (21 patients with a short ID and 22 with a long ID) and HC (23 participants) using diffusion tensor and structural imaging. CC microstructural alterations were detected in both SZ groups compared to the HC group, without differences between the SZ groups. In contrast, CC macrostructural alterations were only found in the long ID group. CC microstructural alterations might be detected in schizophrenia at an early stage, without an increase of magnitude thereafter, while CC macrostructural alterations might become apparent at later stages of the illness.
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Affiliation(s)
- Jérémy Madigand
- Normandie Univ, UNICAEN, ISTS EA 7466, GIP CYCERON, Caen F-14000, France; CHU de Caen, Service de psychiatrie Adulte, Centre Esquirol, Caen F-14000, France; Normandie Univ, UNICAEN, UFR de Médecine (Medical School), Caen F-14000, France.
| | - Maxime Tréhout
- Normandie Univ, UNICAEN, ISTS EA 7466, GIP CYCERON, Caen F-14000, France; CHU de Caen, Service de psychiatrie Adulte, Centre Esquirol, Caen F-14000, France; Normandie Univ, UNICAEN, UFR de Médecine (Medical School), Caen F-14000, France.
| | - Nicolas Delcroix
- Normandie Univ, UNICAEN, CNRS, UMS GIP CYCERON, Caen F-14000, France.
| | - Sonia Dollfus
- Normandie Univ, UNICAEN, ISTS EA 7466, GIP CYCERON, Caen F-14000, France; CHU de Caen, Service de psychiatrie Adulte, Centre Esquirol, Caen F-14000, France; Normandie Univ, UNICAEN, UFR de Médecine (Medical School), Caen F-14000, France.
| | - Elise Leroux
- Normandie Univ, UNICAEN, ISTS EA 7466, GIP CYCERON, Caen F-14000, France.
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