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Dini H, Bruni LE, Ramsøy TZ, Calhoun VD, Sendi MSE. The overlap across psychotic disorders: A functional network connectivity analysis. Int J Psychophysiol 2024; 201:112354. [PMID: 38670348 PMCID: PMC11163820 DOI: 10.1016/j.ijpsycho.2024.112354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 03/20/2024] [Accepted: 04/20/2024] [Indexed: 04/28/2024]
Abstract
Functional network connectivity (FNC) has previously been shown to distinguish patient groups from healthy controls (HC). However, the overlap across psychiatric disorders such as schizophrenia (SZ), bipolar (BP), and schizoaffective disorder (SAD) is not evident yet. This study focuses on studying the overlap across these three psychotic disorders in both dynamic and static FNC (dFNC/sFNC). We used resting-state fMRI, demographics, and clinical information from the Bipolar-Schizophrenia Network on Intermediate Phenotypes cohort (BSNIP). The data includes three groups of patients with schizophrenia (SZ, N = 181), bipolar (BP, N = 163), and schizoaffective (SAD, N = 130) and HC (N = 238) groups. After estimating each individual's dFNC, we group them into three distinct states. We evaluated two dFNC features, including occupancy rate (OCR) and distance travelled over time. Finally, the extracted features, including both sFNC and dFNC, are tested statistically across patients and HC groups. In addition, we explored the link between the clinical scores and the extracted features. We evaluated the connectivity patterns and their overlap among SZ, BP, and SAD disorders (false discovery rate or FDR corrected p < 0.05). Results showed dFNC captured unique information about overlap across disorders where all disorder groups showed similar pattern of activity in state 2. Moreover, the results showed similar patterns between SZ and SAD in state 1 which was different than BP. Finally, the distance travelled feature of SZ (average R = 0.245, p < 0.01) and combined distance travelled from all disorders was predictive of the PANSS symptoms scores (average R = 0.147, p < 0.01).
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Affiliation(s)
- Hossein Dini
- Augmented Cognition Lab, Department of Architecture, Design and Media Technology, Aalborg University, Copenhagen, Denmark
| | - Luis E Bruni
- Augmented Cognition Lab, Department of Architecture, Design and Media Technology, Aalborg University, Copenhagen, Denmark
| | - Thomas Z Ramsøy
- Department of Applied Neuroscience, Neurons Inc., Taastrup, Denmark; Faculty of Neuroscience, Singularity University, Santa Clara, CA, United States
| | - Vince D Calhoun
- Wallace H. Coulter Department of Biomedical Engineering at, Georgia Institute of Technology and Emory University, Atlanta, GA, United States; Department of Electrical and Computer Engineering at, Georgia Institute of Technology, Atlanta, GA, United States; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Mohammad S E Sendi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States; McLean Hospital and Harvard Medical School, Boston, MA, USA.
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Yan H, Li G, Zhang X, Zhang C, Li M, Qiu Y, Sun W, Dong Y, Li S, Li J. Targeted metabolomics-based understanding of the sleep disturbances in drug-naïve patients with schizophrenia. BMC Psychiatry 2024; 24:355. [PMID: 38741058 DOI: 10.1186/s12888-024-05805-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 04/30/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Sleep disturbances are a common occurrence in patients with schizophrenia, yet the underlying pathogenesis remain poorly understood. Here, we performed a targeted metabolomics-based approach to explore the potential biological mechanisms contributing to sleep disturbances in schizophrenia. METHODS Plasma samples from 59 drug-naïve patients with schizophrenia and 36 healthy controls were subjected to liquid chromatography-mass spectrometry (LC-MS) targeted metabolomics analysis, allowing for the quantification and profiling of 271 metabolites. Sleep quality and clinical symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS), respectively. Partial correlation analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) model were used to identify metabolites specifically associated with sleep disturbances in drug-naïve schizophrenia. RESULTS 16 characteristic metabolites were observed significantly associated with sleep disturbances in drug-naïve patients with schizophrenia. Furthermore, the glycerophospholipid metabolism (Impact: 0.138, p<0.001), the butanoate metabolism (Impact: 0.032, p=0.008), and the sphingolipid metabolism (Impact: 0.270, p=0.104) were identified as metabolic pathways associated with sleep disturbances in drug-naïve patients with schizophrenia. CONCLUSIONS Our study identified 16 characteristic metabolites (mainly lipids) and 3 metabolic pathways related to sleep disturbances in drug-naïve schizophrenia. The detection of these distinct metabolites provide valuable insights into the underlying biological mechanisms associated with sleep disturbances in schizophrenia.
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Affiliation(s)
- Huiming Yan
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Gang Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
- Chifeng Anding Hospital, NO.18 Gongger Street, Hongshan District, Chifeng City, 024000, Inner Mongolia Autonomous Region, China
| | - Xue Zhang
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
- Chifeng Anding Hospital, NO.18 Gongger Street, Hongshan District, Chifeng City, 024000, Inner Mongolia Autonomous Region, China
| | - Chuhao Zhang
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Meijuan Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Yuying Qiu
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Wei Sun
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Yeqing Dong
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China
| | - Shen Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China.
| | - Jie Li
- Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China.
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Chen MY, Wang YY, Si TL, Liu YF, Su Z, Cheung T, Ungvari GS, Jackson T, Zhang Q, Xiang YT. Poor sleep quality in schizophrenia patients: A systematic review and meta-analyses of epidemiological and case-control studies. Schizophr Res 2024; 264:407-415. [PMID: 38241784 DOI: 10.1016/j.schres.2024.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 12/18/2023] [Accepted: 01/01/2024] [Indexed: 01/21/2024]
Abstract
OBJECTIVE Poor sleep quality is common in patients with schizophrenia but estimated prevalence rates in this population have been mixed. This systematic review and meta-analysis examined the prevalence of poor sleep quality in schizophrenia samples and moderators of prevalence from epidemiological studies as well as the risk of poor sleep quality in schizophrenia patients based on case-control studies. METHODS Both international (PubMed, Web of Science, PsycINFO, EMBASE) and Chinese databases [Chinese Nation knowledge Infrastructure (CNKI) and WANFANG] were systematically searched. Studies that estimated the prevalence of poor sleep quality in schizophrenia were analyzed using a random effects model. Funnel plots and Egger's tests were used to assess publication bias. Statistical analyses were performed using R software. RESULTS In total, 23 epidemiological studies and nine case-control studies were included. Based on the epidemiological studies, the pooled overall prevalence of poor sleep quality was 63.4 % [95 % confidence interval (CI): 57.0 %-69.9 %]. Additionally, based on the nine case-control studies, schizophrenia patients had a significantly higher risk for poor sleep quality compared to healthy controls [odd ratio (OR) = 4.5; 95%CI: 2.4-8.3; P < 0.0001]. CONCLUSION Poor sleep quality is common among schizophrenia patients. Considering negative outcomes caused by poor sleep quality, regular screening on poor sleep quality should be conducted and effective interventions should be provided to those in need.
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Affiliation(s)
- Meng-Yi Chen
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China; Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China
| | - Yue-Ying Wang
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China
| | - Tong Leong Si
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China
| | - Yu-Fei Liu
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China
| | - Zhaohui Su
- School of Public Health, Southeast University, Nanjing, China
| | - Teris Cheung
- School of Nursing, Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Gabor S Ungvari
- University of Notre Dame Australia, Fremantle, Australia; Division of Psychiatry, School of Medicine, University of Western Australia, Perth, Australia
| | - Todd Jackson
- Department of Psychology, University of Macau, Macao SAR, China
| | - Qinge Zhang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Yu-Tao Xiang
- Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China; Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China.
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Demirlek C, Bora E. Sleep-dependent memory consolidation in schizophrenia: A systematic review and meta-analysis. Schizophr Res 2023; 254:146-154. [PMID: 36889181 DOI: 10.1016/j.schres.2023.02.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 02/06/2023] [Accepted: 02/27/2023] [Indexed: 03/10/2023]
Abstract
Sleep disturbances and cognitive impairment are both persistent and common features of schizophrenia. Accumulating evidence indicates that sleep-dependent memory consolidation might be impaired in patients with schizophrenia compared to healthy controls. The current systematic review was performed in accordance with PRISMA guidelines. A random-effects model was used to calculate effect sizes (Hedge's g). In the quantitative review, three separate meta-analyses were conducted for procedural memory in healthy controls, schizophrenia, and comparison between healthy controls and schizophrenia. Additionally, separate meta-analyses were conducted for the studies using finger tapping motor sequence task, as it is the most commonly used task. The current systematic review included 14 studies including 304 patients with schizophrenia and 209 healthy controls. The random-effects model analyses for sleep-dependent procedural memory consolidation resulted in a small effect size in schizophrenia (g = 0.26), a large effect size in healthy controls (g = 0.98), a moderate effect size in healthy controls vs schizophrenia (g = 0.64). For the studies using finger tapping motor sequence task, meta-analyses resulted in a small effect size in schizophrenia (g = 0.19), a large effect size in healthy controls (g = 1.07), a moderate effect size in healthy controls vs schizophrenia (g = 0.70). In the qualitative review, there was also impaired sleep-dependent declarative memory consolidation in schizophrenia compared to healthy controls. Current findings support that sleep improves memory consolidation in healthy adults, but there is a deficit in sleep-dependent memory consolidation in people with schizophrenia. Future studies investigating sleep-dependent consolidation of different memory subtypes with polysomnography in different stages of psychotic disorders are needed.
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Affiliation(s)
- Cemal Demirlek
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey.
| | - Emre Bora
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey; Department of Psychiatry, Dokuz Eylul University Medical School, Izmir, Turkey; Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Carlton South, Victoria 3053, Australia
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