1
|
Oomen PP, Begemann MJH, Brand BA, de Haan L, Veling W, Koops S, van Os J, Smit F, Bakker PR, van Beveren N, Boonstra N, Gülöksüz S, Kikkert M, Lokkerbol J, Marcelis M, Rosema BS, de Beer F, Gangadin SS, Geraets CNW, van ‘t Hag E, Haveman Y, van der Heijden I, Voppel AE, Willemse E, van Amelsvoort T, Bak M, Batalla A, Been A, van den Bosch M, van den Brink T, Faber G, Grootens KP, de Jonge M, Knegtering R, Kurkamp J, Mahabir A, Pijnenborg GHM, Staring T, Veen N, Veerman S, Wiersma S, Graveland E, Hoornaar J, Sommer IEC. Longitudinal clinical and functional outcome in distinct cognitive subgroups of first-episode psychosis: a cluster analysis. Psychol Med 2023; 53:2317-2327. [PMID: 34664546 PMCID: PMC10123843 DOI: 10.1017/s0033291721004153] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/16/2021] [Accepted: 09/23/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Cognitive deficits may be characteristic for only a subgroup of first-episode psychosis (FEP) and the link with clinical and functional outcomes is less profound than previously thought. This study aimed to identify cognitive subgroups in a large sample of FEP using a clustering approach with healthy controls as a reference group, subsequently linking cognitive subgroups to clinical and functional outcomes. METHODS 204 FEP patients were included. Hierarchical cluster analysis was performed using baseline brief assessment of cognition in schizophrenia (BACS). Cognitive subgroups were compared to 40 controls and linked to longitudinal clinical and functional outcomes (PANSS, GAF, self-reported WHODAS 2.0) up to 12-month follow-up. RESULTS Three distinct cognitive clusters emerged: relative to controls, we found one cluster with preserved cognition (n = 76), one moderately impaired cluster (n = 74) and one severely impaired cluster (n = 54). Patients with severely impaired cognition had more severe clinical symptoms at baseline, 6- and 12-month follow-up as compared to patients with preserved cognition. General functioning (GAF) in the severely impaired cluster was significantly lower than in those with preserved cognition at baseline and showed trend-level effects at 6- and 12-month follow-up. No significant differences in self-reported functional outcome (WHODAS 2.0) were present. CONCLUSIONS Current results demonstrate the existence of three distinct cognitive subgroups, corresponding with clinical outcome at baseline, 6- and 12-month follow-up. Importantly, the cognitively preserved subgroup was larger than the severely impaired group. Early identification of discrete cognitive profiles can offer valuable information about the clinical outcome but may not be relevant in predicting self-reported functional outcomes.
Collapse
Affiliation(s)
- Priscilla P. Oomen
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marieke J. H. Begemann
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Bodyl A. Brand
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Lieuwe de Haan
- Department of Early Psychosis, Amsterdam UMC, Academic Medical Center, Amsterdam, The Netherlands
| | - Wim Veling
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sanne Koops
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jim van Os
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MheNS), Maastricht University Medical Centre, Maastricht, The Netherlands
- King's College London, King's Health Partners Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Filip Smit
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
- Department of Clinical, Neuro and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
- Centre of Economic Evaluation & Machine Learning, Trimbos Institute (Netherlands Institute of Mental Health), Utrecht, The Netherlands
| | - P. Roberto Bakker
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MheNS), Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Research, Arkin Mental Health Care, Amsterdam, The Netherlands
| | - Nico van Beveren
- Antes Center for Mental Health Care, Rotterdam, The Netherlands
- Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands
- Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands
| | - Nynke Boonstra
- NHL/Stenden, University of Applied Sciences, Leeuwarden, The Netherlands
- KieN VIP Mental Health Care Services, Leeuwarden, The Netherlands
| | - Sinan Gülöksüz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MheNS), Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Martijn Kikkert
- Department of Research, Arkin Mental Health Care, Amsterdam, The Netherlands
| | - Joran Lokkerbol
- Centre of Economic Evaluation & Machine Learning, Trimbos Institute (Netherlands Institute of Mental Health), Utrecht, The Netherlands
| | - Machteld Marcelis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Center, Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
| | - Bram-Sieben Rosema
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Franciska de Beer
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Shiral S. Gangadin
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Chris N. W. Geraets
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Erna van ‘t Hag
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Yudith Haveman
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Inge van der Heijden
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Janssen-Cilag B.V., Breda, the Netherlands
| | - Alban E. Voppel
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Elske Willemse
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MheNS), Maastricht University Medical Centre, Maastricht, The Netherlands
- Mondriaan Mental Health Care, Heerlen, The Netherlands
| | - Maarten Bak
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MheNS), Maastricht University Medical Centre, Maastricht, The Netherlands
- Mondriaan Mental Health Care, Heerlen, The Netherlands
| | - Albert Batalla
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Agaath Been
- Dimence Institute for Mental Health, Deventer, Zwolle, The Netherlands
| | | | | | - Gunnar Faber
- Yulius, Mental Health Institute, Dordrecht, The Netherlands
| | - Koen P. Grootens
- Reinier van Arkel Institute for Mental Health Care, ‘s Hertogenbosch, The Netherlands
| | - Martin de Jonge
- Program for Psychosis & Severe Mental Illness, Pro Persona Mental Health, Wolfheze, The Netherlands
| | - Rikus Knegtering
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Lentis Research, Lentis Psychiatric Institute, Groningen, The Netherlands
| | - Jörg Kurkamp
- Center for Youth with Psychosis, Mediant ABC Twente, Enschede, The Netherlands
| | | | - Gerdina H. M. Pijnenborg
- Department of Psychotic Disorders, GGZ-Drenthe, Assen, The Netherlands
- Department of Clinical and Developmental Neuropsychology, Faculty BSS, University of Groningen, Groningen, The Netherlands
| | - Tonnie Staring
- Department ABC Early Psychosis, Altrecht Psychiatric Institute, Utrecht, The Netherlands
| | - Natalie Veen
- GGZ Delfland, Delfland Institute for Mental Health Care, Delft, The Netherlands
| | - Selene Veerman
- Community Mental Health, Mental Health Service Noord-Holland Noord, Alkmaar, The Netherlands
| | - Sybren Wiersma
- Early Intervention Psychosis Team, GGZ inGeest Specialized Mental Health Care, Hoofddorp, The Netherlands
| | | | - Joelle Hoornaar
- Antes Center for Mental Health Care, Rotterdam, The Netherlands
| | - Iris E. C. Sommer
- Department of Biomedical Sciences of Cells and Systems, and Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| |
Collapse
|
2
|
Liang C, Pearlson G, Bustillo J, Kochunov P, Turner JA, Wen X, Jiang R, Fu Z, Zhang X, Li K, Xu X, Zhang D, Qi S, Calhoun VD. Psychotic Symptom, Mood, and Cognition-associated Multimodal MRI Reveal Shared Links to the Salience Network Within the Psychosis Spectrum Disorders. Schizophr Bull 2023; 49:172-184. [PMID: 36305162 PMCID: PMC9810025 DOI: 10.1093/schbul/sbac158] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Schizophrenia (SZ), schizoaffective disorder (SAD), and psychotic bipolar disorder share substantial overlap in clinical phenotypes, associated brain abnormalities and risk genes, making reliable diagnosis among the three illness challenging, especially in the absence of distinguishing biomarkers. This investigation aims to identify multimodal brain networks related to psychotic symptom, mood, and cognition through reference-guided fusion to discriminate among SZ, SAD, and BP. Psychotic symptom, mood, and cognition were used as references to supervise functional and structural magnetic resonance imaging (MRI) fusion to identify multimodal brain networks for SZ, SAD, and BP individually. These features were then used to assess the ability in discriminating among SZ, SAD, and BP. We observed shared links to functional and structural covariation in prefrontal, medial temporal, anterior cingulate, and insular cortices among SZ, SAD, and BP, although they were linked with different clinical domains. The salience (SAN), default mode (DMN), and fronto-limbic (FLN) networks were the three identified multimodal MRI features within the psychosis spectrum disorders from psychotic symptom, mood, and cognition associations. In addition, using these networks, we can classify patients and controls and distinguish among SZ, SAD, and BP, including their first-degree relatives. The identified multimodal SAN may be informative regarding neural mechanisms of comorbidity for psychosis spectrum disorders, along with DMN and FLN may serve as potential biomarkers in discriminating among SZ, SAD, and BP, which may help investigators better understand the underlying mechanisms of psychotic comorbidity from three different disorders via a multimodal neuroimaging perspective.
Collapse
Affiliation(s)
- Chuang Liang
- Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Godfrey Pearlson
- Department of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Juan Bustillo
- Departments of Neurosciences and Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jessica A Turner
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Xuyun Wen
- Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Rongtao Jiang
- Department of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Xiao Zhang
- Department of Psychiatry, Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xijia Xu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Daoqiang Zhang
- Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Shile Qi
- Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Vince D Calhoun
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Electrical and Computer Engineering, Georgia Tech University, Atlanta, GA, USA
| |
Collapse
|
3
|
Hasse-Sousa M, Martins DS, Petry-Perin C, Britto MJSD, Remus IB, Lapa CDO, Reckziegel RDFX, Sales SCD, Jesus LSD, Philippsen M, Massuda R, Van Rheenen TE, Gama CS, Czepielewski LS. The role of semantic clustering in the relationship between verbal memory and psychosocial functioning in schizophrenia and bipolar disorder: Possible distinct cognitive pathway compared to healthy controls. J Affect Disord 2023; 320:330-339. [PMID: 36162669 DOI: 10.1016/j.jad.2022.09.077] [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: 11/24/2021] [Revised: 09/02/2022] [Accepted: 09/20/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Verbal memory (VM) is impaired in schizophrenia (SZ) and bipolar disorder (BD), and predicts psychosocial functioning. However, there is a lack of research exploring the role of VM component processes, including semantic clustering, in these disorders. Semantic clustering might impact this association, as effective semantic memory strategies may reflect unimpaired executive control, leading to an adequate functioning. We aimed to investigate VM components in SZ and BD, and the role of semantic clustering in the relationship between VM and functioning. METHODS We included 495 participants (156 SZ, 172 BD, and 167 healthy controls (HC)) that underwent an assessment using the Hopkins Verbal Learning Test - Revised for VM and the Functioning Assessment Short Test for psychosocial functioning. We compared groups through ANOVAs and investigated the effect of semantic clustering in the relationship between VM total immediate free recall and functioning through linear regression models. RESULTS SZ had worse overall VM performance compared to BD, which performed worse than HCs. HCs used more semantic clustering than SZ and BD, but there were no differences between the two clinical groups. In HCs, semantic clustering impacted the relationship between VM performance and functioning, while no interaction was observed in SZ or BD. LIMITATIONS Cross-sectional design; no medication effects or other cognitive functions were assessed. CONCLUSIONS SZ and BD may use an alternative cognitive pathway in which the relationship between VM and functioning is independent of complex cognitive processes such as semantic clustering, supporting the cognitive remediation targeting of VM in these disorders.
Collapse
Affiliation(s)
- Mathias Hasse-Sousa
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós-Graduação em Psicologia, Departamento de Psicologia do Desenvolvimento e da Personalidade, Instituto de Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Dayane Santos Martins
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Carolina Petry-Perin
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Maria Julia Silva de Britto
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Isadora Bosini Remus
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Clara de Oliveira Lapa
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Ramiro de Freitas Xavier Reckziegel
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Sarah Corrêa de Sales
- Psychosis Treatment and Research Program, Department of Forensic Medicine and Psychiatry, Universidade Federal do Paraná (UFPR), Curitiba, Brazil
| | - Letícia Stephane de Jesus
- Psychosis Treatment and Research Program, Department of Forensic Medicine and Psychiatry, Universidade Federal do Paraná (UFPR), Curitiba, Brazil
| | - Marielli Philippsen
- Psychosis Treatment and Research Program, Department of Forensic Medicine and Psychiatry, Universidade Federal do Paraná (UFPR), Curitiba, Brazil
| | - Raffael Massuda
- Psychosis Treatment and Research Program, Department of Forensic Medicine and Psychiatry, Universidade Federal do Paraná (UFPR), Curitiba, Brazil
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC, Australia; Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, VIC, Australia
| | - Clarissa Severino Gama
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Letícia Sanguinetti Czepielewski
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre; Programa de Pós-Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Programa de Pós-Graduação em Psicologia, Departamento de Psicologia do Desenvolvimento e da Personalidade, Instituto de Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
| |
Collapse
|
4
|
Martins DS, Hasse-Sousa M, Reckziegel RDFX, Lapa CDO, Petry-Perin C, Britto MJ, Remus IB, Gama CS, Czepielewski LS. A five-year follow-up of the verbal memory performance of individuals with bipolar disorder and schizophrenia: evidence of unchanging deficits under treatment. Cogn Neuropsychiatry 2023; 28:19-35. [PMID: 36254742 DOI: 10.1080/13546805.2022.2133694] [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] [Indexed: 11/03/2022]
Abstract
OBJECTIVE Bipolar disorder (BD) and schizophrenia (SZ) are chronic and heterogeneous mental disorders that present cognitive and functional impairments. Verbal memory is considered an important predictor of functioning and a domain vulnerable to the aging process. However, only few studies investigate the progression of memory longitudinally in BD and SZ, especially in lower- and middle-income countries. Therefore, we aim to evaluate the course of verbal memory in individuals with BD and SZ. METHODS We assessed 31 individuals with BD and 27 individuals with SZ under treatment at outpatient clinics at baseline and after five years. They were assessed through a sociodemographic questionnaire, memory and estimated IQ (eIQ) instruments, and clinical scales. RESULTS Individuals with SZ showed worse verbal memory performance in comparison to BD, however, we did not observe changes over time within patient groups. Individuals with BD with higher eIQ showed a better verbal memory performance, while no effect of eIQ was found for subjects with SZ. CONCLUSION Patients with SZ and BD showed different levels of verbal memory impairment, although they had similar unchanging trajectories after 5 years under psychiatric treatment. This finding indicates a relative stable cognitive course for both disorders.
Collapse
Affiliation(s)
- Dayane Santos Martins
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Mathias Hasse-Sousa
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Programa de Pós-Graduação em Psicologia, Departamento de Psicologia do Desenvolvimento e da Personalidade, Instituto de Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Ramiro de Freitas Xavier Reckziegel
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Clara de Olivera Lapa
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Carolina Petry-Perin
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Maria Julia Britto
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Isadora Bosini Remus
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Clarissa Severino Gama
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Programa de Pós Graduação em Psiquiatria e Ciências do Comportamento, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Leticia Sanguinetti Czepielewski
- Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Programa de Pós-Graduação em Psicologia, Departamento de Psicologia do Desenvolvimento e da Personalidade, Instituto de Psicologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| |
Collapse
|
5
|
Miles S, Nedeljkovic M, Sumner P, Phillipou A. Understanding self-report and neurocognitive assessments of cognitive flexibility in people with and without lifetime anorexia nervosa. Cogn Neuropsychiatry 2022; 27:325-341. [PMID: 35142252 DOI: 10.1080/13546805.2022.2038554] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Objective: Anorexia nervosa (AN) is a serious eating disorder associated with several cognitive difficulties including poor cognitive flexibility (i.e. difficulties in effectively adapting to changes in the environment and/or changing task demands). AN research has primarily assessed cognitive flexibility using neurocognitive tests, and little is known about the differences or similarities between self-report and neurocognitive assessments of cognitive flexibility. This study investigated the relationship between self-report and neurocognitive assessments of cognitive flexibility in people with no history of an eating disorder (n = 207) and people with a self-reported lifetime diagnosis of AN (n = 19).Methods: Participants completed self-report and neurocognitive assessments of cognitive flexibility through an online study.Results: No significant correlations were found between self-report and neurocognitive assessments of cognitive flexibility for either group of the sample, suggesting that these assessments may evaluate different aspects of cognitive flexibility. Further, negative mood and self-reported eating disorder symptoms were found to significantly relate to self-reported cognitive flexibility, but were not associated with performance on neurocognitive tests of cognitive flexibility.Conclusions: To provide a comprehensive understanding of perceived and objective cognitive flexibility in AN, future research and clinical assessments should include both self-report and neurocognitive assessments.
Collapse
Affiliation(s)
- Stephanie Miles
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
| | - Maja Nedeljkovic
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
| | - Andrea Phillipou
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia.,Department of Mental Health, St Vincent's Hospital, Melbourne, Australia.,Department of Psychiatry, The University of Melbourne, Melbourne, Australia.,Department of Mental Health, Austin Health, Melbourne, Australia
| |
Collapse
|
6
|
Miles S, Phillipou A, Sumner P, Nedeljkovic M. Cognitive flexibility and the risk of anorexia nervosa: An investigation using self-report and neurocognitive assessments. J Psychiatr Res 2022; 151:531-538. [PMID: 35636028 DOI: 10.1016/j.jpsychires.2022.05.043] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 02/28/2022] [Accepted: 05/20/2022] [Indexed: 10/18/2022]
Abstract
Impaired cognitive flexibility has been suggested as a risk factor for the development of anorexia nervosa (AN). The current study aimed to 1) investigate cognitive flexibility in people at various levels of risk of AN; and 2) compare people with a history of AN to people at different levels of risk of AN in cognitive flexibility. The sample comprised of 262 community participants (79% female) and 36 participants with a lifetime diagnosis of AN (97.2% female) aged between 18 and 64 years old. Participants completed self-report (the Depression Anxiety Stress Scale short-form version, the Eating Disorders Examination-Questionnaire, the Neuroticism Scale, and the Cognitive Flexibility Inventory) and neurocognitive (the Trail Making Test and the Wisconsin Card Sorting Test) assessments online to evaluate eating disorder symptoms, depression, neuroticism, and cognitive flexibility. Using a cluster analysis, participants were allocated into low-, medium-, and high-risk of AN groups (n = 88, 128, 46, and 36 respectively). Although high-risk participants self-reported significantly poorer cognitive flexibility than the other risk groups, performance on the neurocognitive tasks was similar across groups. Further, participants with lifetime AN reported significantly poorer cognitive flexibility than the low-risk group. People at high-risk of AN may perceive themselves to have poorer cognitive flexibility compared to those at a lower risk of AN. These results have implications for early identification of people at high-risk of AN.
Collapse
Affiliation(s)
- Stephanie Miles
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Victoria, Australia.
| | - Andrea Phillipou
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Victoria, Australia; Department of Mental Health, St Vincent's Hospital, Melbourne, Victoria, Australia; Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia; Department of Mental Health, Austin Health, Melbourne, Victoria, Australia
| | - Philip Sumner
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Victoria, Australia
| | - Maja Nedeljkovic
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Victoria, Australia
| |
Collapse
|
7
|
A neuropsychological study on Leonhard's nosological system. Eur Arch Psychiatry Clin Neurosci 2022; 272:427-436. [PMID: 34269880 DOI: 10.1007/s00406-021-01298-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 07/04/2021] [Indexed: 12/17/2022]
Abstract
Phenotype validation of endogenous psychosis is a problem that remains to be solved. This study investigated the neuropsychological performance of endogenous psychosis subtypes according to Wernicke-Kleist-Leonhard's classification system (WKL). The participants included consecutive admissions of patients with schizophrenia spectrum disorder or mood disorder with psychotic symptoms (N = 98) and healthy comparison subjects (N = 50). The patients were assessed by means of semi-structured interviews and diagnosed through the WKL system into three groups: a manic-depressive illness and cycloid psychosis group (MDC), unsystematic schizophrenia (USch) and systematic schizophrenia (SSch). All the participants completed a comprehensive neuropsychological battery. The three Leonhard's psychosis subtypes showed a common neuropsychological profile with differences in the severity of impairment relative to healthy controls. MDC patients showed better performance on premorbid intelligence, verbal memory and global cognitive index than USch and SSch patients, and they showed better performance on processing speed, and working memory than SSch patients. USch patients outperformed SSch patients in verbal memory, working memory and global cognitive index. Neuropsychological performance showed a modest accuracy for classification into the WKL nosology. Our results suggest the existence of a common profile of cognitive impairment cutting across WKL subtypes of endogenous psychosis but with significant differences on a severity continuum. In addition, classification accuracy in the three WKL subtypes by means of neuropsychological performance was modest, ranging between 40 and 64% of correctly classified patients.
Collapse
|
8
|
Oomen PP, Gangadin SS, Begemann MJH, Visser E, Mandl RCW, Sommer IEC. The neurobiological characterization of distinct cognitive subtypes in early-phase schizophrenia-spectrum disorders. Schizophr Res 2022; 241:228-237. [PMID: 35176721 DOI: 10.1016/j.schres.2022.02.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 01/28/2022] [Accepted: 02/04/2022] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Cognitive deficits are present in some, but not all patients with schizophrenia-spectrum disorders (SSD). We and others have demonstrated three cognitive clusters: cognitively intact patients, patients with deficits in a few domains and those with global cognitive deficits. This study aimed to identify cognitive subtypes of early-phase SSD with matched controls as a reference group, and evaluated cognitive subgroups regarding clinical and brain volumetric measures. METHODS Eighty-six early-phase SSD patients were included. Hierarchical cluster analysis was conducted using global performance on the Brief Assessment of Cognition in Schizophrenia (BACS). Cognitive subgroups were subsequently related to clinical and brain volumetric measures (cortical, subcortical and cortical thickness) using ANCOVA. RESULTS Three distinct cognitive clusters emerged: relative to controls we found one cluster of patients with preserved cognition (n = 25), one moderately impaired cluster (n = 38) and one severely impaired cluster (n = 23). Cognitive subgroups were characterized by differences in volume of the left postcentral gyrus, left middle caudal frontal gyrus and left insula, while differences in cortical thickness were predominantly found in fronto-parietal regions. No differences were demonstrated in subcortical brain volume. DISCUSSION Current results replicate the existence of three distinct cognitive subgroups including one relatively large group with preserved cognitive function. Cognitive subgroups were characterized by differences in cortical regional brain volume and cortical thickness, suggesting associations with cortical, but not subcortical development and cognitive functioning such as attention, executive functions and speed of processing.
Collapse
Affiliation(s)
- P P Oomen
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands.
| | - S S Gangadin
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - M J H Begemann
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - E Visser
- Department of Psychiatry, University Medical Center, Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - R C W Mandl
- Department of Psychiatry, University Medical Center, Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - I E C Sommer
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| |
Collapse
|
9
|
Mondragón-Maya A, Flores-Medina Y, Silva-Pereyra J, Ramos-Mastache D, Yáñez-Téllez G, Escamilla-Orozco R, Saracco-Álvarez R. Neurocognition in Bipolar and Depressive Schizoaffective Disorder: A Comparison with Schizophrenia. Neuropsychobiology 2021; 80:45-51. [PMID: 32516783 DOI: 10.1159/000508188] [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: 10/30/2019] [Accepted: 04/18/2020] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Schizoaffective disorder (SA) is classified into bipolar (bSA) and depressive (dSA) subtypes. Although clinical differences between both have been reported, there is no clear information regarding their specific cognitive profile. OBJECTIVE To compare neurocognition between SA subtypes and schizophrenia (SC). METHODS A total of 61 patients were assessed and divided into 3 groups: 35 SC, 16 bSA, and 10 dSA. All participants signed an informed consent letter. The MATRICS Consensus Cognitive Battery, Central and South American version was used to assess neurocognition. The study was performed at the Instituto Nacional de Psiquiatría "Ramón de la Fuente". Participants were identified by specialized psychiatrists. Trained neuropsychologists carried out the clinical and cognitive assessment, which lasted 2 h approximately. RESULTS The cognitive assessment showed a significant difference in Trail Making Test part A subtest (F[2,58] = 4.043; p = 0.023]. Post hoc analyses indicated that dSA obtained a significantly higher score than SC (MD = -11.523; p = 0.018). The f test showed a large effect size (f = 0.401). No statistical differences were observed regarding other cognitive variables. CONCLUSIONS The cognitive profile of SA subtypes and SC is similar since no differences were found in most subtests. However, dSA may be less impaired than SC in measures of processing speed. Further research with larger samples must be conducted.
Collapse
Affiliation(s)
- Alejandra Mondragón-Maya
- Carrera de Psicología, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla de Baz, Mexico,
| | - Yvonne Flores-Medina
- Servicio de Rehabilitación, Instituto Nacional de Psiquiatría "Ramón de la Fuente", Mexico City, Mexico
| | - Juan Silva-Pereyra
- Proyecto de Neurociencias, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla de Baz, Mexico
| | - Daniela Ramos-Mastache
- Residencia en Neuropsicología Clínica, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla de Baz, Mexico
| | - Guillermina Yáñez-Téllez
- Proyecto de Neurociencias, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Tlalnepantla de Baz, Mexico
| | - Raúl Escamilla-Orozco
- Servicios clínicos, Instituto Nacional de Psiquiatría "Ramón de la Fuente", Mexico City, Mexico
| | - Ricardo Saracco-Álvarez
- Servicios clínicos, Instituto Nacional de Psiquiatría "Ramón de la Fuente", Mexico City, Mexico
| |
Collapse
|
10
|
Karantonis JA, Carruthers SP, Rossell SL, Pantelis C, Hughes M, Wannan C, Cropley V, Van Rheenen TE. A Systematic Review of Cognition-Brain Morphology Relationships on the Schizophrenia-Bipolar Disorder Spectrum. Schizophr Bull 2021; 47:1557-1600. [PMID: 34097043 PMCID: PMC8530395 DOI: 10.1093/schbul/sbab054] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The nature of the relationship between cognition and brain morphology in schizophrenia-spectrum disorders (SSD) and bipolar disorder (BD) is uncertain. This review aimed to address this, by providing a comprehensive systematic investigation of links between several cognitive domains and brain volume, cortical thickness, and cortical surface area in SSD and BD patients across early and established illness stages. An initial search of PubMed and Scopus databases resulted in 1486 articles, of which 124 met inclusion criteria and were reviewed in detail. The majority of studies focused on SSD, while those of BD were scarce. Replicated evidence for specific regions associated with indices of cognition was minimal, however for several cognitive domains, the frontal and temporal regions were broadly implicated across both recent-onset and established SSD, and to a lesser extent BD. Collectively, the findings of this review emphasize the significance of both frontal and temporal regions for some domains of cognition in SSD, while highlighting the need for future BD-related studies on this topic.
Collapse
Affiliation(s)
- James A Karantonis
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Sean P Carruthers
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Susan L Rossell
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- St Vincent’s Mental Health, St Vincent’s Hospital, Melbourne, Australia
| | - Christos Pantelis
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Australia
- Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, Australia
| | - Matthew Hughes
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Cassandra Wannan
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Vanessa Cropley
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Tamsyn E Van Rheenen
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| |
Collapse
|
11
|
Brain morphology does not clearly map to cognition in individuals on the bipolar-schizophrenia-spectrum: a cross-diagnostic study of cognitive subgroups. J Affect Disord 2021; 281:776-785. [PMID: 33246649 DOI: 10.1016/j.jad.2020.11.064] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 11/08/2020] [Indexed: 01/11/2023]
Abstract
BACKGROUND Characterisation of brain morphological features common to cognitively similar individuals with bipolar disorder (BD) and schizophrenia spectrum disorders (SSD) may be key to understanding their shared neurobiological deficits. In the current study we examined whether three previously characterised cross-diagnostic cognitive subgroups differed among themselves and in comparison to healthy controls across measures of brain morphology. METHOD T1-weighted structural magnetic resonance imaging scans were obtained for 143 individuals; 65 healthy controls and 78 patients (SSD, n = 40; BD I, n = 38) classified into three cross-diagnostic cognitive subgroups: Globally Impaired (n = 24), Selectively Impaired (n = 32), and Superior/Near-Normal (n = 22). Cognitive subgroups were compared to each other and healthy controls on three separate analyses investigating (1) global, (2) regional, and (3) vertex-wise comparisons of brain volume, thickness, and surface area. RESULTS No significant subgroup differences were evident in global measures of brain morphology. In region of interest analyses, the Selectively Impaired subgroup had greater right accumbens volume than those Superior/Near-Normal subgroup and healthy controls, and the Superior/Near-Normal subgroup had reduced volume of the left entorhinal region compared to all other groups. In vertex-wise comparisons, the Globally Impaired subgroup had greater right precentral volume than the Selectively Impaired subgroup, and thicker cortex in the postcentral region relative to the Superior/Near-Normal subgroup. LIMITATIONS Exploration of medication effects was limited in our data. CONCLUSIONS Although some differences were evident in this sample, generally cross-diagnostic cognitive subgroups of individuals with SSD and BD did not appear to be clearly distinguished by patterns in brain morphology.
Collapse
|
12
|
Shi J, Guo H, Liu S, Xue W, Fan F, Li H, Fan H, An H, Wang Z, Tan S, Yang F, Tan Y. Subcortical Brain Volumes Relate to Neurocognition in First-Episode Schizophrenia, Bipolar Disorder, Major Depression Disorder, and Healthy Controls. Front Psychiatry 2021; 12:747386. [PMID: 35145436 PMCID: PMC8821164 DOI: 10.3389/fpsyt.2021.747386] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 11/30/2021] [Indexed: 12/04/2022] Open
Abstract
OBJECTIVE To explore differences and similarities in relationships between subcortical structure volumes and neurocognition among the four subject groups, including first-episode schizophrenia (FES), bipolar disorder (BD), major depression disorder (MDD), and healthy controls (HCs). METHODS We presented findings from subcortical volumes and neurocognitive analyses of 244 subjects (109 patients with FES; 63 patients with BD, 30 patients with MDD, and 42 HCs). Using the FreeSurfer software, volumes of 16 selected subcortical structures were automatically segmented and analyzed for relationships with results from seven neurocognitive tests from the MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Cognitive Consensus Battery (MCCB). RESULTS Larger left lateral ventricle volumes in FES and BD, reduced bilateral hippocampus and amygdala volumes in FES, and lower bilateral amygdala volumes in BD and MDD were presented compared with HCs, and both FES and BD had a lower bilateral amygdala volume than MDD; there were seven cognitive dimension, five cognitive dimension, and two cognitive dimension impairments in FES, BD, and MDD, respectively; significant relationships were found between subcortical volumes and neurocognition in FES and BD but not in MDD and HCs; besides age and years of education, some subcortical volumes can predict neurocognitive performances variance. CONCLUSION The different degrees of subcortical volume lessening may contribute to the differences in cognitive impairment among the three psychiatric disorders.
Collapse
Affiliation(s)
- Jing Shi
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Hua Guo
- The Psychiatric Hospital of Zhumadian, Zhumadian, China
| | - Sijia Liu
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Wei Xue
- Department of Clinical Pharmacology, Beijing Hospital of the Ministry of Health, Beijing, China
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Hui Li
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Hongzhen Fan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Huimei An
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| |
Collapse
|
13
|
Tan EJ, Neill E, Tomlinson K, Rossell SL. Semantic Memory Impairment Across the Schizophrenia Continuum: A Meta-Analysis of Category Fluency Performance. ACTA ACUST UNITED AC 2020. [DOI: 10.1093/schizbullopen/sgaa054] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Abstract
Semantic memory (SM) impairments are a core feature of schizophrenia and are present along the psychosis continuum. It is, however, unclear whether the degree of SM impairments vary along this continuum and if demographic and clinical factors affect impairment severity. This study performed meta-analyses of category fluency task performance (a task commonly used to assess SM) in 4 groups along the schizophrenia continuum: high schizotypes (HSZT), first-degree relatives (FDR), recent-onset patients (≤2 y; ROP) and chronic patients (CSZ). Electronic databases were searched for relevant studies published up to October 2019 resulting in the inclusion of 48 articles. The main analyses assessed fluency productivity scores in 2978 schizophrenia spectrum disorder patients, 340 first-degree relatives of schizophrenia spectrum disorder patients, and 3204 healthy controls. Further analyses assessed errors, mean cluster size, and switching data that were available in the CSZ group only. Results revealed significant impairments in fluency productivity were present in the FDR, ROP, and CSZ groups relative to healthy controls, but not in HSZT. In the CSZ group, significant differences relative to healthy controls were also observed in non-perseverative errors, mean cluster size, and number of switches. The findings collectively suggest that SM deficits are present at each stage of the continuum and are exacerbated post-illness onset. They also support the centrality of SM impairments in schizophrenia and most elevated risk groups. Future studies with more diverse measures of SM function are needed to replicate and extend this research.
Collapse
Affiliation(s)
- Eric Josiah Tan
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
- Department of Psychiatry, St Vincent’s Hospital, Melbourne, Australia
| | - Erica Neill
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
- Department of Psychiatry, St Vincent’s Hospital, Melbourne, Australia
- Department of Psychiatry, The University of Melbourne, Melbourne, Australia
| | - Kiandra Tomlinson
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
| | - Susan Lee Rossell
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
- Department of Psychiatry, St Vincent’s Hospital, Melbourne, Australia
| |
Collapse
|
14
|
Wortinger LA, Engen K, Barth C, Lonning V, Jørgensen KN, Andreassen OA, Haukvik UK, Vaskinn A, Ueland T, Agartz I. Obstetric complications and intelligence in patients on the schizophrenia-bipolar spectrum and healthy participants. Psychol Med 2020; 50:1914-1922. [PMID: 31456537 PMCID: PMC7477368 DOI: 10.1017/s0033291719002046] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/27/2019] [Accepted: 07/24/2019] [Indexed: 11/26/2022]
Abstract
BACKGROUND Whether severe obstetric complications (OCs), which harm neural function in offspring, contribute to impaired cognition found in psychiatric disorders is currently unknown. Here, we sought to evaluate how a history of severe OCs is associated with cognitive functioning, indicated by Intelligence Quotient (IQ). METHODS We evaluated the associations of a history of OCs and IQ in 622 healthy controls (HC) and 870 patients on the schizophrenia (SCZ) - bipolar disorder (BIP) spectrum from the ongoing Thematically Organized Psychosis study cohort, Oslo, Norway. Participants underwent assessments using the NART (premorbid IQ) and the WASI (current IQ). Information about OCs was obtained from the Medical Birth Registry of Norway. Multiple linear regression models were used for analysis. RESULTS Severe OCs were equally common across groups. SCZ patients with OCs had lower performances on both premorbid and current IQ measures, compared to those without OCs. However, having experienced more than one co-occurring severe OC was associated with lower current IQ in all groups. CONCLUSIONS Severe OCs were associated with lower IQ in the SCZ group and in the BIP and HC groups, but only if they had experienced more than one severe OC. Low IQ might be a neurodevelopmental marker for SCZ; wherein, severe OCs influence cognitive abilities and increase the risk of developing SCZ. Considering OCs as a variable of neurodevelopmental risk for severe mental illness may promote the development of neuroprotective interventions, improve outcome in vulnerable newborns and advance our ability to make clinical prognoses.
Collapse
Affiliation(s)
- Laura Anne Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kristine Engen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Claudia Barth
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Vera Lonning
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kjetil Nordbø Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Unn Kristin Haukvik
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anja Vaskinn
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torill Ueland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institute, Stockholm, Sweden
| |
Collapse
|
15
|
Achalia R, Sinha A, Jacob A, Achalia G, Kaginalkar V, Venkatasubramanian G, Rao NP. A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder. Asian J Psychiatr 2020; 50:101984. [PMID: 32143176 DOI: 10.1016/j.ajp.2020.101984] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 02/18/2020] [Accepted: 02/24/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomarker in Alzheimer's dementia. However, such an approach has not been examined to differentiate healthy individuals from Bipolar disorder. In this study, we examined the utility of support vector machine (SVM) technique to differentiate bipolar disorder patients and healthy using structural, functional and diffusion tensor images of brain and neurocognitive measures. METHODS 30 patients with Bipolar disorder-I and 30 age, sex matched individuals participated in the study. Structural MRI, resting state functional MRI and diffusion tensor images were obtained using a 1.5 T scanner. All participants were administered neuropsychological tests to measure executive functions. SVM, a supervised machine learning technique was applied to differentiate patients and healthy individuals with k-fold cross validation over 10 trials. RESULTS The composite marker consisting of both neuroimaging and neuropsychological measures, had an accuracy of 87.60 %, sensitivity of 82.3 % and specificity of 92.7 %. The performance of composite marker was better compared to that of individual markers on classificatory. CONCLUSIONS We were able to achieve a high accuracy for machine learning technique in distinguishing BD from HV using a combination of multimodal neuroimaging and neurocognitive measures. Findings of this proof of concept study, if replicated in larger samples, could have potential clinical applications.
Collapse
Affiliation(s)
| | - Anannya Sinha
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Arpitha Jacob
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Garimaa Achalia
- Achalia Neuropsychiatry Hospital, Aurangabad, Maharashtra, India
| | | | | | - Naren P Rao
- National Institute of Mental Health and Neurosciences, Bangalore, India.
| |
Collapse
|
16
|
Karantonis JA, Rossell SL, Carruthers SP, Sumner P, Hughes M, Green MJ, Pantelis C, Burdick KE, Cropley V, Van Rheenen TE. Cognitive validation of cross-diagnostic cognitive subgroups on the schizophrenia-bipolar spectrum. J Affect Disord 2020; 266:710-721. [PMID: 32056949 DOI: 10.1016/j.jad.2020.01.123] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Revised: 12/03/2019] [Accepted: 01/20/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs. METHOD Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline. RESULTS A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups. LIMITATIONS For clustering analysis, sample size was relatively small. CONCLUSIONS The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.
Collapse
Affiliation(s)
- James A Karantonis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; St Vincent's Mental Health, St Vincent's Hospital, VIC, Australia
| | - Sean P Carruthers
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Matthew Hughes
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Melissa J Green
- School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW, Australia; Neuroscience Research Australia, Randwick, NSW, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia; Centre for Neuropsychiatric Schizophrenia Research (CNSR) and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Centre Glostrup, Glostrup, Denmark
| | - Katherine E Burdick
- Harvard Medical School, Department of Psychiatry, Boston, MA, United States; Brigham and Women's Hospital, Boston, MA, United States
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia.
| |
Collapse
|
17
|
Neurodevelopmental pathways in bipolar disorder. Neurosci Biobehav Rev 2020; 112:213-226. [PMID: 32035092 DOI: 10.1016/j.neubiorev.2020.02.005] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 01/03/2020] [Accepted: 02/04/2020] [Indexed: 12/14/2022]
Abstract
Aberrations in neurodevelopmental trajectories have been implicated in the neurobiology of several mental disorders and evidence indicates a pathophysiological and genetic overlap of schizophrenia and bipolar disorder (BD). In this narrative review, we summarize findings related to developmental and perinatal factors as well as epidemiological, clinical, neuropsychological, brain imaging, postmortem brain and genomic studies that provide evidence for a putative neurodevelopmental pathogenesis and etiology of BD. Overall, aberrations in neurodevelopmental pathways have been more consistently implicated in the pathophysiology of schizophrenia compared to BD. Nevertheless, an accumulating body of evidence indicates that dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of at least a subset of individuals with BD particularly those with an early age of illness onset and those exhibiting psychotic symptoms. A heuristic neurodevelopmental model for the pathophysiology of BD based on the findings of this review is proposed. Furthermore, we critically discuss clinical and research implications of this model. Finally, further research directions for this emerging field are provided.
Collapse
|
18
|
Joaquim HPG, Costa AC, Talib LL, Dethloff F, Serpa MH, Zanetti MV, van de Bilt M, Turck CW. Plasma Metabolite Profiles in First Episode Psychosis: Exploring Symptoms Heterogeneity/Severity in Schizophrenia and Bipolar Disorder Cohorts. Front Psychiatry 2020; 11:496. [PMID: 32581873 PMCID: PMC7290160 DOI: 10.3389/fpsyt.2020.00496] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 05/15/2020] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION The first symptoms of psychosis are frequently shared amongst several neuropsychiatry disorders, which makes the differentiation by clinical diagnosis challenging. Early recognition of symptoms is important in the management of psychosis. Therefore, the implementation of molecular biomarkers will be crucial for transforming the currently used diagnostic and therapeutic approach, improving insights into the underlying biological processes and clinical management. OBJECTIVES To define a set of metabolites that supports diagnosis or prognosis of schizophrenia (SCZ) and bipolar disorder (BD) at first onset psychosis. METHODS Plasma samples from 55 drug-naïve patients, 28 SCZ and 27 BD, and 42 healthy controls (HC). All participants underwent a seminaturalistic treatment regimen, clinically evaluated on a weekly basis until achieving clinical remission. All clinical or sociodemographic aspects considered for this study were equivalent between the groups at first-onset psychosis time point. The plasma samples were analyzed by untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) using reversed-phase and hydrophilic interaction chromatography. The acquired molecular features were analyzed with MetaboAnalyst. RESULTS We identified two patient groups with different metabolite profiles. Both groups are composed of SCZ and BD patients. We found differences between these two groups regarding general symptoms of PANSS score after remission (p = 0.008), and the improvement of general symptoms (delta of the score at remission minus the baseline) (-0.50 vs. -0.33, p = 0.019). CONCLUSION Our results suggest that plasma metabolite profiles cluster clinical remission phenotypes based on PANSS general psychopathology scores.
Collapse
Affiliation(s)
- Helena P G Joaquim
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil.,Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Alana C Costa
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil
| | - Leda L Talib
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil
| | - Frederik Dethloff
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Mauricio H Serpa
- Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil.,Laboratory of Psychiatric Neuroimaging LIM-21, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Marcus V Zanetti
- Laboratory of Psychiatric Neuroimaging LIM-21, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Hospital Sírio-Libanês, São Paulo, Brazil
| | - Martinus van de Bilt
- Laboratory of Neuroscience LIM-27, Department and Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Sao Paulo, Brazil
| | - Christoph W Turck
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| |
Collapse
|
19
|
A Systematic Review of Studies Reporting Data-Driven Cognitive Subtypes across the Psychosis Spectrum. Neuropsychol Rev 2019; 30:446-460. [PMID: 31853717 DOI: 10.1007/s11065-019-09422-7] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 12/02/2019] [Indexed: 10/25/2022]
Abstract
The delineation of cognitive subtypes of schizophrenia and bipolar disorder may offer a means of determining shared genetic markers and neuropathology among individuals with these conditions. We systematically reviewed the evidence from published studies reporting the use of data-driven (i.e., unsupervised) clustering methods to delineate cognitive subtypes among adults diagnosed with schizophrenia, schizoaffective disorder, or bipolar disorder. We reviewed 24 studies in total, contributing data to 13 analyses of schizophrenia spectrum patients, 8 analyses of bipolar disorder, and 5 analyses of mixed samples of schizophrenia and bipolar disorder participants. Studies of bipolar disorder most consistently revealed a 3-cluster solution, comprising a subgroup with 'near-normal' (cognitively spared) cognition and two other subgroups demonstrating graded deficits across cognitive domains. In contrast, there was no clear consensus regarding the number of cognitive subtypes among studies of cognitive subtypes in schizophrenia, while four of the five studies of mixed diagnostic groups reported a 4-cluster solution. Common to all cluster solutions was a severe cognitive deficit subtype with cognitive impairments of moderate to large effect size relative to healthy controls. Our review highlights several key factors (e.g., symptom profile, sample size, statistical procedures, and cognitive domains examined) that may influence the results of data-driven clustering methods, and which were largely inconsistent across the studies reviewed. This synthesis of findings suggests caution should be exercised when interpreting the utility of particular cognitive subtypes for biological investigation, and demonstrates much heterogeneity among studies using unsupervised clustering approaches to cognitive subtyping within and across the psychosis spectrum.
Collapse
|
20
|
Wang K, Zhao YL, Tan SP, Zhang JG, Li D, Chen JX, Zhang LG, Yu XY, Zhao D, Cheung EFC, Turetsky BI, Gur RC, Chan RCK. Semantic processing event‐related potential features in patients with schizophrenia and bipolar disorder. Psych J 2019; 9:247-257. [PMID: 31788984 DOI: 10.1002/pchj.321] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2019] [Revised: 10/15/2019] [Accepted: 10/16/2019] [Indexed: 11/07/2022]
Affiliation(s)
- Kui Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yan-Li Zhao
- Beijing Huilongguan Hospital, Beijing, China
| | | | | | - Dong Li
- Beijing Huilongguan Hospital, Beijing, China
| | | | | | - Xin-Yang Yu
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Dan Zhao
- School of Education, Changchun Normal University, Changchun, China
| | | | - Bruce I Turetsky
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
21
|
Sorella S, Lapomarda G, Messina I, Frederickson JJ, Siugzdaite R, Job R, Grecucci A. Testing the expanded continuum hypothesis of schizophrenia and bipolar disorder. Neural and psychological evidence for shared and distinct mechanisms. NEUROIMAGE-CLINICAL 2019; 23:101854. [PMID: 31121524 PMCID: PMC6529770 DOI: 10.1016/j.nicl.2019.101854] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 04/24/2019] [Accepted: 05/02/2019] [Indexed: 12/21/2022]
Affiliation(s)
- Sara Sorella
- Department of Psychology and Cognitive Science (DiPSCo), University of Trento, Rovereto, Italy.
| | - Gaia Lapomarda
- Department of Psychology and Cognitive Science (DiPSCo), University of Trento, Rovereto, Italy.
| | | | | | - Roma Siugzdaite
- Department of Experimental Psychology, Faculty of Psychological and Pedagogical Sciences, Ghent University, Ghent, Belgium.
| | - Remo Job
- Department of Psychology and Cognitive Science (DiPSCo), University of Trento, Rovereto, Italy.
| | - Alessandro Grecucci
- Department of Psychology and Cognitive Science (DiPSCo), University of Trento, Rovereto, Italy.
| |
Collapse
|
22
|
Kargar M, Askari S, Khoshaman A, Mohammadi A. Differential diagnosis of schizophrenia and schizoaffective disorder from normal subjects using virtual reality. Psychiatry Res 2019; 273:378-386. [PMID: 30682560 DOI: 10.1016/j.psychres.2019.01.037] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 01/01/2019] [Accepted: 01/11/2019] [Indexed: 01/08/2023]
Abstract
Dysfunction of allocentric and egocentric memories is one of the core features of psychiatric disorders. There are a few navigational studies on these memories in schizophrenia and bipolar disorders, but studies in schizoaffective disorder are lacking. Here, we aim to explore allocentric and egocentric navigation deficits in these subjects using our advanced recently developed virtual reality navigation task (VRNT). Twenty patients with schizophrenia and 20 with schizoaffective disorder were compared with 20 normal volunteer subjects on VRNTs consisting of a virtual neighbourhood (allocentric memory) and a virtual maze (egocentric memory). Compared with schizoaffective disorder and control subjects, patients with schizophrenia had the worst performance on both virtual neighbourhood and virtual maze tasks. The allocentric memory in both patients with schizophrenia and those with schizoaffective disorder was more impaired than the egocentric memory (p ˂ 0.001). However, the patients with schizoaffective disorder performed better in egocentric memory than those with schizophrenia, as they had fewer errors in the virtual maze. It was concluded that allocentric memory is more impaired than egocentric in both schizoaffective disorder and schizophrenia patients, whereas patients with schizoaffective disorder performed better in egocentric memory than patients with schizophrenia. It was also concluded that allocentric memory deficits can help differentiate patients with schizophrenia and schizoaffective disorder from healthy participants, whereas egocentric memory deficits can be used to distinguish them from each other.
Collapse
Affiliation(s)
- Mahmoud Kargar
- Department of Speech Therapy, School of Rehabilitation, Tehran University of Medical Sciences, Tehran, Iran
| | - Sajad Askari
- Department of Urban Planning, Shiraz University, Shiraz, Iran
| | | | - Alireza Mohammadi
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
| |
Collapse
|
23
|
Abstract
Cognitive dysfunction is common in many psychiatric disorders. While it has long been described as a core feature in schizophrenia, more recent data suggest qualitatively similar impairments in patients with bipolar disorder and major depressive disorder. There is compelling evidence to suggest that cognitive impairment contributes directly to functional disability and reduced quality of like across these disorders. As current treatments focus heavily on "primary" symptoms of mood and psychosis, the standard of care typically leaves cognitive deficits unmanaged. With this in mind, the field has recently begun to consider intervening directly on this important symptom domain, with several ongoing trials in schizophrenia. Fewer studies have targeted cognition in bipolar disorder and still fewer in MDD. With progress toward considering this domain as a target for treatment comes the need for consensus guidelines and methodological recommendations on cognitive trial design. In this manuscript, we first summarize the work conducted to date in this area for schizophrenia and for bipolar disorder. We then begin to address these same issues in MDD and emphasize the need for additional work in this area.
Collapse
|
24
|
Sheffield JM, Karcher NR, Barch DM. Cognitive Deficits in Psychotic Disorders: A Lifespan Perspective. Neuropsychol Rev 2018; 28:509-533. [PMID: 30343458 DOI: 10.1007/s11065-018-9388-2] [Citation(s) in RCA: 237] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 10/15/2018] [Indexed: 12/15/2022]
Abstract
Individuals with disorders that include psychotic symptoms (i.e. psychotic disorders) experience broad cognitive impairments in the chronic state, indicating a dimension of abnormality associated with the experience of psychosis. These impairments negatively impact functional outcome, contributing to the disabling nature of schizophrenia, bipolar disorder, and psychotic depression. The robust and reliable nature of cognitive deficits has led researchers to explore the timing and profile of impairments, as this may elucidate different neurodevelopmental patterns in individuals who experience psychosis. Here, we review the literature on cognitive deficits across the life span of individuals with psychotic disorder and psychotic-like experiences, highlighting the dimensional nature of both psychosis and cognitive ability. We identify premorbid generalized cognitive impairment in schizophrenia that worsens throughout development, and stabilizes by the first-episode of psychosis, suggesting a neurodevelopmental course. Research in affective psychosis is less clear, with mixed evidence regarding premorbid deficits, but a fairly reliable generalized deficit at first-episode, which appears to worsen into the chronic state. In general, cognitive impairments are most severe in schizophrenia, intermediate in bipolar disorder, and the least severe in psychotic depression. In all groups, cognitive deficits are associated with poorer functional outcome. Finally, while the generalized deficit is the clearest and most reliable signal, data suggests specific deficits in verbal memory across all groups, specific processing speed impairments in schizophrenia and executive functioning impairments in bipolar disorder. Cognitive deficits are a core feature of psychotic disorders that provide a window into understanding developmental course and risk for psychosis.
Collapse
Affiliation(s)
- Julia M Sheffield
- Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center, 1601 23rd Ave S, Nashville, TN, 37212, USA.
| | - Nicole R Karcher
- Department of Psychological & Brain Sciences, Washington University St. Louis, 1 Brookings Dr., St. Louis, MO, 63130, USA
| | - Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University St. Louis, 1 Brookings Dr., St. Louis, MO, 63130, USA.,Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA.,Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| |
Collapse
|
25
|
Chen CK, Lee CY, Lee Y, Hung CF, Huang YC, Lee SY, Huang MC, Chong MY, Chen YC, Wang LJ. Could schizoaffective disorder, schizophrenia and bipolar I disorder be distinguishable using cognitive profiles? Psychiatry Res 2018; 266:79-84. [PMID: 29852325 DOI: 10.1016/j.psychres.2018.05.062] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 04/09/2018] [Accepted: 05/23/2018] [Indexed: 10/16/2022]
Abstract
This study seeks to determine whether the cognition profiles of patients with schizoaffective disorder (SAD), schizophrenia and bipolar I disorder (BD) are distinguishable. A total of 227 participants, comprising 88 healthy control subjects, 50 patients with SAD, 48 patients with schizophrenia and 41 patients with BD, were recruited. The participants' cognitive functions were evaluated using the Brief Assessment of Cognition in Schizophrenia (BACS). A discriminant functions analysis (DFA) was conducted to determine whether using cognitive performance can be used to distinguish these participant groups. Relative to healthy control subjects, patients with SAD, schizophrenia and BD exhibited significant deficits in all cognitive domains (verbal memory, working memory, motor speed, verbal fluency, attention and processing speed, executive function and a composite BACS score). Among the three patient groups, the schizophrenia group exhibited particularly impaired motor speed, and the BD group performed best in attention, processing speed, executive function and the composite BACS score. The classification accuracy rates of patients with SAD, schizophrenia and BD in the DFA model were 38%, 47.9% and 46.3%, respectively. These findings suggest that the impairments of some cognitive domains were less severe in patients with BD than in patients with schizophrenia or SAD.
Collapse
Affiliation(s)
- Chih-Ken Chen
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung, Taiwan; Chang Gung University School of Medicine, Taoyuan, Taiwan
| | - Chun-Yi Lee
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yu Lee
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chi-Fa Hung
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yu-Chi Huang
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Sheng-Yu Lee
- Department of Psychiatry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Department of Psychiatry, College of Medicine, National Yang-Ming University, Taipei, Taiwan; Department of Psychiatry, School of Medicine, and Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ming-Chyi Huang
- Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan; Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Mian-Yoon Chong
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yi-Chih Chen
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung, Taiwan; Chang Gung University School of Medicine, Taoyuan, Taiwan
| | - Liang-Jen Wang
- Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
| |
Collapse
|
26
|
Calafiore D, Rossell SL, Van Rheenen TE. Cognitive abilities in first-degree relatives of individuals with bipolar disorder. J Affect Disord 2018; 225:147-152. [PMID: 28829959 DOI: 10.1016/j.jad.2017.08.029] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Revised: 03/16/2017] [Accepted: 08/10/2017] [Indexed: 02/03/2023]
Abstract
BACKGROUND Although the study of cognition in first degree relatives (FDRs) is not new, findings in this group are still somewhat inconsistent and much of the research examining FDR populations include individuals under the age of 25, who are arguably still at significant risk to go on to develop BD. The present study aimed to establish the value of cognitive performance as a genuine endophenotypic marker of familial risk for bipolar disorder (BD), by examining cognition in FDRs aged 25 years or older. METHODS The current study compared the cognitive performance of 27 unaffected FDRs to 47 healthy controls (HCs) and 28 BD patients using the MATRICS Consensus Cognitive Battery (MCCB). RESULTS Results indicated that FDRs had impaired verbal learning performance, as well as selective impairments on a measure of speed of processing; and a measure of spatial working memory compared to HC. LIMITATIONS Limitations relate to the potential insensitivity of some of the tests in the MCCB for detecting cognitive deficits that have been previously noted in BD and FDR samples using other batteries. CONCLUSIONS Findings from this study implicate verbal learning, processing speed and working memory performance as promising candidate endophenotypes of familial risk for BD.
Collapse
Affiliation(s)
- Daniela Calafiore
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; Cognitive Neuropsychiatry Laboratory, Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia; Department of Psychiatry, St Vincent's Hospital, Melbourne, Australia
| | - Tamsyn E Van Rheenen
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; Department of Psychiatry, St Vincent's Hospital, Melbourne, Australia; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia.
| |
Collapse
|
27
|
Hoonakker M, Doignon-Camus N, Bonnefond A. Sustaining attention to simple visual tasks: a central deficit in schizophrenia? A systematic review. Ann N Y Acad Sci 2017; 1408:32-45. [PMID: 29090832 DOI: 10.1111/nyas.13514] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Revised: 08/20/2017] [Accepted: 09/11/2017] [Indexed: 11/30/2022]
Abstract
Impairments in sustained attention, that is, the ability to achieve and maintain the focus of cognitive activity on a given stimulation source or task, have been described as central to schizophrenia. Today, sustained attention deficit is still considered as a hallmark of schizophrenia. Nevertheless, current findings on this topic are not consistent. To clarify these findings, we attempt to put these results into perspective according to the type of assessment (i.e., overall and over time assessment), the participants' characteristics (i.e., clinical and demographic characteristics), and the paradigms (i.e., traditionally formatted tasks, go/no-go tasks, and the sustained attention task) and measures used. Two types of assessment lead to opposite findings; they do not evaluate sustained attention the same way. Studies using overall assessments of sustained attention ability tend to reveal a deficit, whereas studies using over time assessments do not. Therefore, further research is needed to investigate the underlying cognitive control mechanisms of changes in sustained attention in schizophrenia.
Collapse
Affiliation(s)
- Marc Hoonakker
- INSERM U1114, Department of Psychiatry, University Hospital of Strasbourg, Strasbourg, France
| | - Nadège Doignon-Camus
- University of Strasbourg, University of Haute-Alsace, University of Lorraine, LISEC EA 2310, Strasbourg, France
| | - Anne Bonnefond
- INSERM U1114, Department of Psychiatry, University Hospital of Strasbourg, Strasbourg, France
| |
Collapse
|
28
|
Lin YL, Persaud SD, Nhieu J, Wei LN. Cellular Retinoic Acid-Binding Protein 1 Modulates Stem Cell Proliferation to Affect Learning and Memory in Male Mice. Endocrinology 2017; 158:3004-3014. [PMID: 28911165 PMCID: PMC5659671 DOI: 10.1210/en.2017-00353] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 06/14/2017] [Indexed: 01/05/2023]
Abstract
Retinoic acid (RA) is the active ingredient of vitamin A. It exerts its canonical activity by binding to nuclear RA receptors (RARs) to regulate gene expression. Increasingly, RA is also known to elicit nongenomic RAR-independent activities, most widely detected in activating extracellular regulated kinase (ERK)1/2. This study validated the functional role of cellular retinoic acid-binding protein 1 (Crabp1) in mediating nongenomic activity in RA, specifically activating ERK1/2 to rapidly augment the cell cycle by expanding the growth 1 phase and slowing down embryonic stem cell and neural stem cell (NSC) proliferation. The study further uncovered the physiological activity of Crabp1 in modulating NSC proliferation and animal behavior. In the Crabp1 knockout mouse hippocampus, where Crabp1 is otherwise detected in the subgranular zone, neurogenesis and NSC proliferation increased and hippocampus-dependent brain functions such as learning and memory correspondingly improved. This study established the physiological role of Crabp1 in modulating stem cell proliferation and hippocampus-dependent brain activities such as learning and memory.
Collapse
Affiliation(s)
- Yu-Lung Lin
- Department of Pharmacology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Shawna D. Persaud
- Department of Pharmacology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Jennifer Nhieu
- Department of Pharmacology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Li-Na Wei
- Department of Pharmacology, University of Minnesota, Minneapolis, Minnesota 55455
| |
Collapse
|
29
|
Van Rheenen TE, Lewandowski KE, Tan EJ, Ospina LH, Ongur D, Neill E, Gurvich C, Pantelis C, Malhotra AK, Rossell SL, Burdick KE. Characterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrum. Psychol Med 2017; 47:1848-1864. [PMID: 28241891 DOI: 10.1017/s0033291717000307] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. METHOD Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). RESULTS Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. CONCLUSIONS Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.
Collapse
Affiliation(s)
- T E Van Rheenen
- Melbourne Neuropsychiatry Centre,Department of Psychiatry,University of Melbourne and Melbourne Health,Carlton,VIC,Australia
| | - K E Lewandowski
- Schizophrenia and Bipolar Disorder Program,McLean Hospital,Belmont, MA,USA
| | - E J Tan
- Brain and Psychological Sciences Research Centre,Faculty of Health, Arts and Design,School of Health Sciences, Swinburne University,Hawthorn,VIC,Australia
| | - L H Ospina
- Icahn School of Medicine,Mount Sinai, NY,USA
| | - D Ongur
- Schizophrenia and Bipolar Disorder Program,McLean Hospital,Belmont, MA,USA
| | - E Neill
- Brain and Psychological Sciences Research Centre,Faculty of Health, Arts and Design,School of Health Sciences, Swinburne University,Hawthorn,VIC,Australia
| | - C Gurvich
- Cognitive Neuropsychiatry Laboratory,Monash Alfred Psychiatry Research Centre, The Alfred Hospital and Central Clinical School, Monash University,Melbourne,VIC,Australia
| | - C Pantelis
- Melbourne Neuropsychiatry Centre,Department of Psychiatry,University of Melbourne and Melbourne Health,Carlton,VIC,Australia
| | - A K Malhotra
- Hofstra Northwell School of Medicine,Hempstead, NY,USA
| | - S L Rossell
- Brain and Psychological Sciences Research Centre,Faculty of Health, Arts and Design,School of Health Sciences, Swinburne University,Hawthorn,VIC,Australia
| | - K E Burdick
- Icahn School of Medicine,Mount Sinai, NY,USA
| |
Collapse
|
30
|
Case K, Guo Y, Nixon SJ, Muller K, Huo T, Prather R, Morris H, Stoner D, Shenkman E. Exploring the Role of Executive Functioning Capacity in Patient Activation and Health Outcomes Among Medicaid Members With Multiple Comorbidities. Med Care Res Rev 2017; 76:444-461. [DOI: 10.1177/1077558717709419] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Patient activation, the perceived capacity to manage one’s health, is positively associated with better health outcomes and lower costs. Underlying characteristics influencing patient activation are not completely understood leading to gaps in intervention strategies designed to improve patient activation. We suggest that variability in executive functioning influences patient activation and ultimately has an impact on health outcomes. To examine this hypothesis, 440 chronically ill Medicaid enrollees completed measures of executive functioning, patient activation, and health-related quality of life. Mediation analyses revealed that executive functioning: (a) directly affected patient activation and mental health-related quality of life, (b) indirectly affected mental health-related quality of life through patient activation, and (c) was unrelated to physical health-related quality of life. These data indicate that further study of the relationships among neurocognitive processes, patient activation, and health-related quality of life is needed and reinforces previous work demonstrating the association between patient activation and self-reported outcomes.
Collapse
Affiliation(s)
| | - Yi Guo
- University of Florida, Gainesville, FL, USA
| | | | | | | | | | | | - Dena Stoner
- Department of State Health Services, Austin, TX, USA
| | | |
Collapse
|
31
|
Scott J, Vaaler AE, Fasmer OB, Morken G, Krane-Gartiser K. A pilot study to determine whether combinations of objectively measured activity parameters can be used to differentiate between mixed states, mania, and bipolar depression. Int J Bipolar Disord 2017; 5:5. [PMID: 28155205 PMCID: PMC5331021 DOI: 10.1186/s40345-017-0076-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Accepted: 01/17/2017] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Until recently, actigraphy studies in bipolar disorders focused on sleep rather than daytime activity in mania or depression, and have failed to analyse mixed episodes separately. Furthermore, even those studies that assessed activity parameters reported only mean levels rather than complexity or predictability of activity. We identified cases presenting in one of three acute phases of bipolar disorder and examined whether the application of non-linear dynamic models to the description of objectively measured activity can be used to predict case classification. METHODS The sample comprised 34 adults who were hospitalized with an acute episode of mania (n = 16), bipolar depression (n = 12), or a mixed state (n = 6), who agreed to wear an actiwatch for a continuous period of 24 h. Mean level, variability, regularity, entropy, and predictability of activity were recorded for a defined 64-min active morning and active evening period. Discriminant function analysis was used to determine the combination of variables that best classified cases based on phase of illness. RESULTS The model identified two discriminant functions: the first was statistically significant and correlated with intra-individual fluctuation in activity and regularity of activity (sample entropy) in the active morning period; the second correlated with several measures of activity from the evening period (e.g. Fourier analysis, autocorrelation, sample entropy). A classification table generated from both functions correctly classified 79% of all cases based on phase of illness (χ 2 = 36.21; df 4; p = 0.001). However, 42% of bipolar depression cases were misclassified as being in manic phase. CONCLUSIONS The findings should be treated with caution as this was a small-scale pilot study and we did not control for prescribed treatments, medication adherence, etc. However, the insights gained should encourage more widespread adoption of statistical approaches to the classification of cases alongside the application of more sophisticated modelling of activity patterns. The difficulty of accurately classifying cases of bipolar depression requires further research, as it is unclear whether the lower prediction rate reflects weaknesses in a model based only on actigraphy data, or if it reflects clinical reality i.e. the possibility that there may be more than one subtype of bipolar depression.
Collapse
Affiliation(s)
- Jan Scott
- Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK.
| | - Arne E Vaaler
- Department of Neuroscience, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Psychiatry, St. Olav's University Hospital, Trondheim, Norway
| | - Ole Bernt Fasmer
- Department of Clinical Medicine, Section for Psychiatry, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway.,Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Gunnar Morken
- Department of Neuroscience, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Psychiatry, St. Olav's University Hospital, Trondheim, Norway
| | - Karoline Krane-Gartiser
- Department of Neuroscience, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Psychiatry, St. Olav's University Hospital, Trondheim, Norway
| |
Collapse
|