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Yassin W, Green J, Keshavan M, Del Re EC, Addington J, Bearden CE, Cadenhead KS, Cannon TD, Cornblatt BA, Mathalon DH, Perkins DO, Walker EF, Woods SW, Stone WS. Cognitive subtypes in youth at clinical high risk for psychosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.07.24311240. [PMID: 39211862 PMCID: PMC11361220 DOI: 10.1101/2024.08.07.24311240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Introduction Schizophrenia is a mental health condition that severely impacts well-being. Cognitive impairment is among its core features, often presenting well before the onset of overt psychosis, underscoring a critical need to study it in the psychosis proneness (clinical high risk; CHR) stage, to maximize the benefits of interventions and to improve clinical outcomes. However, given the heterogeneity of cognitive impairment in this population, a one-size-fits-all approach to therapeutic interventions would likely be insufficient. Thus, identifying cognitive subtypes in this population is crucial for tailored and successful therapeutic interventions. Here we identify, validate, and characterize cognitive subtypes in large CHR samples and delineate their baseline and longitudinal cognitive and functional trajectories. Methods Using machine learning, we performed cluster analysis on cognitive measures in a large sample of CHR youth (n = 764), and demographically comparable controls (HC; n = 280) from the North American Prodrome Longitudinal Study (NAPLS) 2, and independently validated our findings with an equally large sample (NAPLS 3; n = 628 CHR, 84 HC). By utilizing several statistical approaches, we compared the clusters on cognition and functioning at baseline, and over 24 months of followup. We further delineate the conversion status within those clusters. Results Two main cognitive clusters were identified, "impaired" and "intact" across all cognitive domains in CHR compared to HC. Baseline differences between the cognitively intact cluster and HC were found in the verbal abilities and attention and working memory domains. Longitudinally, those in the cognitively impaired cluster group demonstrated an overall floor effect and did not deteriorate further over time. However, a "catch up" trajectory was observed in the attention and working memory domain. This group had higher instances of conversion overall, with these converters having significantly more non-affective psychotic disorder diagnosis versus bipolar disorder, than those with intact cognition. In the cognitively intact group, we observed differences in trajectory based on conversion status, where those who start with intact cognition and later convert demonstrate a sharp decline in attention and functioning. Functioning was significantly better in the cognitively intact than in the impaired group at baseline. Most of the cognitive trajectories demonstrate a positive relationship with functional ones. Conclusion Our findings provide evidence for intact and impaired cognitive subtypes in youth at CHR, independent of conversion status. They further indicate that attention and working memory are important to distinguish between the CHR with intact cognition and controls. The cognitively intact CHR group becomes less attentive after conversion, while the cognitively impaired one demonstrates a catch up trajectory on both attention and working memory. Overall, early evaluation, covering several cognitive domains, is crucial for identifying trajectories of improvement and deterioration for the purpose of tailoring intervention for improving outcomes in individuals at CHR for psychosis.
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Gifford G, Avila A, Kempton MJ, Fusar-Poli P, McCutcheon RA, Coutts F, Tognin S, Valmaggia L, de Haan L, van der Gaag M, Nelson B, Pantelis C, Riecher-Rössler A, Bressan R, Barrantes-Vidal N, Krebs MO, Glenthøj B, Ruhrmann S, Sachs G, Rutten BPF, van Os J, Eu-Gei High Risk Study, McGuire P. Do Cognitive Subtypes Exist in People at Clinical High Risk for Psychosis? Results From the EU-GEI Study. Schizophr Bull 2024:sbae133. [PMID: 39052918 DOI: 10.1093/schbul/sbae133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/27/2024]
Abstract
BACKGROUND AND HYPOTHESIS Cognition has been associated with socio-occupational functioning in individuals at Clinical High Risk for Psychosis (CHR-P). The present study hypothesized that clustering CHR-P participants based on cognitive data could reveal clinically meaningful subtypes. STUDY DESIGN A cohort of 291 CHR-P subjects was recruited through the multicentre EU-GEI high-risk study. We explored whether an underlying cluster structure was present in the cognition data. Clustering of cognition data was performed using k-means clustering and density-based spatial clustering of applications with noise. Cognitive subtypes were validated by comparing differences in functioning, psychosis symptoms, transition outcome, and grey matter volume between clusters. Network analysis was used to further examine relationships between cognition scores and clinical symptoms. STUDY RESULTS No underlying cluster structure was found in the cognitive data. K-means clustering produced "spared" and "impaired" cognition clusters similar to those reported in previous studies. However, these clusters were not associated with differences in functioning, symptomatology, outcome, or grey matter volume. Network analysis identified cognition and symptoms/functioning measures that formed separate subnetworks of associations. CONCLUSIONS Stratifying patients according to cognitive performance has the potential to inform clinical care. However, we did not find evidence of cognitive clusters in this CHR-P sample. We suggest that care needs to be taken in inferring the existence of distinct cognitive subtypes from unsupervised learning studies. Future research in CHR-P samples could explore the existence of cognitive subtypes across a wider range of cognitive domains.
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Affiliation(s)
- George Gifford
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Alessia Avila
- Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- Faculty of Medicine, Universidade Católica de Lisboa, Lisbon, Portugal
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Paolo Fusar-Poli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Outreach and Support in South-London (OASIS) Service, South London and Maudlsey (SLaM) NHS Foundation Trust, London, UK
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University (LMU), Munich, Germany
| | | | - Fiona Coutts
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Stefania Tognin
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Lucia Valmaggia
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Lieuwe de Haan
- Department Early Psychosis, AMC, Academic Psychiatric Centre, Amsterdam, The Netherlands
| | - Mark van der Gaag
- Department of Clinical Psychology, Faculty of Behavioural and Movement Sciences, VU University, Amsterdam, The Netherlands
- EMGO+ Institute for Health and Care Research, VU University, Amsterdam, The Netherlands
- Parnassia Psychiatric Institute, Department of Psychosis Research, The Hague, The Netherlands
| | - Barnaby Nelson
- Orygen, Victoria, Melbourne, Australia
- Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, University of Melbourne & Melbourne Health, Carlton South, Vic, Australia
| | | | - Rodrigo Bressan
- Department of Psychiatry, Interdisciplinary Lab for Clinical Neurosciences (LiNC), Universidade Federal de Sao Paulo (UNIFESP), Sao Paulo, Brazil
| | - Neus Barrantes-Vidal
- Departamento de Psicologia Clínica i de la Salut (Universitat Autònoma de Barcelona), Fundació Sanitària Sant Pere Claver (Spain), Spanish Mental Health Research Network (CIBERSAM), Barcelona, Spain
| | - Marie-Odile Krebs
- University Paris Descartes, Hôpital Sainte-Anne, C'JAAD, Service Hospitalo-Universitaire, Inserm U894, Institut de Psychiatrie (CNRS 3557), Paris, France
| | - Birte Glenthøj
- Centre for Neuropsychiatric Schizophrenia Research (CNSR) & Centre for Clinical Intervention and Neuropsychiatric SchizophreSnia Research (CINS), Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | - Gabriele Sachs
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | | | - Philip McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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Espinosa V, Bagaeva A, López-Carrilero R, Barajas A, Barrigón ML, Birulés I, Frígola-Capell E, Díaz-Cutraro L, González-Higueras F, Grasa E, Gutiérrez-Zotes A, Lorente-Rovira E, Pélaez T, Pousa E, Ruiz-Delgado I, Verdaguer-Rodríguez M, Ochoa S. Neuropsychological profiles in first-episodes psychosis and their relationship with clinical, metacognition and social cognition variables. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01813-z. [PMID: 38806850 DOI: 10.1007/s00406-024-01813-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 04/19/2024] [Indexed: 05/30/2024]
Abstract
An increasing interest in the assessment of neuropsychological performance variability in people with first-episode psychosis (FEP) has emerged. However, its association with clinical and functional outcomes requires further study. Furthermore, FEP neuropsychological subgroups have not been characterized by clinical insight or metacognition and social cognition domains. The aim of this exploratory study was to identify specific groups of patients with FEP based on neuropsychological variables and to compare their sociodemographic, clinical, metacognition and social cognition profiles. A sample of 149 FEP was recruited from adult mental health services. Neuropsychological performance was assessed by a neuropsychological battery (WAIS-III; TMT; WSCT; Stroop Test; TAVEC). The assessment also included sociodemographic characteristics, clinical, functional, metacognition and social cognition variables. Two distinct neuropsychological profiles emerged: one neuropsychological impaired cluster (N = 56) and one relatively intact cluster (N = 93). Significant differences were found between both profiles in terms of sociodemographic characteristics (age and level of education) (p = 0.001), clinical symptoms (negative, positive, disorganized, excitement and anxiety) (p = 0.041-0.001), clinical insight (p = 0.038-0.017), global functioning (p = 0.014), as well as in social cognition domains (emotional processing and theory of mind) (p = 0.001; p = 0.002). No significant differences were found in metacognitive variables (cognitive insight and 'jumping to conclusions' bias). Relationship between neurocognitive impairment, social cognition and metacognition deficits are discussed. Early identifying of neuropsychological profiles in FEP, characterized by significant differences in clinical and social cognition variables, could provide insight into the prognosis and guide the implementation of tailored early-intervention.
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Affiliation(s)
- Victoria Espinosa
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain.
- Fundació Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain.
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain.
| | - Alana Bagaeva
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Fundació Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Raquel López-Carrilero
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Fundació Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Ana Barajas
- Departament de Psicologia, Facultat de Psicologia Clínica I de la Salut. Serra Húnter Programme, Universitat Autònoma de Barcelona, Barcelona, Spain
- Departament of Research, Centre d'Higiene Mental Les Corts, Barcelona, Spain
| | - María Luisa Barrigón
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Departament of Psychiatry, University Hospital Virgen del Rocio, Sevilla, Spain
- Psychiatry Service, Area de Gestión Sanitaria Sur Granada, Motril, Granada, Spain
| | - Irene Birulés
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Facultat de Psicologia Departament de Cognició, Desenvolupament i Psicologia de l'Educació, Universitat de Barcelona, Barcelona, Spain
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Eva Frígola-Capell
- Mental Health and Addiction Research Group, Fundació Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta (IDIBGI), Girona, Spain
- Institut d'Assistencia Sanitària, Girona, Spain
| | - Luciana Díaz-Cutraro
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Fundació Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
- Psychology Department, FPCEE Blanquerna, Universitat Ramon Llull, Barcelona, Spain
| | | | - Eva Grasa
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, Hospital de La Santa Creu I Sant Pau, Institut d'Investigació Biomèdica-Sant Pau (IIB-Sant Pau), Barcelona, Spain
| | - Alfonso Gutiérrez-Zotes
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili-CERCA, Universitat Rovira I Virgili, Reus, Spain
| | - Ester Lorente-Rovira
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Psychiatry Service, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Trinidad Pélaez
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Esther Pousa
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychiatry, Hospital de La Santa Creu I Sant Pau, Institut d'Investigació Biomèdica-Sant Pau (IIB-Sant Pau), Barcelona, Spain
| | | | - Marina Verdaguer-Rodríguez
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Fundació Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193, Barcelona, Spain
| | - Susana Ochoa
- Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
- Etiopatogènia I Tractament Dels Trastorns Mentals Greus (MERITT), Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
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Soodla HL, Soidla K, Akkermann K. Reading tea leaves or tracking true constructs? An assessment of personality-based latent profiles in eating disorders. Front Psychiatry 2024; 15:1376565. [PMID: 38807687 PMCID: PMC11130490 DOI: 10.3389/fpsyt.2024.1376565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 04/12/2024] [Indexed: 05/30/2024] Open
Abstract
Background Eating disorder (ED) subtyping studies have often extracted an undercontrolled, an overcontrolled and a resilient profile based on trait impulsivity and perfectionism. However, the extent to which methodological choices impact the coherence and distinctness of resulting subtypes remains unclear. Objective In this paper, we aimed to assess the robustness of these findings by extracting personality-based subtypes on a sample of ED patients (N = 221) under different analytic conditions. Methods We ran four latent profile analyses (LPA), varying the extent to which we constrained variances and covariances during model parametrization. We then performed a comparative analysis also including state ED symptom measures as indicators. Finally, we used cross-method validation via k-means clustering to further assess the robustness of our profiles. Results Our results demonstrated a four-profile model based on variances in impulsivity and perfectionism to fit the data well. Across model solutions, the profiles with the most and least state and trait disturbances were replicated most stably, while more nuanced variations in trait variables resulted in less consistent profiles. Inclusion of ED symptoms as indicator variables increased subtype differentiation and similarity across profiles. Validation cluster analyses aligned most with more restrictive LPA models. Conclusion These results suggest that ED subtypes track true constructs, since subtypes emerged method-independently. We found analytic methods to constrain the theoretical and practical conclusions that can be drawn. This underscores the importance of objective-driven analytic design and highlights its relevance in applying research findings in clinical practice.
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Affiliation(s)
- Helo Liis Soodla
- Institute of Psychology, University of Tartu, Tartu, Estonia
- Centre for Cognitive and Behavioural Therapy, Tartu, Estonia
| | - Kärol Soidla
- Institute of Psychology, University of Tartu, Tartu, Estonia
- Centre for Cognitive and Behavioural Therapy, Tartu, Estonia
| | - Kirsti Akkermann
- Institute of Psychology, University of Tartu, Tartu, Estonia
- Centre for Cognitive and Behavioural Therapy, Tartu, Estonia
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Gupta T, Eckstrand KL, Lenniger CJ, Haas GL, Silk JS, Ryan ND, Phillips ML, Flores LE, Pizzagalli DA, Forbes EE. Anhedonia in adolescents at transdiagnostic familial risk for severe mental illness: Clustering by symptoms and mechanisms of association with behavior. J Affect Disord 2024; 347:249-261. [PMID: 37995926 PMCID: PMC10843785 DOI: 10.1016/j.jad.2023.11.062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 11/07/2023] [Accepted: 11/17/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Anhedonia is a transdiagnostic symptom of severe mental illness (SMI) and emerges during adolescence. Possible subphenotypes and neural mechanisms of anhedonia in adolescents at risk for SMI are understudied. METHODS Adolescents at familial risk for SMI (N = 81) completed anhedonia (e.g., consummatory, anticipatory, social), demographic, and clinical measures and one year prior, a subsample (N = 46) completed fMRI scanning during a monetary reward task. Profiles were identified using k-means clustering of anhedonia type and differences in demographics, suicidal ideation, impulsivity, and emotional processes were examined. Moderation analyses were conducted to investigate whether levels of brain activation of reward regions moderated the relationships between anhedonia type and behaviors. RESULTS Two-clusters emerged: a high anhedonia profile (high-anhedonia), characterized by high levels of all types of anhedonia, (N = 32) and a low anhedonia profile (low-anhedonia), characterized by low levels of anhedonia types (N = 49). Adolescents in the high-anhedonia profile reported more suicidal ideation and negative affect, and less positive affect and desire for emotional closeness than low-anhedonia profile. Furthermore, more suicidal ideation, less positive affect, and less desire for emotional closeness differentiated the familial high-risk, high-anhedonia profile adolescents from the familial high-risk, low-anhedonia profile adolescents. Across anhedonia profiles, moderation analyses revealed that adolescents with high dmPFC neural activation in response to reward had positive relationships between social, anticipatory, and consummatory anhedonia and suicidal ideation. LIMITATIONS Small subsample with fMRI data. CONCLUSION Profiles of anhedonia emerge transdiagnostically and vary on clinical features. Anhedonia severity and activation in frontostriatal reward areas have value for clinically important outcomes such as suicidal ideation.
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Affiliation(s)
- T Gupta
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, USA.
| | - K L Eckstrand
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, USA
| | - C J Lenniger
- University of Pittsburgh, Department of Psychology, Pittsburgh, PA, USA
| | - G L Haas
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, USA; University of Pittsburgh, Department of Psychology, Pittsburgh, PA, USA; VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - J S Silk
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, USA; University of Pittsburgh, Department of Psychology, Pittsburgh, PA, USA
| | - N D Ryan
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, USA
| | - M L Phillips
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, USA
| | - L E Flores
- Queens University, Department of Psychology, Kingston, Ontario, CA, USA
| | - D A Pizzagalli
- Harvard Medical School and McLean Hospital, Department of Psychiatry, Boston, MA, USA
| | - E E Forbes
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, USA; University of Pittsburgh, Department of Psychology, Pittsburgh, PA, USA; University of Pittsburgh, Department of Pediatrics, Pittsburgh, PA, USA; University of Pittsburgh, Department of Clinical and Translational Science, Pittsburgh, PA, USA
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Accardo V, Barlati S, Ceraso A, Nibbio G, Vieta E, Vita A. Efficacy of Functional Remediation on Cognitive and Psychosocial Functioning in Patients with Bipolar Disorder: Study Protocol for a Randomized Controlled Study. Brain Sci 2023; 13:brainsci13050708. [PMID: 37239180 DOI: 10.3390/brainsci13050708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 04/17/2023] [Accepted: 04/20/2023] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND Neurocognitive impairment is a prominent characteristic of bipolar disorder (BD), linked with poor psychosocial functioning. This study's purpose is to evaluate the effectiveness of functional remediation (FR) in enhancing neurocognitive dysfunctions in a sample of remitted patients with diagnosis of BD in comparison to treatment as usual-TAU. To quantify the neurocognitive damage, the Brief Assessment of Cognition in Affective Disorders (BAC-A) will be used, and the overall psychosocial functioning will be measured with the Functioning Assessment Short Test-FAST. METHODS The randomized, rater-blinded, controlled study will include two arms (1:1) encompassing 54 outpatients with diagnosis of BD-I and BD-II, as defined by the DSM-5 criteria. In the experimental phase, remitted patients aged 18-55 years will be involved. At the baseline, at the end of intervention and at the 6-month follow-up, patients will be evaluated using clinical scales (Young Mania Rating Scale (Y-MRS) and Hamilton Depression Rating Scale (HAM-D)). Neurocognitive measurements and psychosocial functioning will be valued, respectively, with BAC-A and FAST. DISCUSSION The primary expected outcome is that following FR intervention, patients will exhibit improved cognitive abilities and psychosocial outcomes compared to the participants in the TAU group. It is now recognized that neurocognitive deficits are potential predictors of functional outcome in patients with BD. In recent years, there has been a growing interest in the implementation of interventions that, in addition to symptomatic remission, are also aimed at neurocognitive dysfunctions in order to achieve a recovery of psychosocial functioning.
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Affiliation(s)
- Vivian Accardo
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, 25123 Brescia, Italy
| | - Stefano Barlati
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, 25123 Brescia, Italy
- Department of Clinical and Experimental Sciences, University of Brescia, 25123 Brescia, Italy
| | - Anna Ceraso
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, 25123 Brescia, Italy
| | - Gabriele Nibbio
- Department of Clinical and Experimental Sciences, University of Brescia, 25123 Brescia, Italy
| | - Eduard Vieta
- Hospital Clinic, Institute of Neuroscience, University of Barcelona, IDIBAPS, CIBERSAM, 08036 Barcelona, Spain
| | - Antonio Vita
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, 25123 Brescia, Italy
- Department of Clinical and Experimental Sciences, University of Brescia, 25123 Brescia, Italy
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Brain Morphological Characteristics of Cognitive Subgroups of Schizophrenia-Spectrum Disorders and Bipolar Disorder: A Systematic Review with Narrative Synthesis. Neuropsychol Rev 2023; 33:192-220. [PMID: 35194692 PMCID: PMC9998576 DOI: 10.1007/s11065-021-09533-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 11/23/2021] [Indexed: 10/19/2022]
Abstract
Despite a growing body of research, there is yet to be a cohesive synthesis of studies examining differences in brain morphology according to patterns of cognitive function among both schizophrenia-spectrum disorder (SSD) and bipolar disorder (BD) individuals. We aimed to provide a systematic overview of the morphological differences-inclusive of grey and white matter volume, cortical thickness, and cortical surface area-between cognitive subgroups of these disorders and healthy controls, and between cognitive subgroups themselves. An initial search of PubMed and Scopus databases resulted in 1486 articles of which 20 met inclusion criteria and were reviewed in detail. The findings of this review do not provide strong evidence that cognitive subgroups of SSD or BD map to unique patterns of brain morphology. There is preliminary evidence to suggest that reductions in cortical thickness may be more strongly associated with cognitive impairment, whilst volumetric deficits may be largely tied to the presence of disease.
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Bora E, Verim B, Akgul O, Ildız A, Ceylan D, Alptekin K, Özerdem A, Akdede BB. Clinical and developmental characteristics of cognitive subgroups in a transdiagnostic sample of schizophrenia spectrum disorders and bipolar disorder. Eur Neuropsychopharmacol 2023; 68:47-56. [PMID: 36640733 DOI: 10.1016/j.euroneuro.2022.12.005] [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: 08/24/2022] [Revised: 12/18/2022] [Accepted: 12/20/2022] [Indexed: 01/15/2023]
Abstract
Evidence suggests that neurocognitive dysfunction is a transdiagnostic feature of individuals across the continuum between schizophrenia and bipolar disorder. However, there is significant heterogeneity of neuropsychological and social-cognitive abilities in schizophrenia, schizoaffective disorder, and bipolar disorder. The current study aimed to investigate the clinical and developmental characteristics of cognitive subgroups within the schizo-bipolar spectrum. 147 clinically stable patients with schizophrenia, schizoaffective or bipolar disorder were assessed using clinical rating scales for current psychotic and affective symptoms, and a comprehensive neuropsychological battery including measures of social cognition (Hinting and Reading the mind from the Eyes (RMET) task)). Developmental history and premorbid academic functioning were also evaluated. The study also included 36 healthy controls. Neurocognitive subgroups were investigated using latent class analysis (LCA). The optimal number of clusters was determined based on the Bayesian information criterion. A logistic regression analysis was conducted to investigate the predictors of membership to the globally impaired subgroup. LCA revealed two neurocognitive clusters including globally impaired (n = 89, 60.5%) and near-normal cognitive functioning (n = 58, 39.5%) subgroups. The near-normal cognitive functioning subgroup was not significantly different from healthy controls. The globally impaired subgroup had a higher score of developmental abnormalities (p<0.001), poorer premorbid academic functioning, mothers who were less educated and more severe disorganized speech (p = 0.001) and negative symptoms (p = 0.004) compared to the near-normal cognitive functioning group. History of developmental abnormalities and persistent disorganization rather than diagnosis are significant predictors of the subgroup of individuals with global cognitive impairment in the schizophrenia-bipolar disorder continuum.
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Affiliation(s)
- Emre Bora
- Department of Psychiatry, Faculty of Medicine, Izmir, Turkey; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, Victoria 3053, Australia; Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey.
| | - Burcu Verim
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Ozge Akgul
- Department of Psychology, İzmir Demokrasi University, İzmir, Turkey
| | - Ayşegül Ildız
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Deniz Ceylan
- Department of Psychiatry and Psychology, Koc University, Istanbul, Turkey
| | - Köksal Alptekin
- Department of Psychiatry, Faculty of Medicine, Izmir, Turkey; Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Ayşegül Özerdem
- Department of Psychiatry and Psychology, Mayo Clinic Depression Center, Mayo Clinic, Rochester, MN, USA
| | - Berna Binnur Akdede
- Department of Psychiatry, Faculty of Medicine, Izmir, Turkey; Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
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9
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State of illness-dependent associations of neuro-cognition and psychopathological syndromes in a large transdiagnostic cohort. J Affect Disord 2023; 324:589-599. [PMID: 36586619 DOI: 10.1016/j.jad.2022.12.129] [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: 12/14/2021] [Revised: 05/19/2022] [Accepted: 12/23/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND There is a lack of knowledge regarding the relationship between dimensional psychopathological syndromes and neurocognitive functions, particularly across the major psychiatric disorders (i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), and Schizophrenia (SZ)). METHOD SANS, SAPS, HAMA, HAM-D, and YMRS were assessed in 1064 patients meeting DSM-IV-TR criteria for MDD, BD, SZ or schizoaffective disorder (SZA). In addition, a comprehensive neuropsychological test battery was administered. Psychopathological syndromes derived from factor analysis and present state of illness were used to explore psychopathology-cognition relationships. Correlational analyses were corrected for age, sex, verbal IQ, years of education, and DSM-IV-TR diagnosis. Age of onset and total duration of hospitalizations as proxies for illness severity were tested as moderators on the cognition - psychopathology relationship. RESULTS The negative syndrome, positive formal thought disorder as well as the paranoid-hallucinatory syndrome exhibited associations with neuro-cognition in an illness state-dependent manner, while the psychopathological factors depression and increased appetite only showed weak associations. Illness severity showed moderating effects on the neurocognitive-psychopathology relationship only for the negative syndrome and positive formal thought disorder. LIMITATIONS No healthy control subjects were entered into the analyses because of lack of variance in psychopathological symptoms, which prevents from drawing conclusions regarding the relative level of potential cognitive impairments. CONCLUSIONS This study suggests the relationship of neuro-cognition and psychopathology to be highly state of illness-dependent across affective and psychotic disorders. Results hint at the moderating effects of illness severity on psychopathological factors that might be more treatment resistant.
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10
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Li X, Deng W, Xue R, Wang Q, Ren H, Wei W, Zhang Y, Li M, Zhao L, Du X, Meng Y, Ma X, Hall MH, Li T. Auditory event-related potentials, neurocognition, and global functioning in drug naïve first-episode schizophrenia and bipolar disorder. Psychol Med 2023; 53:785-794. [PMID: 34474699 DOI: 10.1017/s0033291721002130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Deficits in event-related potential (ERP) including duration mismatch negativity (MMN) and P3a have been demonstrated widely in chronic schizophrenia (SZ) but inconsistent findings were reported in first-episode patients. Psychotropic medications and diagnosis might contribute to different findings on MMN/P3a ERP in first-episode patients. The present study examined MMN and P3a in first episode drug naïve SZ and bipolar disorder (BPD) patients and explored the relationships among ERPs, neurocognition and global functioning. METHODS Twenty SZ, 24 BPD and 49 age and sex-matched healthy controls were enrolled in this study. Data of clinical symptoms [Positive and Negative Symptoms Scale (PANSS), Young Manic Rating Scale (YMRS), Hamilton Depression Rating Scale (HAMD)], neurocognition [Wechsler Adult Intelligence Scale (WAIS), Cattell's Culture Fair Intelligence Test (CCFT), Delay Matching to Sample (DMS), Rapid Visual Information Processing (RVP)], and functioning [Functioning Assessment Short Test (FAST)] were collected. P3a and MMN were elicited using a passive auditory oddball paradigm. RESULTS Significant MMN and P3a deficits and impaired neurocognition were found in both SZ and BPD patients. In SZ, MMN was significantly correlated with FAST (r = 0.48) and CCFT (r = -0.31). In BPD, MMN was significantly correlated with DMS (r = -0.54). For P3a, RVP and FAST scores were significant predictors in SZ, whereas RVP, WAIS and FAST were significant predictors in BPD. CONCLUSIONS The present study found deficits in MMN, P3a, neurocognition in drug naïve SZ and BPD patients. These deficits appeared to link with levels of higher-order cognition and functioning.
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Affiliation(s)
- Xiaojing Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Wei Deng
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Rui Xue
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Hongyan Ren
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Wei Wei
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Yamin Zhang
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Mingli Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiangdong Du
- Suzhou Psychiatry hospital, The Affiliated Guangji Hospital of Soochow University, Jiangsu, China
| | - Yajing Meng
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Mei-Hua Hall
- Psychosis Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Tao Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Mental Health Education Center, Sichuan University, Chengdu, Sichuan, China
- Suzhou Psychiatry hospital, The Affiliated Guangji Hospital of Soochow University, Jiangsu, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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11
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Valli I, De la Serna E, Segura AG, Pariente JC, Calvet-Mirabent A, Borras R, Ilzarbe D, Moreno D, Martín-Martínez N, Baeza I, Rosa-Justicia M, Garcia-Rizo C, Díaz-Caneja CM, Crossley NA, Young AH, Vieta E, Mas S, Castro-Fornieles J, Sugranyes G. Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder. J Am Acad Child Adolesc Psychiatry 2023; 62:74-83. [PMID: 35710081 DOI: 10.1016/j.jaac.2022.05.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/21/2022] [Accepted: 06/06/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Cognitive impairment is an important feature of schizophrenia (SZ) and bipolar disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership. METHOD One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores. RESULTS Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area. CONCLUSION Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.
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Affiliation(s)
- Isabel Valli
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London.
| | - Elena De la Serna
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | | | - Jose C Pariente
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Roger Borras
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Daniel Ilzarbe
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Dolores Moreno
- Institute of Neuroscience, Hospital Clínic Barcelona, Spain; Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nuria Martín-Martínez
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Inmaculada Baeza
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Mireia Rosa-Justicia
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente Garcia-Rizo
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nicolas A Crossley
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Allan H Young
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, United Kingdom
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Sergi Mas
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; University of Barcelona, Spain
| | - Josefina Castro-Fornieles
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Gisela Sugranyes
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
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12
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Sumiyoshi C, Ohi K, Fujino H, Yamamori H, Fujimoto M, Yasuda Y, Uno Y, Takahashi J, Morita K, Katsuki A, Yamamoto M, Okahisa Y, Sata A, Katsumoto E, Koeda M, Hirano Y, Nakataki M, Matsumoto J, Miura K, Hashimoto N, Makinodan M, Takahashi T, Nemoto K, Kishimoto T, Suzuki M, Sumiyoshi T, Hashimoto R. Transdiagnostic comparisons of intellectual abilities and work outcome in patients with mental disorders: multicentre study. BJPsych Open 2022; 8:e98. [PMID: 35656577 PMCID: PMC9230699 DOI: 10.1192/bjo.2022.50] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Cognitive impairment is common in people with mental disorders, leading to transdiagnostic classification based on cognitive characteristics. However, few studies have used this approach for intellectual abilities and functional outcomes. AIMS The present study aimed to classify people with mental disorders based on intellectual abilities and functional outcomes in a data-driven manner. METHOD Seven hundred and forty-nine patients diagnosed with schizophrenia, bipolar disorder, major depression disorder or autism spectrum disorder and 1030 healthy control subjects were recruited from facilities in various regions of Japan. Two independent k-means cluster analyses were performed. First, intelligence variables (current estimated IQ, premorbid IQ, and IQ discrepancy) were included. Second, number of work hours per week was included instead of premorbid IQ. RESULTS Four clusters were identified in the two analyses. These clusters were specifically characterised in terms of IQ discrepancy in the first cluster analysis, whereas the work variable was the most salient feature in the second cluster analysis. Distributions of clinical diagnoses in the two cluster analyses showed that all diagnoses were unevenly represented across the clusters. CONCLUSIONS Intellectual abilities and work outcomes are effective classifiers in transdiagnostic approaches. The results of our study also suggest the importance of diagnosis-specific strategies to support functional recovery in people with mental disorders.
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Affiliation(s)
- Chika Sumiyoshi
- Faculty of Human Development and Culture, Fukushima University, Fukushima, Japan; Department of Preventive Intervention for Psychiatric Disorders and Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan; and Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Haruo Fujino
- United Graduate School of Child Development, Osaka University, Suita, Japan
| | - Hidenaga Yamamori
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan; Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan; and Japan Community Health Care Organization, Osaka Hospital, Osaka, Japan
| | - Michiko Fujimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan; and Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yuka Yasuda
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan; and Medical Corporation Foster, Life Grow Brilliant Mental Clinic, Osaka, Japan
| | - Yota Uno
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Junichi Takahashi
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kentaro Morita
- Day Hospital (Psychiatric Day Care) Department of Rehabilitation, University of Tokyo Hospital, Tokyo, Japan
| | - Asuka Katsuki
- Nijofukushikai Social Welfare Corporation Senjuen, Fukuoka, Japan
| | - Maeri Yamamoto
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Nagoya, Japan
| | - Yuko Okahisa
- Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | | | | | - Michihiko Koeda
- Department of Neuropsychiatry, Nippon Medical School, Tama Nagayama Hospital, Tama, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masahito Nakataki
- Department of Psychiatry, Tokushima University Hospital, Tokushima, Japan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Naoki Hashimoto
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Manabu Makinodan
- Department of Psychiatry, Nara Medical University School of Medicine, Kashihara, Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
| | - Kiyotaka Nemoto
- Department of Psychiatry, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
| | | | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
| | - Tomiki Sumiyoshi
- Department of Preventive Intervention for Psychiatric Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
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13
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A novel longitudinal clustering approach to psychopathology across diagnostic entities in the hospital-based PsyCourse study. Schizophr Res 2022; 244:29-38. [PMID: 35567871 DOI: 10.1016/j.schres.2022.05.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/23/2022] [Accepted: 05/02/2022] [Indexed: 12/21/2022]
Abstract
Biological research and clinical management in psychiatry face two major impediments: the high degree of overlap in psychopathology between diagnoses and the inherent heterogeneity with regard to severity. Here, we aim to stratify cases into homogeneous transdiagnostic subgroups using psychometric information with the ultimate aim of identifying individuals with higher risk for severe illness. 397 participants of the PsyCourse study with schizophrenia- or bipolar-spectrum diagnoses were prospectively phenotyped over 18 months. Factor analysis of mixed data of different rating scales and subsequent longitudinal clustering were used to cluster disease trajectories. Five clusters of longitudinal trajectories were identified in the psychopathologic dimensions. Clusters differed significantly with regard to Global Assessment of Functioning, disease course, and-in some cases-diagnosis while there were no significant differences regarding sex, age at baseline or onset, duration of illness, or polygenic burden for schizophrenia. Longitudinal clustering may aid in identifying transdiagnostic homogeneous subgroups of individuals with severe psychiatric disease.
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14
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Catalan A, Radua J, McCutcheon R, Aymerich C, Pedruzo B, González-Torres MÁ, Baldwin H, Stone WS, Giuliano AJ, McGuire P, Fusar-Poli P. Examining the variability of neurocognitive functioning in individuals at clinical high risk for psychosis: a meta-analysis. Transl Psychiatry 2022; 12:198. [PMID: 35551176 PMCID: PMC9098884 DOI: 10.1038/s41398-022-01961-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 04/18/2022] [Accepted: 04/27/2022] [Indexed: 11/09/2022] Open
Abstract
This study aims to meta-analytically characterize the presence and magnitude of within-group variability across neurocognitive functioning in young people at Clinical High-Risk for psychosis (CHR-P) and comparison groups. Multistep, PRISMA/MOOSE-compliant systematic review (PROSPERO-CRD42020192826) of the Web of Science database, Cochrane Central Register of Reviews and Ovid/PsycINFO and trial registries up to July 1, 2020. The risk of bias was assessed using a modified version of the NOS for cohort and cross-sectional studies. Original studies reporting neurocognitive functioning in individuals at CHR-P compared to healthy controls (HC) or first-episode psychosis (FEP) patients were included. The primary outcome was the random-effect meta-analytic variability ratios (VR). Secondary outcomes included the coefficient of variation ratios (CVR). Seventy-eight studies were included, relating to 5162 CHR-P individuals, 2865 HC and 486 FEP. The CHR-P group demonstrated higher variability compared to HC (in descending order of magnitude) in visual memory (VR: 1.41, 95% CI 1.02-1.94), executive functioning (VR: 1.31, 95% CI 1.18-1.45), verbal learning (VR: 1.29, 95% CI 1.15-1.45), premorbid IQ (VR: 1.27, 95% CI 1.09-1.49), processing speed (VR: 1.26, 95% CI 1.07-1.48), visual learning (VR: 1.20, 95% CI 1.07-1.34), and reasoning and problem solving (VR: 1.17, 95% CI 1.03-1.34). In the CVR analyses the variability in CHR-P population remains in the previous neurocognitive domains and emerged in attention/vigilance, working memory, social cognition, and visuospatial ability. The CHR-P group transitioning to psychosis showed greater VR in executive functioning compared to those not developing psychosis and compared to FEP groups. Clinical high risk for psychosis subjects shows increased variability in neurocognitive performance compared to HC. The main limitation of this study is the validity of the VR and CVR as an index of variability which has received debate. This finding should be explored by further individual-participant data research and support precision medicine approaches.
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Affiliation(s)
- Ana Catalan
- Mental Health Department. Basurto University Hospital. Biocruces Bizkaia Health Research Institute. Department of Neuroscience, Campus de Leioa, University of the Basque Country, UPV/EHU. Plaza de Cruces 12. 48903, Barakaldo, Bizkaia, Spain. .,Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Joaquim Radua
- grid.13097.3c0000 0001 2322 6764Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.10403.360000000091771775Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Mental Health Research Networking Center (CIBERSAM), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain ,grid.4714.60000 0004 1937 0626Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden
| | - Robert McCutcheon
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Claudia Aymerich
- grid.414269.c0000 0001 0667 6181Psychiatry Department, Basurto University Hospital, Bilbao, Spain
| | - Borja Pedruzo
- grid.414269.c0000 0001 0667 6181Psychiatry Department, Basurto University Hospital, Bilbao, Spain
| | - Miguel Ángel González-Torres
- grid.11480.3c0000000121671098Mental Health Department. Basurto University Hospital. Biocruces Bizkaia Health Research Institute. Department of Neuroscience, Campus de Leioa, University of the Basque Country, UPV/EHU. Plaza de Cruces 12. 48903, Barakaldo, Bizkaia Spain
| | - Helen Baldwin
- grid.13097.3c0000 0001 2322 6764Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - William S. Stone
- grid.239395.70000 0000 9011 8547Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA
| | - Anthony J. Giuliano
- grid.435881.30000 0001 0394 0960Worcester Recovery Center & Hospital, Massachusetts Department of Mental Health, Boston, MA USA
| | - Philip McGuire
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Paolo Fusar-Poli
- grid.13097.3c0000 0001 2322 6764Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.8982.b0000 0004 1762 5736Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy ,grid.451056.30000 0001 2116 3923National Institute for Health Research (NIHR) Biomedical Research Centre (BRC), London, UK ,grid.37640.360000 0000 9439 0839Outreach and Support in South London (OASIS) service, South London and Maudsley NHS Foundation Trust, London, UK
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15
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Yan W, Palaniyappan L, Liddle PF, Rangaprakash D, Wei W, Deshpande G. Characterization of Hemodynamic Alterations in Schizophrenia and Bipolar Disorder and Their Effect on Resting-State fMRI Functional Connectivity. Schizophr Bull 2022; 48:695-711. [PMID: 34951473 PMCID: PMC9077436 DOI: 10.1093/schbul/sbab140] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Common and distinct neural bases of Schizophrenia (SZ) and bipolar disorder (BP) have been explored using resting-state fMRI (rs-fMRI) functional connectivity (FC). However, fMRI is an indirect measure of neural activity, which is a convolution of the hemodynamic response function (HRF) and latent neural activity. The HRF, which models neurovascular coupling, varies across the brain within and across individuals, and is altered in many psychiatric disorders. Given this background, this study had three aims: quantifying HRF aberrations in SZ and BP, measuring the impact of such HRF aberrations on FC group differences, and exploring the genetic basis of HRF aberrations. We estimated voxel-level HRFs by deconvolving rs-fMRI data obtained from SZ (N = 38), BP (N = 19), and matched healthy controls (N = 35). We identified HRF group differences (P < .05, FDR corrected) in many regions previously implicated in SZ/BP, with mediodorsal, habenular, and central lateral nuclei of the thalamus exhibiting HRF differences in all pairwise group comparisons. Thalamus seed-based FC analysis revealed that ignoring HRF variability results in false-positive and false-negative FC group differences, especially in insula, superior frontal, and lingual gyri. HRF was associated with DRD2 gene expression (P < .05, 1.62 < |Z| < 2.0), as well as with medication dose (P < .05, 1.75 < |Z| < 3.25). In this first study to report HRF aberrations in SZ and BP, we report the possible modulatory effect of dopaminergic signalling on HRF, and the impact that HRF variability can have on FC studies in clinical samples. To mitigate the impact of HRF variability on FC group differences, we suggest deconvolution during data preprocessing.
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Affiliation(s)
- Wenjing Yan
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, USA
- Department of Information Management, School of E-business and Logistics, Beijing Technology and Business University, Beijing, China
| | - Lena Palaniyappan
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Peter F Liddle
- Centre for Translational Neuroimaging, Division of Mental Health and Clinical Neuroscience, Institute of Mental Health, University of Nottingham, UK
| | - D Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Wei Wei
- Department of Information Management, School of E-business and Logistics, Beijing Technology and Business University, Beijing, China
| | - Gopikrishna Deshpande
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, USA
- Department of Psychological Sciences, Auburn University, Auburn, AL
- Alabama Advanced Imaging Consortium, Birmingham, AL
- Center for Neuroscience, Auburn University, AL, USA
- School of Psychology, Capital Normal University, Beijing, China
- Key Laboratory for Learning and Cognition, Capital Normal University, Beijing, China
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
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16
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Sharpe V, Schoot L, Lewandowski KE, Ongur D, Türközer HB, Hasoglu T, Kuperberg GR. We both say tomato: Intact lexical alignment in schizophrenia and bipolar disorder. Schizophr Res 2022; 243:138-146. [PMID: 35290874 PMCID: PMC9188992 DOI: 10.1016/j.schres.2022.02.032] [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: 06/27/2021] [Revised: 01/10/2022] [Accepted: 02/24/2022] [Indexed: 11/15/2022]
Abstract
In people with schizophrenia and related disorders, impairments in communication and social functioning can negatively impact social interactions and quality of life. In the present study, we investigated the cognitive basis of a specific aspect of linguistic communication-lexical alignment-in people with schizophrenia and bipolar disorder. We probed lexical alignment as participants played a collaborative picture-naming game with the experimenter, in which the two players alternated between naming a dual-name picture (e.g., rabbit/bunny) and listening to their partner name a picture. We found evidence of lexical alignment in all three groups, with no differences between the patient groups and the controls. We argue that these typical patterns of lexical alignment in patients were supported by preserved-and in some cases increased-bottom-up mechanisms, which balanced out impairments in top-down perspective-taking.
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Affiliation(s)
- Victoria Sharpe
- Department of Psychology, Tufts University, Medford, MA, United States of America.
| | - Lotte Schoot
- Department of Psychology, Tufts University, Medford, MA
| | - Kathryn Eve Lewandowski
- McLean Hospital, Harvard Medical School, Belmont, MA,Department of Psychiatry, Harvard Medical School, Boston, MA
| | - Dost Ongur
- McLean Hospital, Harvard Medical School, Belmont, MA,Department of Psychiatry, Harvard Medical School, Boston, MA
| | - Halide Bilge Türközer
- McLean Hospital, Harvard Medical School, Belmont, MA,Department of Psychiatry, Harvard Medical School, Boston, MA,The University of Texas Southwestern Medical Center
| | - Tuna Hasoglu
- McLean Hospital, Harvard Medical School, Belmont, MA,Department of Psychiatry, Harvard Medical School, Boston, MA,Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA
| | - Gina R. Kuperberg
- Department of Psychology, Tufts University, Medford, MA,Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts General Hospital, Harvard Medical School, Boston, MA
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17
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Haining K, Gajwani R, Gross J, Gumley AI, Ince RAA, Lawrie SM, Schultze-Lutter F, Schwannauer M, Uhlhaas PJ. Characterising cognitive heterogeneity in individuals at clinical high-risk for psychosis: a cluster analysis with clinical and functional outcome prediction. Eur Arch Psychiatry Clin Neurosci 2022; 272:437-448. [PMID: 34401957 PMCID: PMC8938352 DOI: 10.1007/s00406-021-01315-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 07/26/2021] [Indexed: 12/24/2022]
Abstract
Schizophrenia is characterised by cognitive impairments that are already present during early stages, including in the clinical high-risk for psychosis (CHR-P) state and first-episode psychosis (FEP). Moreover, data suggest the presence of distinct cognitive subtypes during early-stage psychosis, with evidence for spared vs. impaired cognitive profiles that may be differentially associated with symptomatic and functional outcomes. Using cluster analysis, we sought to determine whether cognitive subgroups were associated with clinical and functional outcomes in CHR-P individuals. Data were available for 146 CHR-P participants of whom 122 completed a 6- and/or 12-month follow-up; 15 FEP participants; 47 participants not fulfilling CHR-P criteria (CHR-Ns); and 53 healthy controls (HCs). We performed hierarchical cluster analysis on principal components derived from neurocognitive and social cognitive measures. Within the CHR-P group, clusters were compared on clinical and functional variables and examined for associations with global functioning, persistent attenuated psychotic symptoms and transition to psychosis. Two discrete cognitive subgroups emerged across all participants: 45.9% of CHR-P individuals were cognitively impaired compared to 93.3% of FEP, 29.8% of CHR-N and 30.2% of HC participants. Cognitively impaired CHR-P participants also had significantly poorer functioning at baseline and follow-up than their cognitively spared counterparts. Specifically, cluster membership predicted functional but not clinical outcome. Our findings support the existence of distinct cognitive subgroups in CHR-P individuals that are associated with functional outcomes, with implications for early intervention and the understanding of underlying developmental processes.
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Affiliation(s)
- Kate Haining
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Ruchika Gajwani
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Andrew I Gumley
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Robin A A Ince
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Stephen M Lawrie
- Department of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Department of Psychology and Mental Health, Faculty of Psychology, Airlangga University, Surabaya, Indonesia
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany.
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18
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Engelke R, Ouanes S, Ghuloum S, Chamali R, Kiwan N, Sarwath H, Schmidt F, Suhre K, Al-Amin H. Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics: Comparison to Patients Off Antipsychotics and Normal Controls. Front Psychiatry 2022; 13:809071. [PMID: 35546954 PMCID: PMC9081931 DOI: 10.3389/fpsyt.2022.809071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/21/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Schizophrenia (SZ) and bipolar disorder (BD) share many features: overlap in mood and psychotic symptoms, common genetic predisposition, treatment with antipsychotics (APs), and similar metabolic comorbidities. The pathophysiology of both is still not well defined, and no biomarkers can be used clinically for diagnosis and management. This study aimed to assess the plasma proteomics profile of patients with SZ and BD maintained on APs compared to those who had been off APs for 6 months and to healthy controls (HCs). METHODS We analyzed the data using functional enrichment, random forest modeling to identify potential biomarkers, and multivariate regression for the associations with metabolic abnormalities. RESULTS We identified several proteins known to play roles in the differentiation of the nervous system like NTRK2, CNTN1, ROBO2, and PLXNC1, which were downregulated in AP-free SZ and BD patients but were "normalized" in those on APs. Other proteins (like NCAM1 and TNFRSF17) were "normal" in AP-free patients but downregulated in patients on APs, suggesting that these changes are related to medication's effects. We found significant enrichment of proteins involved in neuronal plasticity, mainly in SZ patients on APs. Most of the proteins associated with metabolic abnormalities were more related to APs use than having SZ or BD. The biomarkers identification showed specific and sensitive results for schizophrenia, where two proteins (PRL and MRC2) produced adequate results. CONCLUSIONS Our results confirmed the utility of blood samples to identify protein signatures and mechanisms involved in the pathophysiology and treatment of SZ and BD.
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Affiliation(s)
- Rudolf Engelke
- Proteomics Core, Research Department, Weill Cornell Medicine in Qatar, Doha, Qatar
| | - Sami Ouanes
- Psychiatry Department, Hamad Medical Corporation, Doha, Qatar
| | - Suhaila Ghuloum
- Psychiatry Department, Hamad Medical Corporation, Doha, Qatar
| | - Rifka Chamali
- Psychiatry Department, Weill Cornell Medicine, Doha, Qatar
| | - Nancy Kiwan
- Psychiatry Department, Weill Cornell Medicine, Doha, Qatar
| | - Hina Sarwath
- Proteomics Core, Research Department, Weill Cornell Medicine in Qatar, Doha, Qatar
| | - Frank Schmidt
- Proteomics Core, Research Department, Weill Cornell Medicine in Qatar, Doha, Qatar
| | - Karsten Suhre
- Bioinformatics Core, Research Department, Weill Cornell Medicine in Qatar, Doha, Qatar
| | - Hassen Al-Amin
- Psychiatry Department, Weill Cornell Medicine, Doha, Qatar
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19
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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.
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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
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20
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Pelin H, Ising M, Stein F, Meinert S, Meller T, Brosch K, Winter NR, Krug A, Leenings R, Lemke H, Nenadić I, Heilmann-Heimbach S, Forstner AJ, Nöthen MM, Opel N, Repple J, Pfarr J, Ringwald K, Schmitt S, Thiel K, Waltemate L, Winter A, Streit F, Witt S, Rietschel M, Dannlowski U, Kircher T, Hahn T, Müller-Myhsok B, Andlauer TFM. Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning. Neuropsychopharmacology 2021; 46:1895-1905. [PMID: 34127797 PMCID: PMC8429672 DOI: 10.1038/s41386-021-01051-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 05/24/2021] [Accepted: 05/28/2021] [Indexed: 02/07/2023]
Abstract
Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.
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Affiliation(s)
- Helena Pelin
- Max Planck Institute of Psychiatry, Munich, Germany.
- International Max Planck Research School for Translational Psychiatry, Munich, Germany.
| | - Marcus Ising
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Nils R Winter
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Julia Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Kai Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Fabian Streit
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie Witt
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marcella Rietschel
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Bertram Müller-Myhsok
- Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Till F M Andlauer
- Max Planck Institute of Psychiatry, Munich, Germany.
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
- Global Computational Biology and Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany.
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21
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Eum S, Hill SK, Alliey-Rodriguez N, Stevenson JM, Rubin LH, Lee AM, Mills LJ, Reilly JL, Lencer R, Keedy SK, Ivleva E, Keefe RSE, Pearlson GD, Clementz BA, Tamminga CA, Keshavan MS, Gershon ES, Sweeney JA, Bishop JR. Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders. Neuropsychopharmacology 2021; 46:1802-1810. [PMID: 34145405 PMCID: PMC8358015 DOI: 10.1038/s41386-021-01057-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 05/17/2021] [Accepted: 06/03/2021] [Indexed: 12/13/2022]
Abstract
Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.
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Affiliation(s)
- Seenae Eum
- grid.412555.20000 0001 0511 4494Department of Pharmacogenomics, Shenandoah University, Fairfax, VA USA
| | - S. Kristian Hill
- grid.262641.50000 0004 0388 7807Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL USA
| | - Ney Alliey-Rodriguez
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - James M. Stevenson
- grid.21107.350000 0001 2171 9311Division of Clinical Pharmacology, Department of Medicine, Johns Hopkins University, Baltimore, MD USA
| | - Leah H. Rubin
- grid.21107.350000 0001 2171 9311Departments of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD USA
| | - Adam M. Lee
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA
| | - Lauren J. Mills
- grid.17635.360000000419368657Masonic Cancer Center and Department of Pediatrics, University of Minnesota, Minneapolis, MN USA
| | - James L. Reilly
- grid.16753.360000 0001 2299 3507Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL USA
| | - Rebekka Lencer
- grid.5949.10000 0001 2172 9288Institute of Translational Psychiatry and Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Muenster, Muenster, Germany ,grid.4562.50000 0001 0057 2672Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Sarah K. Keedy
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - Elena Ivleva
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Richard S. E. Keefe
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry, Duke University School of Medicine, Durham, NC USA
| | - Godfrey D. Pearlson
- grid.277313.30000 0001 0626 2712Departments of Psychiatry and Neuroscience, Yale School of Medicine, Olin Center, Institute of Living, Hartford Healthcare, Hartford, CT USA
| | - Brett A. Clementz
- grid.213876.90000 0004 1936 738XDepartment of Psychology, University of Georgia, Athens, GA USA
| | - Carol A. Tamminga
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Matcheri S. Keshavan
- grid.239395.70000 0000 9011 8547Beth Israel Deaconess Medical Center, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Elliot S. Gershon
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - John A. Sweeney
- grid.413561.40000 0000 9881 9161Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, OH USA
| | - Jeffrey R. Bishop
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA ,grid.17635.360000000419368657Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN USA
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22
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Sparding T, Joas E, Clements C, Sellgren CM, Pålsson E, Landén M. Long-term trajectory of cognitive performance in people with bipolar disorder and controls: 6-year longitudinal study. BJPsych Open 2021; 7:e115. [PMID: 34140054 PMCID: PMC8240122 DOI: 10.1192/bjo.2021.66] [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] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Cross-sectional studies have found impaired cognitive functioning in patients with bipolar disorder, but long-term longitudinal studies are scarce. AIMS The aims of this study were to examine the 6-year longitudinal course of cognitive functioning in patients with bipolar disorder and healthy controls. Subsets of patients were examined to investigate possible differences in cognitive trajectories. METHOD Patients with bipolar I disorder (n = 44) or bipolar II disorder (n = 28) and healthy controls (n = 59) were tested with a comprehensive cognitive test battery at baseline and retested after 6 years. We conducted repeated measures ANCOVAs with group as a between-subject factor and tested the significance of group and time interaction. RESULTS By and large, the change in cognitive functioning between baseline and follow-up did not differ significantly between participants with bipolar disorder and healthy controls. Comparing subsets of patients, for example those with bipolar I and II disorder and those with and without manic episodes during follow-up, did not reveal subgroups more vulnerable to cognitive decline. CONCLUSIONS Cognitive performance remained stable in patients with bipolar disorder over a 6-year period and evolved similarly to healthy controls. These findings argue against the notion of a general progressive decline in cognitive functioning in bipolar disorder.
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Affiliation(s)
- Timea Sparding
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Erik Joas
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| | | | - Carl M Sellgren
- Department of Physiology and Pharmacology, Karolinska Institutet, Sweden
| | - Erik Pålsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Mikael Landén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
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23
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Tan EJ, Rossell SL, Subotnik KL, Ventura J, Nuechterlein KH. Cognitive heterogeneity in first-episode psychosis and its relationship with premorbid developmental adjustment. Psychol Med 2021; 52:1-10. [PMID: 33706841 DOI: 10.1017/s0033291721000738] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Patients with schizophrenia spectrum disorders have been increasingly recognised to form cognitive subgroups with differential levels of impairment. Using cluster analytical techniques, this study sought to identify cognitive clusters in a sample of first-episode psychosis (FEP) patients and examine clinical and developmental differences across the resultant groups. METHODS In total, 105 FEP patients in the University of California Los Angeles Aftercare Research Program were assessed for cognition, symptoms and premorbid developmental adjustment. Hierarchical cluster analysis with Ward's method and squared Euclidean distance was conducted, confirmed by discriminant function analysis and optimised with k-means clustering. The stability of the solution was evaluated through split-sample (random, 80 and 70% samples) and alternate method (average linkage method) replication via Cohen's κ analysis. Controlling for multiple comparisons, one-way analysis of variances examined group differences in symptom severity and premorbid adjustment. RESULTS Three groups were identified: severely impaired (n = 27), moderately impaired (n = 41) and relatively intact (n = 37). There were no significant differences in symptom severity across the groups. Significant differences were observed for scholastic performance at three different developmental stages: childhood, early adolescence and late adolescence, with the relatively intact group demonstrating significantly better scholastic performance at all three stages than both the moderately impaired and severely impaired groups (who did not significantly differ from each other). CONCLUSIONS The findings add to growing evidence that cognitive clusters in FEP mirror that of later-stage schizophrenia. They also suggest that premorbid scholastic performance may not just be a risk factor for developing schizophrenia, but is also related to cognitive impairment severity and potentially to prognosis.
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Affiliation(s)
- Eric J Tan
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
- Department of Psychiatry, St Vincent's Hospital, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health, Swinburne University of Technology, Melbourne, Australia
- Department of Psychiatry, St Vincent's Hospital, Melbourne, Australia
| | - Kenneth L Subotnik
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Joseph Ventura
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Keith H Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- UCLA Department of Psychology, Los Angeles, CA, USA
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24
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Cognitive heterogeneity in the offspring of patients with schizophrenia or bipolar disorder: a cluster analysis across family risk. J Affect Disord 2021; 282:757-765. [PMID: 33601716 DOI: 10.1016/j.jad.2020.12.090] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/13/2020] [Accepted: 12/22/2020] [Indexed: 01/22/2023]
Abstract
BACKGROUND Neurocognitive impairment is considered to lie on a continuum of severity across schizophrenia (SZ) and bipolar disorder (BP), possibly reflecting a gradient of neurodevelopmental load. Cluster analyses have identified different levels of impairment across the two disorders, from none to widespread and severe. We for the first time used this approach to examine cognitive function pooling together children and adolescents at familial risk of SZ or BP. METHODS 220 participants, 49 offspring of individuals with schizophrenia (SZO), 90 offspring of individuals with bipolar disorder (BPO) and 81 offspring of healthy control parents (HC), aged 6 to 17 years, underwent a comprehensive clinical and cognitive assessment. Cognitive measures were used to group SZO and BPO using K-means clustering. Cognitive performance within each of the clusters was compared to that of HC and clinical variables were compared between clusters. RESULTS We identified three cognitive subgroups: a moderate impairment group, a mild impairment group, and a cognitively intact group. Both SZO and BPO were represented in each of the clusters, yet not evenly, with a larger proportion of the SZO in the moderately impaired cluster, but also a subgroup of BPO showing moderate cognitive dysfunction. LIMITATIONS Participants have yet to reach the age of onset for the examined disorders. CONCLUSIONS The findings point to a range of neurodevelopmental loadings across youth at familial risk of both SZ and BP. They have therefore important implications for the stratification of cognitive functioning and the possibility to tailor interventions to individual levels of impairment.
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25
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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.
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26
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Liang S, Xing X, Wang M, Wei D, Tian T, Liu J, Sha S. The MATRICS Consensus Cognitive Battery: Psychometric Properties of the Chinese Version in Young Patients With Major Depression Disorder. Front Psychiatry 2021; 12:745486. [PMID: 34777049 PMCID: PMC8580868 DOI: 10.3389/fpsyt.2021.745486] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 09/27/2021] [Indexed: 01/10/2023] Open
Abstract
Background: Young patients with major depressive disorder are also associated with cognitive deficits. The development of an accurate and effective battery to measure cognitive impairment in young patients with major depressive disorder (Y-MDD) is necessary for both research and clinical practice. This study was designed to test the psychometric properties of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) in Y-MDD. Method: Fifty Y-MDD patients, 38 euthymic young patients with bipolar disorder (Y-BD), and 51 healthy teenagers were recruited. The MCCB and the Montreal Cognitive Assessment (MoCA) were administered to assess cognitive impairment at baseline. The MCCB was also assessed 2 weeks later in Y-MDD patients. All subjects were between the ages of 13 and 24 years. Result: In the current study, cognitive impairment was greater in Y-BD patients than in Y-MDD patients in some domains. The MCCB has good internal consistency and reliability in Y-MDD patients. The Pearson correlation coefficients for retest reliability were good. Our findings also revealed an acceptable correlation between the MCCB and the MoCA, indicating good concurrent validity of the MCCB. Furthermore, exploratory factor analysis of the MCCB in Y-MDD patients revealed five domains with acceptable internal structures. Conclusion: The MCCB has acceptable psychometric properties and is a sensitive battery of cognitive impairment in Y-MDD patients. In the future, additional studies need to be carried out with larger samples while controlling for the use of psychotropic medications and antidepressants to validate the findings of the present study.
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Affiliation(s)
- Sixiang Liang
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,The Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xiaomeng Xing
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,The Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Mingwan Wang
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,The Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Dan Wei
- School of Nursing, Peking Union Medical College, Beijing, China
| | - Tengfei Tian
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,The Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Jun Liu
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,The Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Sha Sha
- The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,The Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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27
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López-Villarreal A, Sánchez-Morla EM, Jiménez-López E, Martínez-Vizcaíno V, Aparicio AI, Mateo-Sotos J, Rodriguez-Jimenez R, Vieta E, Santos JL. Progression of the functional deficit in a group of patients with bipolar disorder: a cluster analysis based on longitudinal data. Eur Arch Psychiatry Clin Neurosci 2020; 270:947-957. [PMID: 31422453 DOI: 10.1007/s00406-019-01050-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Accepted: 08/07/2019] [Indexed: 12/23/2022]
Abstract
We aimed to examine the trajectory of psychosocial functioning in a sample of euthymic patients with bipolar disorder (BD) throughout a 5-year follow-up. Ninety-nine euthymic bipolar patients and 40 healthy controls (HC) were included. A neurocognitive assessment (17 neurocognitive measures grouped in 6 domains) was carried out at baseline. The split version of the Global Assessment of Functioning scale (GAF-F) and the Functioning Assessment Short Test (FAST) were used to examine psychosocial functioning at baseline (T1), and after a 5-year follow-up (T2). The statistical analysis was performed through repeated measures ANOVA and hierarchical cluster analysis based on the GAF-F and the FAST scores at T1 and T2. Eighty-seven patients (87.9%) were evaluated at T2. The cluster analysis identified two groups of patients. The first group included 44 patients (50.6%) who did not show a progression of the functional impairment (BD-NPI). The second cluster, which included 43 patients (49.4%), was characterized by a progression of the functional impairment (BD-PI). The BD-PI had a higher number of relapses and a higher number of hospitalizations during the follow-up period, as well as worse neurocognitive functioning than the BD-NPI. The repeated measures ANOVA confirmed that the psychosocial performance of BD-NPI is stable while there was a progression of the functional deterioration in BD-PI. The trajectory of the psychosocial functioning of patients with BD is not homogeneous. Our results suggest that in at least one subset of patients with BD, which might account for half of the patients, the disease has a progressive course.
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Affiliation(s)
- Ana López-Villarreal
- Department of Psychiatry, Hospital Virgen de La Luz CIBERSAM, Cuenca, Spain.,Neurobiological Research Group, Institute of Technology, Universidad de Castilla-La Mancha, Cuenca, Spain
| | - Eva María Sánchez-Morla
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), CIBERSAM, Madrid, Spain. .,CogPsy-Group, Universidad Complutense de Madrid (UCM), Madrid, Spain. .,Department of Psychiatry, Hospital Universitario 12 de Octubre, Avda. Córdoba km. 5400, 28041, Madrid, Spain.
| | - Estela Jiménez-López
- Department of Psychiatry, Hospital Virgen de La Luz CIBERSAM, Cuenca, Spain.,Neurobiological Research Group, Institute of Technology, Universidad de Castilla-La Mancha, Cuenca, Spain.,Health and Social Research Center, Universidad de Castilla-La Mancha, Cuenca, Spain
| | - Vicente Martínez-Vizcaíno
- Health and Social Research Center, Universidad de Castilla-La Mancha, Cuenca, Spain.,Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile
| | - Ana Isabel Aparicio
- Department of Psychiatry, Hospital Virgen de La Luz CIBERSAM, Cuenca, Spain.,Neurobiological Research Group, Institute of Technology, Universidad de Castilla-La Mancha, Cuenca, Spain
| | - Jorge Mateo-Sotos
- Neurobiological Research Group, Institute of Technology, Universidad de Castilla-La Mancha, Cuenca, Spain
| | - Roberto Rodriguez-Jimenez
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), CIBERSAM, Madrid, Spain.,CogPsy-Group, Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Eduard Vieta
- Department of Psychiatry, Hospital Clínic of Barcelona, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
| | - José Luis Santos
- Department of Psychiatry, Hospital Virgen de La Luz CIBERSAM, Cuenca, Spain.,Neurobiological Research Group, Institute of Technology, Universidad de Castilla-La Mancha, Cuenca, Spain
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28
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Léda-Rêgo G, Bezerra-Filho S, Miranda-Scippa Â. Functioning in euthymic patients with bipolar disorder: A systematic review and meta-analysis using the Functioning Assessment Short Test. Bipolar Disord 2020; 22:569-581. [PMID: 32243046 DOI: 10.1111/bdi.12904] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Systematically review the prevalence of functional impairment (FI) in euthymic patients with bipolar disorder (BD), as assessed only with the Functioning Assessment Short Test (FAST), explore the prevalence of this impairment among all the domains, identify the most compromised of them and the clinical variables associated with low functioning in this population. METHODS Meta-analyses were performed, searching for relevant papers published from 2007 to 2019 in Medline, Embase, Cochrane, PsycINFO databases and via hand-searching, without language restrictions. 1128 studies were initially identified, 13 of which were ultimately chosen based on the eligibility criteria. A two-step meta-analysis was performed using the mean difference with a 95% confidence interval for continuous variables and proportion estimation with a fixed-effects model for categorical variables. RESULTS In the first step, all FAST domains showed worse FI in patients than in healthy controls, with significant differences between groups. In the second step, the prevalence of FI domains were as follows: global, 58.6%; occupational, 65.6%; cognitive, 49.2%; autonomy, 42.6%; interpersonal relationships, 42.1%; leisure, 29.2%; and financial issues, 28.8%. Residual depressive symptoms were the most frequently cited variable associated with FI. CONCLUSIONS This study reinforces the relevant functional impact of BD in this population and suggests that the occupational domain may be the most impaired. Greater efforts should be directed toward targeting functioning in patient care, as it constitutes the most meaningful endpoint of response to treatment, especially with occupational and cognitive rehabilitation, thus allowing patients to overcome the course of illness and carry fulfilling lives.
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Affiliation(s)
- Gabriela Léda-Rêgo
- Mood and Anxiety Disorders Program (CETHA), Federal University of Bahia (UFBA), Salvador, Brazil.,Postgraduate Program in Medicine and Health, UFBA, Salvador, Brazil
| | - Severino Bezerra-Filho
- Mood and Anxiety Disorders Program (CETHA), Federal University of Bahia (UFBA), Salvador, Brazil.,Postgraduate Program in Medicine and Health, UFBA, Salvador, Brazil
| | - Ângela Miranda-Scippa
- Mood and Anxiety Disorders Program (CETHA), Federal University of Bahia (UFBA), Salvador, Brazil.,Postgraduate Program in Medicine and Health, UFBA, Salvador, Brazil.,Department of Neurosciences and Mental Health, Medical School, UFBA, Salvador, Brazil
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29
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Corponi F, Anmella G, Pacchiarotti I, Samalin L, Verdolini N, Popovic D, Azorin JM, Angst J, Bowden CL, Mosolov S, Young AH, Perugi G, Vieta E, Murru A. Deconstructing major depressive episodes across unipolar and bipolar depression by severity and duration: a cross-diagnostic cluster analysis on a large, international, observational study. Transl Psychiatry 2020; 10:241. [PMID: 32684621 PMCID: PMC7370235 DOI: 10.1038/s41398-020-00922-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 06/07/2020] [Accepted: 06/09/2020] [Indexed: 11/18/2022] Open
Abstract
A cross-diagnostic, post-hoc analysis of the BRIDGE-II-MIX study was performed to investigate how unipolar and bipolar patients suffering from an acute major depressive episode (MDE) cluster according to severity and duration. Duration of index episode, Clinical Global Impression-Bipolar Version-Depression (CGI-BP-D) and Global Assessment of Functioning (GAF) were used as clustering variables. MANOVA and post-hoc ANOVAs examined between-group differences in clustering variables. A stepwise backward regression model explored the relationship with the 56 clinical-demographic variables available. Agglomerative hierarchical clustering with two clusters was shown as the best fit and separated the study population (n = 2314) into 65.73% (Cluster 1 (C1)) and 34.26% (Cluster 2 (C2)). MANOVA showed a significant main effect for cluster group (p < 0.001) but ANOVA revealed that significant between-group differences were restricted to CGI-BP-D (p < 0.001) and GAF (p < 0.001), showing greater severity in C2. Psychotic features and a minimum of three DSM-5 criteria for mixed features (DSM-5-3C) had the strongest association with C2, that with greater disease burden, while non-mixed depression in bipolar disorder (BD) type II had negative association. Mixed affect defined as DSM-5-3C associates with greater acute severity and overall impairment, independently of the diagnosis of bipolar or unipolar depression. In this study a pure, non-mixed depression in BD type II significantly associates with lesser burden of clinical and functional severity. The lack of association for less restrictive, researched-based definitions of mixed features underlines DSM-5-3C specificity. If confirmed in further prospective studies, these findings would warrant major revisions of treatment algorithms for both unipolar and bipolar depression.
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Affiliation(s)
- Filippo Corponi
- grid.6292.f0000 0004 1757 1758Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy ,Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia Spain
| | - Gerard Anmella
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia Spain
| | - Isabella Pacchiarotti
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia Spain ,Biomedical Research Networking Center for Mental Health (CIBERSAM), Barcelona, Spain ,grid.10403.36August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Ludovic Samalin
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia Spain
| | - Norma Verdolini
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia Spain ,Biomedical Research Networking Center for Mental Health (CIBERSAM), Barcelona, Spain ,grid.10403.36August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Dina Popovic
- grid.413795.d0000 0001 2107 2845Psychiatry B, Chaim Sheba Medical Center, Ramat-Gan, Israel
| | - Jean-Michel Azorin
- grid.414438.e0000 0000 9834 707XDepartment of Psychiatry, Sainte Marguerite Hospital, Marseille, France
| | - Jules Angst
- grid.7400.30000 0004 1937 0650Department of Psychiatry, University of Zurich, Zurich, Switzerland
| | - Charles L. Bowden
- grid.267309.90000 0001 0629 5880Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX USA
| | - Sergey Mosolov
- grid.473242.4Department for Therapy of Mental Disorders, Moscow Research Institute of Psychiatry, Moscow, Russia
| | - Allan H. Young
- grid.13097.3c0000 0001 2322 6764Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, Centre for Affective Disorders, London, UK
| | - Giulio Perugi
- grid.5395.a0000 0004 1757 3729Clinica Psichiatrica, University of Pisa, Pisa, Italy
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain. .,Biomedical Research Networking Center for Mental Health (CIBERSAM), Barcelona, Spain. .,August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain.
| | - Andrea Murru
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clínic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia Spain ,Biomedical Research Networking Center for Mental Health (CIBERSAM), Barcelona, Spain ,grid.10403.36August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
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30
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Abstract
Bipolar disorder is associated with significant dysfunction in a broad range of neuropsychological domains and processes. Deficits have been reported to occur in symptomatic states (depression, [hypo]mania) as well as in remission (euthymia), having consequences for psychological well-being and social and occupational functioning. The profile and magnitude of neuropsychological deficits in bipolar disorder have been explored in a number of systematic reviews and meta-analyses. After discussing these briefly, this chapter will focus on examining the clinical and demographic factors that influence and modify the pattern and magnitude of deficits, as well as reviewing methods of assessment and analysis approaches which may improve our understanding of these problems.
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Affiliation(s)
- Peter Gallagher
- Faculty of Medical Sciences, Newcastle University - Translational and Clinical Research Institute, Newcastle upon Tyne, UK.
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31
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Benassi M, Garofalo S, Ambrosini F, Sant'Angelo RP, Raggini R, De Paoli G, Ravani C, Giovagnoli S, Orsoni M, Piraccini G. Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients. Front Psychol 2020; 11:1085. [PMID: 32587546 PMCID: PMC7299079 DOI: 10.3389/fpsyg.2020.01085] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Accepted: 04/28/2020] [Indexed: 11/15/2022] Open
Abstract
The heterogeneity of cognitive profiles among psychiatric patients has been reported to carry significant clinical information. However, how to best characterize such cognitive heterogeneity is still a matter of debate. Despite being well suited for clinical data, cluster analysis techniques, like the Two-Step and the Latent Class, received little to no attention in the literature. The present study aimed to test the validity of the cluster solutions obtained with Two-Step and Latent Class cluster analysis on the cognitive profile of a cross-diagnostic sample of 387 psychiatric inpatients. Two-Step and Latent Class cluster analysis produced similar and reliable solutions. The overall results reported that it is possible to group all psychiatric inpatients into Low and High Cognitive Profiles, with a higher degree of cognitive heterogeneity in schizophrenia and bipolar disorder patients than in depressive disorders and personality disorder patients.
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Affiliation(s)
| | - Sara Garofalo
- Department of Psychology, University of Bologna, Bologna, Italy
| | | | | | - Roberta Raggini
- AUSL della Romagna, SPDC Psychiatric Emergency Unit, Cesena, Italy
| | | | - Claudio Ravani
- AUSL della Romagna, SPDC Psychiatric Emergency Unit, Cesena, Italy
| | - Sara Giovagnoli
- Department of Psychology, University of Bologna, Bologna, Italy
| | - Matteo Orsoni
- Department of Psychology, University of Bologna, Bologna, Italy
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32
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Neurocognitive Impairment in Bipolar Disorder and Associated Factors: Using Population-based Norms and a Strict Criterion for Impairment Definition. Cogn Behav Neurol 2020; 33:103-112. [PMID: 32496295 DOI: 10.1097/wnn.0000000000000231] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Cognitive impairment is often identified in individuals with bipolar disorder and is associated with their functional impairment. However, there is controversy surrounding potential classification methods for impairment in cognitive measures. OBJECTIVE To examine the proportion of cognitive measures indicating impairment of attention, processing speed, memory, visuoconstructional abilities, and executive functions in individuals with bipolar disorder type I (euthymic) and healthy controls, using a strict criterion for defining impairment. METHODS We gave 43 individuals with bipolar disorder type I and 17 healthy controls a comprehensive clinical and neuropsychological assessment. All scores were standardized using means and standard deviations according to age. Impaired performance in all cognitive measures was determined using a distribution-based threshold of z=±1645. The effects of the sociodemographic and clinical variables on cognitive performance were examined using multiple stepwise backward regression analyses. RESULTS Clinically significant cognitive impairment was observed more frequently in the bipolar disorder group, compared to controls, on all measures. From participant factors, we found that level of education and number of manic episodes predicted variation in more cognitive measure scores. DISCUSSION The use of population-based norms to standardize cognitive measures, and a strict criterion to define cognitive impairment, in individuals with bipolar disorder type 1 and healthy controls resulted in a prevalence of impairment in cognitive domains' frequencies of deficits that fell within the ranges previously reported in meta-analyses. CONCLUSIONS Clinically introducing population norms and a stringent cognitive impairment criterion can facilitate more accurate measures of cognitive impairment in individuals with bipolar disorder.
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Neurocognitive heterogeneity across the spectrum of psychopathology: need for improved approaches to deficit detection and intervention. CNS Spectr 2020; 25:436-444. [PMID: 31131779 DOI: 10.1017/s1092852919001081] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Neurocognition is one of the strongest predictors of clinical and functional outcomes across the spectrum of psychopathology, yet there remains a dearth of unified neurocognitive nosology and available neurocognition-targeted interventions. Neurocognitive deficits manifest in a transdiagnostic manner, with no psychiatric disorder uniquely affiliated with one specific deficit. In fact, recent research has identified that essentially all investigated disorders are comprised of 3-4 neurocognitive profiles. This within-disorder neurocognitive heterogeneity has hampered the development of novel, neurocognition-targeted interventions, as only a portion of patients with any given disorder possess neurocognitive deficits that would warrant neurocognitive intervention. The development of criteria and terminology to characterize these neurocognitive deficit syndromes would provide clinicians with the opportunity to more systematically identify and treat their patients and provide researchers the opportunity to develop neurocognition-targeted interventions for patients. This perspective will summarize recent work and discuss possible approaches for neurocognition-focused diagnosis and treatment in psychiatry.
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Karantonis JA, Rossell SL, Carruthers SP, Sumner P, Hughes M, Green MJ, Pantelis C, Burdick KE, Cropley V, Van Rheenen TE. Cognitive validation of cross-diagnostic cognitive subgroups on the schizophrenia-bipolar spectrum. J Affect Disord 2020; 266:710-721. [PMID: 32056949 DOI: 10.1016/j.jad.2020.01.123] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Revised: 12/03/2019] [Accepted: 01/20/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs. METHOD Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline. RESULTS A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups. LIMITATIONS For clustering analysis, sample size was relatively small. CONCLUSIONS The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.
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Affiliation(s)
- James A Karantonis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Susan L Rossell
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; St Vincent's Mental Health, St Vincent's Hospital, VIC, Australia
| | - Sean P Carruthers
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip Sumner
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Matthew Hughes
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Melissa J Green
- School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW, Australia; Neuroscience Research Australia, Randwick, NSW, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia; Centre for Neuropsychiatric Schizophrenia Research (CNSR) and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Centre Glostrup, Glostrup, Denmark
| | - Katherine E Burdick
- Harvard Medical School, Department of Psychiatry, Boston, MA, United States; Brigham and Women's Hospital, Boston, MA, United States
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia.
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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: 51] [Impact Index Per Article: 10.2] [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.
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Affiliation(s)
| | | | - Javier I. Escobar
- Department of Psychiatry. Robert Wood Johnson Medical School, Rutgers University. New Brunswick, New Jersey
| | - Gabriel A. de Erausquin
- Department of Psychiatry and Neurology. University of Texas Rio Grande Valley School of Medicine. Harlingen, Texas
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Cognitive variability in bipolar I disorder: A cluster-analytic approach informed by resting-state data. Neuropharmacology 2019; 156:107585. [PMID: 30914304 DOI: 10.1016/j.neuropharm.2019.03.028] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 03/21/2019] [Accepted: 03/22/2019] [Indexed: 01/15/2023]
Abstract
BACKGROUND While the presence of cognitive performance deficits in bipolar disorder I (BD-I) is well established, there is no consensus about which cognitive abilities are affected. Heterogeneous phenotypes displayed in BD-I further suggest the existence of subgroups among the disorder. The present study sought to identify different cognitive profiles among BD-I patients as well as potentially underlying neuronal network changes. METHODS 54 euthymic BD-I patients underwent cognitive testing and resting state neuroimaging. Hierarchical cluster-analysis was performed on executive function scores of bipolar patients. The derived clusters were compared against 54 age-, gender- and IQ-matched healthy controls (HC) to facilitate the interpretation of results. Further, resting state network properties were compared to identify differences probably underlying cognitive profiles. RESULTS A three-cluster solution emerged. Cluster 1 (n = 22) was characterized by deficits in cognitive flexibility and motor inhibition, cluster 2 (n = 12) displayed impulsive decision-making, while cluster 3 (n = 20) showed good visuospatial planning. Weaker connections in cluster 1 compared to cluster 2 were found between regions activated during tasks cluster 1 showed deficits on. Cluster 3 had a higher modularity than cluster 2, which correlated positively with problem solving performance and risk-taking in this cluster. CONCLUSION Obtained clusters showed distinct cognitive profiles, characterized by deficits and strengths, most of which remained precluded in a general comparison. Weaker interregional connections and separated subnetworks might underly behavioral deficits and strengths, respectively. The findings help explain the phenotypic heterogeneity observed in BD-I. This article is part of the Special Issue entitled 'Current status of the neurobiology of aggression and impulsivity'.
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Etchepare A, Roux S, Destaillats JM, Cady F, Fontanier D, Couhet G, Prouteau A. What are the specificities of social cognition in schizophrenia? A cluster-analytic study comparing schizophrenia with the general population. Psychiatry Res 2019; 272:369-379. [PMID: 30599441 DOI: 10.1016/j.psychres.2018.12.042] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 12/03/2018] [Accepted: 12/06/2018] [Indexed: 12/28/2022]
Abstract
While social cognition (SC) is widely recognized as being impaired in schizophrenia, little is known about the potential heterogeneity in individuals' functioning. Using a wide range of SC measures and a cluster-analytic approach, we compared SC profiles in the general population and in people with schizophrenia. A total of 131 healthy controls and 101 participants with schizophrenia were included. Groups were compared on sociodemographic, neurocognition, anxiety and depressive mood variables. Three profiles were identified in healthy controls: one with good SC abilities (Homogeneous SC group) and two with specific weaknesses in complex Facial Emotion Recognition (Low FER group) or Affective Theory of Mind (Low AToM group). However, these patterns were not found in participants with schizophrenia, who were characterized rather by levels of SC functioning (i.e., Low, Medium and High SC groups). Importantly, while the High SC group (47.9% of the sample) exhibited normal performances, the two others were underpinned by different pathological processes (i.e., alexithymia for Medium SC group or neurocognition dysfunctioning for Low SC group). These results have important implications for future research as well as for clinical practice regarding assessment methodology and therapeutic interventions.
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Affiliation(s)
- Aurore Etchepare
- Laboratoire de Psychologie EA 4139, Université de Bordeaux, 3ter Place de la Victoire, 33 000 Bordeaux, France; Pôle de Soins de Réhabilitation de la Dordogne (PSRD), Centre Hospitalier Vauclaire, Lieu-dit Vauclaire, 24 700 Montpon-Ménestérol, France.
| | - Solenne Roux
- Laboratoire de Psychologie EA 4139, Université de Bordeaux, 3ter Place de la Victoire, 33 000 Bordeaux, France
| | - Jean-Marc Destaillats
- Département de Psychiatrie Adulte, Hôpital de Jonzac, Domaine des Fossés, 17 500 St Martial de Vitaterne, France
| | - Florian Cady
- Centre d'Evaluation et de Réhabilitation (CER), Centre Hospitalier Esquirol, 39 rue Jean-Baptiste Ruchaud, 87 000 Limoges, France
| | - David Fontanier
- Centre d'Evaluation et de Réhabilitation (CER), Centre Hospitalier Esquirol, 39 rue Jean-Baptiste Ruchaud, 87 000 Limoges, France
| | - Geoffroy Couhet
- Centre de Réhabilitation Psycho-Sociale (CRPS), Tour de Gassies, rue de la Tour-de-Gassies, 33 500 Bruges, France
| | - Antoinette Prouteau
- Laboratoire de Psychologie EA 4139, Université de Bordeaux, 3ter Place de la Victoire, 33 000 Bordeaux, France; Département de Psychiatrie Adulte, Hôpital de Jonzac, Domaine des Fossés, 17 500 St Martial de Vitaterne, France
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Proteomic Studies of Psychiatric Disorders. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2019; 1735:59-89. [PMID: 29380307 DOI: 10.1007/978-1-4939-7614-0_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Many diseases result from programming effects in utero. This chapter describes recent advances in proteomic studies which have improved our understanding of the underlying pathophysiological pathways in the major psychiatric disorders, resulting in the development of potential novel biomarker tests. Such tests should be based on measurement of blood-based proteins given the ease of accessibility of this medium and the known connections between the periphery and the central nervous system. Most importantly, emerging biomarker tests should be developed on lab-on-a-chip and other handheld devices to enable point-of-care use. This should help to identify individuals with psychiatric disorders much sooner than ever before, which will allow more rapid treatment options for the best possible patient outcomes.
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Parker S, Siskind D, Hermens DF, Dark F, McKeon G, Korman N, Arnautovska U, Harris M, Whiteford H. A Comprehensive Cohort Description and Statistical Grouping of Community-Based Residential Rehabilitation Service Users in Australia. Front Psychiatry 2019; 10:798. [PMID: 31780965 PMCID: PMC6857698 DOI: 10.3389/fpsyt.2019.00798] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 10/07/2019] [Indexed: 01/10/2023] Open
Abstract
Background: Community Care Units (CCUs) are a model of community-based residential rehabilitation support available in Australia that assists people affected by severe and persistent mental illness to enhance their independent living skills and community involvement. These services have been subject to limited evaluation, and available descriptions of consumer cohorts lack relevance to the understanding of their rehabilitation needs. Method: A clinical assessment battery covering a broad range of relevant domains was completed with consumers commencing at three CCUs in Queensland, Australia, between December 2014 and December 2017 (N = 145). The cohort was described based on demographic, diagnostic, treatment-related variables, and the assessment battery. The comparability of included sites was assessed. This contemporary cohort was also compared to the pooled cohort of Australian community-based residential rehabilitation services emerging from a previous systematic review. Additionally, cluster analysis (CA) was completed in two stages based on the clinician-rated assessments: hierarchical CA (Wards method) to identify the optimal number of clusters, followed by K-means clustering. Results: Dominant features of the cohort were male sex and the primary diagnoses of schizophrenia spectrum disorders. The average consumer age was 31.4 years. Most consumers were referred from the community, had been living with family, and were not subject to involuntary treatment orders. No site-based differences were observed on demographic, diagnostic and treatment-related variables. However, some site-based variation in levels of symptoms and functional impairment emerged. Overall, the cohort was comparable with the Transitional Residential Rehabilitation (TRR) cohort defined in a previous systematic review. Through CA, a three-cluster solution emerged: Cluster 1 (15%) was characterised by higher levels of substance use comorbidity; Cluster 2 (39%) was characterised by higher levels of disability and symptoms; and Cluster 3 (46%) was distinguished by lower levels of general psychiatric symptoms. Conclusions: The cohort was generally comparable to the TRR cohort. Site-based variability in the characteristics of admitted consumers was minimal. The CA solution suggested that three different sub-groups of consumers are admitted to CCUs, which have implications for adapting the approach to rehabilitation. Recommendations include ensuring early availability of interventions to address co-morbidities and pacing rehabilitation expectations to consumers stage of recovery.
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Affiliation(s)
- Stephen Parker
- Rehabilitation Academic Clinical Unit, Metro South Addiction and Mental Health Services (MSAMHS), Brisbane, QLD, Australia.,School of Public Health, University of Queensland, Herston, QLD, Australia
| | - Dan Siskind
- Rehabilitation Academic Clinical Unit, Metro South Addiction and Mental Health Services (MSAMHS), Brisbane, QLD, Australia.,School of Public Health, University of Queensland, Herston, QLD, Australia
| | - Daniel F Hermens
- Sunshine Coast Mind and Neuroscience-Thompson Institute, University of the Sunshine Coast, Birtinya, QLD, Australia
| | - Frances Dark
- Rehabilitation Academic Clinical Unit, Metro South Addiction and Mental Health Services (MSAMHS), Brisbane, QLD, Australia.,School of Public Health, University of Queensland, Herston, QLD, Australia
| | - Gemma McKeon
- Psychosis Academic Clinical Unit, Metro South Addiction and Mental Health Services (MSAMHS), Brisbane, QLD, Australia
| | - Nicole Korman
- Rehabilitation Academic Clinical Unit, Metro South Addiction and Mental Health Services (MSAMHS), Brisbane, QLD, Australia
| | - Urska Arnautovska
- PA Foundation, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Meredith Harris
- School of Public Health, University of Queensland, Herston, QLD, Australia
| | - Harvey Whiteford
- School of Public Health, University of Queensland, Herston, QLD, Australia
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Zhu Y, Womer FY, Leng H, Chang M, Yin Z, Wei Y, Zhou Q, Fu S, Deng X, Lv J, Song Y, Ma Y, Sun X, Bao J, Wei S, Jiang X, Tan S, Tang Y, Wang F. The Relationship Between Cognitive Dysfunction and Symptom Dimensions Across Schizophrenia, Bipolar Disorder, and Major Depressive Disorder. Front Psychiatry 2019; 10:253. [PMID: 31105603 PMCID: PMC6498739 DOI: 10.3389/fpsyt.2019.00253] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 04/02/2019] [Indexed: 12/18/2022] Open
Abstract
Background: Cognitive dysfunction is considered a core feature among schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Despite abundant literature comparing cognitive dysfunction among these disorders, the relationship between cognitive dysfunction and symptom dimensions remains unclear. The study aims are a) to identify the factor structure of the BPRS-18 and b) to examine the relationship between symptom domains and cognitive function across SZ, BD, and MDD. Methods: A total of 716 participants [262 with SZ, 104 with BD, 101 with MDD, and 249 healthy controls (HC)] were included in the study. One hundred eighty participants (59 with SZ, 23 with BD, 24 with MDD, and 74 HC) completed the MATRICS Consensus Cognitive Battery (MCCB), and 507 participants (85 with SZ, 89 with BD, 90 with MDD, and 243 HC) completed the Wisconsin Card Sorting Test (WCST). All patients completed the Brief Psychiatric Rating Scale (BPRS). Results: We identified five BPRS exploratory factor analysis (EFA) factors ("affective symptoms," "psychosis," "negative/disorganized symptoms," "activation," and "noncooperation") and found cognitive dysfunction in all of the participant groups with psychiatric disorders. Negative/disorganized symptoms were the most strongly associated with cognitive dysfunctions across SZ, BD, and MDD. Conclusions: Our findings suggest that cognitive dysfunction severity relates to the negative/disorganized symptom domain across SZ, BD, and MDD, and negative/disorganized symptoms may be an important target for effective cognitive remediation in SZ, BD, and MDD.
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Affiliation(s)
- Yue Zhu
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fay Y Womer
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, United States
| | - Haixia Leng
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Miao Chang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zhiyang Yin
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yange Wei
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Qian Zhou
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Shanghai Mental Health Center, Shanghai, China
| | - Shinan Fu
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xin Deng
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jing Lv
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yanzhuo Song
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yinzhu Ma
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xinyu Sun
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jing Bao
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Shengnan Wei
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xiaowei Jiang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Shuping Tan
- Center for Psychiatric Research, Beijing Huilongguan Hospital, Beijing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Gerontology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
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Sauvé G, Malla A, Joober R, Brodeur MB, Lepage M. Comparing cognitive clusters across first- and multiple-episode of psychosis. Psychiatry Res 2018; 269:707-718. [PMID: 30273896 DOI: 10.1016/j.psychres.2018.08.119] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Revised: 07/11/2018] [Accepted: 08/28/2018] [Indexed: 12/13/2022]
Abstract
Cognitive impairments in psychotic disorders (PD) present heterogeneously across patients. Between 2 and 5 clusters have been identified in previous studies with first-episode (FEP) and multiple-episodes of psychosis (MEP) patients suggesting different profiles of impairment. Past findings suggest there are differences between FEP and MEP patients regarding severity and number of affected cognitive domains. Heterogeneity of cognitive deficits in PD has perhaps hindered our understanding of their course. The present study compared non-affective FEP and MEP patients to assess whether illness chronicity could influence cognitive impairment profiles. We analyzed cognitive data, collected with the Cogstate Schizophrenia Battery, of FEP and MEP patients using cluster analysis. We compared clustering methods to obtain a more robust solution. For FEP patients, data were collected at their entry to a specialized clinic; the MEP group consisted of in- and outpatients. Results suggested cognitive heterogeneity was similar in FEP and MEP samples, although in different proportions. Three clusters were identified as the most stable solution and comprised groups of patients with either 1- no cognitive impairment (over-representation of FEP), 2- generalized deficits (over-representation of MEP), or 3- intermediate impairments. These findings encourage early interventions adapted to the profile of impairment.
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Affiliation(s)
- Geneviève Sauvé
- Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Ashok Malla
- Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Ridha Joober
- Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Mathieu B Brodeur
- Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Martin Lepage
- Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Montreal, Quebec, Canada.
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Hajdúk M, Harvey PD, Penn DL, Pinkham AE. Social cognitive impairments in individuals with schizophrenia vary in severity. J Psychiatr Res 2018; 104:65-71. [PMID: 29982084 DOI: 10.1016/j.jpsychires.2018.06.017] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 06/05/2018] [Accepted: 06/28/2018] [Indexed: 01/02/2023]
Abstract
Social cognitive deficits are a hallmark feature of schizophrenia and have been confirmed by several meta-analyses; however, the uniformity of these impairments across individuals remains unknown. The present study evaluated the heterogeneity of social cognitive impairment. A secondary aim was to identify a subset of measures to quickly identify those individuals who are most in need of remediation. Two independent samples of people with schizophrenia (n = 176; n = 178) and their respective healthy control groups (n = 104; n = 154) were selected from two phases of the Social Cognition Psychometric Evaluation (SCOPE) project, which assessed multiple domains of social cognition. Latent profile analysis was utilized to identify sub-clusters of performance within each patient sample. Receiver operator curve and discriminant analysis were implemented to identify tasks suitable as screening tools. Three clusters were identified in each sample that differed primarily in severity of impairment. The first showed no social cognitive impairment (∼25% of patients). The second consisted of patients with mild impairment (∼40% of each sample), and the third showed severe SC impairment (∼32%). Patients in the severe cluster were older, less educated, more neurocognitively impaired, and lower functioning. Using the Bell Lysaker Emotion Recognition Task (BLERT) for screening provided sensitivity of 80.15% and specificity 89.13%. Combining BLERT with the Reading the Mind in the Eyes task yielded sensitivity of 91.60% and specificity 75.00% for identifying impaired individuals. These results illustrate the existence of distinct degrees of social cognitive impairment in schizophrenia and indicate that remediation efforts may not be necessary for all individuals.
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Affiliation(s)
- Michal Hajdúk
- Department of Psychology, Faculty of Arts, Comenius University, Bratislava, Slovak Republic; Department of Psychiatry, Faculty of Medicine, Comenius University, Bratislava, Slovak Republic
| | - Philip D Harvey
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, USA; Research Service, Miami VA Healthcare System, USA
| | - David L Penn
- Department of Psychology, University of North Carolina, Chapel Hill, NC, USA; School of Psychology, Australian Catholic University, Melbourne, VIC, Australia
| | - Amy E Pinkham
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, USA; Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, USA.
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Bora E. Neurocognitive features in clinical subgroups of bipolar disorder: A meta-analysis. J Affect Disord 2018; 229:125-134. [PMID: 29306692 DOI: 10.1016/j.jad.2017.12.057] [Citation(s) in RCA: 113] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2017] [Revised: 12/17/2017] [Accepted: 12/27/2017] [Indexed: 02/06/2023]
Abstract
OBJECTIVE There is a significant cognitive heterogeneity in bipolar disorder (BD). The aim of this systematic review was to examine the potential distinctive neuropsychological of features of clinical subgroups of BD. A literature search investigating cognitive differences between potential subtypes of BD was conducted. METHODS It was possible to conduct a meta-analysis of studies investigating the relationship between cognitive deficits and subgroups of DSM-IV BD (type I (BD-I) and type II (BD-II)), subgroups based on history of psychosis (PBD and NPBD). The cognitive domains investigated in this meta-analysis included verbal memory, visual memory, processing speed, executive functions speed (EF-speed), EF-accuracy, attention, working memory, social cognition. Current meta-analysis included 48 reports and compared cognitive performances of 1211 BD-I and 836 BD-II patients. It also compared cognitive functioning in 1017 PBD and 744 NPBD patients. RESULTS Both history of psychosis (d = 0.19) and BD-I (d = 0.17) diagnosis were associated with modestly more pronounced global cognitive impairment. In specific domains, BD-I significantly underperformed BD-II in verbal memory, processing speed, EF-speed, EF-accuracy (d = 0.15-0.26). PBD was associated with significantly impaired cognition compared to NPBD in verbal memory, processing speed, EF-speed, EF-accuracy, working memory and social cognition (d = 0.12-0.28). CONCLUSION In BD, history of psychosis and full-manic episode are modestly associated with increased cognitive deficits. Neurocognitive differences between clinical subtypes of BD are quite subtle and are not distinctive. Furthermore, other factors reflecting differences in illness severity can explain observed between-group differences. Most of the cognitive heterogeneity in BD cannot be explained by proposed subtypes of BD.
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Affiliation(s)
- Emre Bora
- Dokuz Eylül University, Faculty of Medicine, Department of Psychiatry, Izmir, Turkey; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, Victoria 3053, Australia.
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Assessing the Relationship between Performance on the University of California Performance Skills Assessment (UPSA) and Outcomes in Schizophrenia: A Systematic Review and Evidence Synthesis. SCHIZOPHRENIA RESEARCH AND TREATMENT 2018; 2018:9075174. [PMID: 30687553 PMCID: PMC6327277 DOI: 10.1155/2018/9075174] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 11/12/2018] [Accepted: 12/05/2018] [Indexed: 01/18/2023]
Abstract
OBJECTIVE To perform a systematic review of the published literature to evaluate how functional capacity, as measured by the University of California at San Diego (UCSD) Performance-based Skills Assessment (UPSA), relates to other functional measures and real-world outcomes among individuals with schizophrenia. METHODS The MEDLINE® and Embase® databases were searched to identify joint evaluations with UPSA and key functional outcomes (functional scale measures; generic or disease-specific, health-related quality of life [HRQoL]; or real-world outcomes [residential status; employment status]) in patients with schizophrenia. Pearson correlations were estimated between UPSA scores, HRQoL, other functional scale measures, and real-world outcomes, for outcomes described in at least six studies. RESULTS The synthesis included 76 studies that provided 73 unique data sets. Quantitative assessment between the Specific Level of Function (SLOF) (n=18) scores and UPSA scores demonstrated a moderate borderline-significant correlation (0.45, p=0.06). Quantitative analysis of the relationship between the Global Assessment of Functioning (GAF) (n=11) and the Multidimensional Scale of Independent Functioning (MSIF) (n=6) scales revealed moderate and small nonsignificant Pearson correlations of -0.34 (p=0.31) and 0.12 (p=0.83), respectively. There was a small borderline-significant correlation between UPSA score and residential status (n=36; 0.31; p=0.08), while no correlation was found between UPSA score and employment status (n=19; 0.04; p=0.88). CONCLUSION The SLOF was the most often used functional measure and had the strongest observed correlation with the UPSA. Although knowledge gaps remain, evidence from this review indicates that there is a quantitative relationship between functional capacity and real-world outcomes in individuals with schizophrenia.
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Cognitive burden of anticholinergic medications in psychotic disorders. Schizophr Res 2017; 190:129-135. [PMID: 28390849 PMCID: PMC5628100 DOI: 10.1016/j.schres.2017.03.034] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 03/10/2017] [Accepted: 03/13/2017] [Indexed: 12/25/2022]
Abstract
BACKGROUND Patients with psychotic disorders are often treated with numerous medications, many of which have anticholinergic activity. We assessed cognition in relation to the cumulative anticholinergic burden of multiple drugs included in treatment regimens of participants from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. METHOD Clinically stable participants with schizophrenia (n=206), schizoaffective disorder (n=131), and psychotic bipolar disorder (n=146) were examined. Anticholinergic properties of all scheduled drugs were quantified using the Anticholinergic Drug Scale (ADS). ADS scores were summed across individual drugs to create a total ADS burden score for each participant and examined in relation to the Brief Assessment of Cognition in Schizophrenia (BACS). RESULTS Anticholinergic burden aggregated across all medications was inversely related to cognitive performance starting at ADS scores of 4 in participants with schizophrenia. Those with ADS scores ≥4 had lower composite BACS scores compared to those with ADS<4 (p=0.004). Among BACS subtests, Verbal Memory was the most adversely affected by high anticholinergic burden. Despite similar anticholinergic burden scores across groups, a significant threshold effect of anticholinergic burden was not detected in schizoaffective or psychotic bipolar disorder. CONCLUSION We identified an adverse effect threshold of anticholinergic burden on cognition in clinically stable participants with schizophrenia. This relationship was not identified in affective psychoses. Examination of other medications, doses, and clinical measures did not account for these findings. Patients with schizophrenia may have increased cognitive susceptibility to anticholinergic medications and the aggregate effects of one's medication regimen may be important to consider in clinical practice.
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Sparding T, Silander K, Pålsson E, Östlind J, Ekman CJ, Sellgren CM, Joas E, Hansen S, Landén M. Classification of cognitive performance in bipolar disorder. Cogn Neuropsychiatry 2017; 22:407-421. [PMID: 28789589 DOI: 10.1080/13546805.2017.1361391] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE To understand the etiology of cognitive impairment associated with bipolar disorder, we need to clarify potential heterogeneity in cognitive functioning. To this end, we used multivariate techniques to study if the correlation structure of cognitive abilities differs between persons with bipolar disorder and controls. METHOD Clinically stable patients with bipolar disorder (type I: n = 64; type II: n = 44) and healthy controls (n = 86) were assessed with a wide range of cognitive tests measuring executive function, speed, memory, and verbal skills. Data were analysed with multivariate techniques. RESULTS A distinct subgroup (∼30%) could be identified that performed significantly poorer on tests concerning memory function. This cognitive phenotype subgroup did not differ from the majority of bipolar disorder patients with respect to other demographic or clinical characteristics. CONCLUSIONS Whereas the majority of patients performed similar to controls, a subgroup of patients with bipolar disorder differed substantially from healthy controls in the correlation pattern of low-level cognitive abilities. This suggests that cognitive impairment is not a general trait in bipolar disorder but characteristic of a cognitive subgroup. This has important clinical implications for cognitive rehabilitation and remediation.
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Affiliation(s)
- Timea Sparding
- a Department of Psychiatry and Neurochemistry , Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg , Gothenburg , Sweden
| | - Katja Silander
- b Department of Psychology , University of Gothenburg , Gothenburg , Sweden
| | - Erik Pålsson
- a Department of Psychiatry and Neurochemistry , Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg , Gothenburg , Sweden
| | - Josefin Östlind
- a Department of Psychiatry and Neurochemistry , Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg , Gothenburg , Sweden
| | - Carl Johan Ekman
- c Department of Clinical Neuroscience , Karolinska Institutet , Stockholm , Sweden
| | - Carl M Sellgren
- d Center for Experimental Drugs and Diagnostics, Center for Genomic Medicine and Department of Psychiatry, Massachusetts General Hospital , Boston , MA , USA
| | - Erik Joas
- a Department of Psychiatry and Neurochemistry , Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg , Gothenburg , Sweden
| | - Stefan Hansen
- b Department of Psychology , University of Gothenburg , Gothenburg , Sweden
| | - Mikael Landén
- a Department of Psychiatry and Neurochemistry , Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg , Gothenburg , Sweden.,e Department of Medical Epidemiology and Biostatistics , Karolinska Institutet , Stockholm , Sweden
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Lannoy S, Billieux J, Poncin M, Maurage P. Binging at the campus: Motivations and impulsivity influence binge drinking profiles in university students. Psychiatry Res 2017; 250:146-154. [PMID: 28161610 DOI: 10.1016/j.psychres.2017.01.068] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 12/16/2016] [Accepted: 01/24/2017] [Indexed: 12/14/2022]
Abstract
This study explored the involvement of two key psychological factors, drinking motives and impulsivity traits, in binge drinking. On the basis of a large screening phase (N=4424), 867 binge drinkers were selected and were first compared with 924 non-binge drinkers. Then, a cluster analysis was performed, focusing on the binge drinker sample, to explore the respective involvement of four drinking motives (DMQ-R model) and four impulsivity facets (UPPS model) in this habit. Centrally, the cluster analysis identified three clusters of binge drinkers presenting distinct psychological characteristics and alcohol consumption patterns: emotional, recreational, and hazardous binge drinkers. Hazardous binge drinkers were characterized by strong drinking motives but moderate impulsivity. Binge drinking should thus no more be considered as a unitary drinking pattern but rather as a habit encompassing a variety of psychological profiles. Moreover, risky drinking habits in young people might be mainly related to disproportionate drinking motives. Future studies should thus consider binge drinking heterogeneity, and prevention programs focusing on drinking motivations should be developed.
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Affiliation(s)
- Séverine Lannoy
- Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Université catholique de Louvain, Place C. Mercier, 10, B-1348 Louvain-la-Neuve, Louvain-la-Neuve, Belgium.
| | - Joël Billieux
- Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Université catholique de Louvain, Place C. Mercier, 10, B-1348 Louvain-la-Neuve, Louvain-la-Neuve, Belgium; Institute for Health and Behavior, Integrative Research Unit on Social and Individual Development (INSIDE), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
| | - Marie Poncin
- Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Université catholique de Louvain, Place C. Mercier, 10, B-1348 Louvain-la-Neuve, Louvain-la-Neuve, Belgium.
| | - Pierre Maurage
- Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Université catholique de Louvain, Place C. Mercier, 10, B-1348 Louvain-la-Neuve, Louvain-la-Neuve, Belgium.
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