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Qiu L, Liang C, Kochunov P, Hutchison KE, Sui J, Jiang R, Zhi D, Vergara VM, Yang X, Zhang D, Fu Z, Bustillo JR, Qi S, Calhoun VD. Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging. Transl Psychiatry 2024; 14:326. [PMID: 39112461 PMCID: PMC11306356 DOI: 10.1038/s41398-024-03035-2] [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: 09/18/2023] [Revised: 07/18/2024] [Accepted: 07/23/2024] [Indexed: 08/10/2024] Open
Abstract
People affected by psychotic, depressive and developmental disorders are at a higher risk for alcohol and tobacco use. However, the further associations between alcohol/tobacco use and symptoms/cognition in these disorders remain unexplored. We identified multimodal brain networks involving alcohol use (n = 707) and tobacco use (n = 281) via supervised multimodal fusion and evaluated if these networks affected symptoms and cognition in people with psychotic (schizophrenia/schizoaffective disorder/bipolar, n = 178/134/143), depressive (major depressive disorder, n = 260) and developmental (autism spectrum disorder/attention deficit hyperactivity disorder, n = 421/346) disorders. Alcohol and tobacco use scores were used as references to guide functional and structural imaging fusion to identify alcohol/tobacco use associated multimodal patterns. Correlation analyses between the extracted brain features and symptoms or cognition were performed to evaluate the relationships between alcohol/tobacco use with symptoms/cognition in 6 psychiatric disorders. Results showed that (1) the default mode network (DMN) and salience network (SN) were associated with alcohol use, whereas the DMN and fronto-limbic network (FLN) were associated with tobacco use; (2) the DMN and fronto-basal ganglia (FBG) related to alcohol/tobacco use were correlated with symptom and cognition in psychosis; (3) the middle temporal cortex related to alcohol/tobacco use was associated with cognition in depression; (4) the DMN related to alcohol/tobacco use was related to symptom, whereas the SN and limbic system (LB) were related to cognition in developmental disorders. In summary, alcohol and tobacco use were associated with structural and functional abnormalities in DMN, SN and FLN and had significant associations with cognition and symptoms in psychotic, depressive and developmental disorders likely via different brain networks. Further understanding of these relationships may assist clinicians in the development of future approaches to improve symptoms and cognition among psychotic, depressive and developmental disorders.
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Affiliation(s)
- Ling Qiu
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
- Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Chuang Liang
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
- Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kent E Hutchison
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Victor M Vergara
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Xiao Yang
- Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Daoqiang Zhang
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
- Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Juan R Bustillo
- Departments of Neurosciences and Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA.
| | - Shile Qi
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
- Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
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Greve AN, Hemager N, Mortensen EL, Gantriis DL, Burton BK, Ellersgaard D, Plessen KJ, Thorup AAE, Jepsen JRM, Nordentoft M, Mors O, Simonsen A. Comparing cognition in parents with schizophrenia or bipolar disorder and their 7-year-old offspring. Psychiatry Res 2024; 340:116112. [PMID: 39121759 DOI: 10.1016/j.psychres.2024.116112] [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: 01/06/2024] [Revised: 06/15/2024] [Accepted: 07/27/2024] [Indexed: 08/12/2024]
Abstract
Individuals with schizophrenia (SZ) or bipolar disorder (BP) display cognitive impairments, while their first-degree relatives perform at an intermediate level between the patient groups and controls. However, the environmental impact of having an ill relative likely varies with the type of kinship and some studies suggest that offspring may be particularly disadvantaged. The present study aimed to investigate the relationship between parent and child cognition in parents with SZ or BD and their 7-year-old offspring. A population-based cohort of 522 children (parental SZ, n = 202; parental BP, n = 120; controls, n = 200) and their parents underwent the same assessment battery covering a wide range of cognitive functions. We used Bayesian statistics to model performance. We found that performance on non-verbal tests was better in offspring than parents with SZ or BP, using the controls as reference. However, for verbal tests, there was little to no evidence for this pattern or even some evidence for the opposite in the BP group: relatively better performance in parents than offspring. The findings suggest that the offspring of parents with SZ or BP may be particularly disadvantaged in verbal abilities. Future studies will show whether this pattern persists throughout development.
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Affiliation(s)
- Aja Neergaard Greve
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Palle Juul-Jensens Boulevard 175, 8200 Aarhus N, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark.
| | - Nicoline Hemager
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark; Copenhagen Research Center for Mental Health- CORE, Mental Health Center Copenhagen, Copenhagen University Hospital, Mental Health Services Capital Region, Denmark; Child and Adolescent Mental Health Centre, Mental Health Services Capital Region, Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
| | - Erik Lykke Mortensen
- Department of Public Health and Center for Healthy Aging, University of Copenhagen, Denmark
| | - Ditte Lou Gantriis
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Palle Juul-Jensens Boulevard 175, 8200 Aarhus N, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark
| | - Birgitte Klee Burton
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark; Child and Adolescent Mental Health Centre, Mental Health Services Capital Region, Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
| | - Ditte Ellersgaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark; Copenhagen Research Center for Mental Health- CORE, Mental Health Center Copenhagen, Copenhagen University Hospital, Mental Health Services Capital Region, Denmark
| | - Kerstin J Plessen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark; Child and Adolescent Mental Health Centre, Mental Health Services Capital Region, Research Unit, Copenhagen University Hospital, Copenhagen, Denmark; Division of Child and Adolescent Psychiatry, Department of Psychiatry, University Hospital Lausanne, Switzerland
| | - Anne A E Thorup
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark; Child and Adolescent Mental Health Centre, Mental Health Services Capital Region, Research Unit, Copenhagen University Hospital, Copenhagen, Denmark; University of Copenhagen, Institute for Clinical Medicine, Faculty of Health, Denmark
| | - Jens Richardt Møllegaard Jepsen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark; Copenhagen Research Center for Mental Health- CORE, Mental Health Center Copenhagen, Copenhagen University Hospital, Mental Health Services Capital Region, Denmark; Child and Adolescent Mental Health Centre, Mental Health Services Capital Region, Research Unit, Copenhagen University Hospital, Copenhagen, Denmark; Centre for Neuropsychiatric Schizophrenia Research & Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Copenhagen University Hospital, Psychiatric Hospital Centre Glostrup, Denmark
| | - Merete Nordentoft
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark; Copenhagen Research Center for Mental Health- CORE, Mental Health Center Copenhagen, Copenhagen University Hospital, Mental Health Services Capital Region, Denmark; University of Copenhagen, Institute for Clinical Medicine, Faculty of Health, Denmark
| | - Ole Mors
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Palle Juul-Jensens Boulevard 175, 8200 Aarhus N, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark
| | - Arndis Simonsen
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Palle Juul-Jensens Boulevard 175, 8200 Aarhus N, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark
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Yao B, Rolfs M, Slate R, Roberts D, Fattal J, Achtyes ED, Tso IF, Diwadkar VA, Kashy D, Bao J, Thakkar KN. Abnormal Oculomotor Corollary Discharge Signaling as a Trans-diagnostic Mechanism of Psychosis. Schizophr Bull 2024; 50:631-641. [PMID: 38245499 PMCID: PMC11059795 DOI: 10.1093/schbul/sbad180] [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] [Indexed: 01/22/2024]
Abstract
BACKGROUND AND HYPOTHESIS Corollary discharge (CD) signals are "copies" of motor signals sent to sensory areas to predict the corresponding input. They are a posited mechanism enabling one to distinguish actions generated by oneself vs external forces. Consequently, altered CD is a hypothesized mechanism for agency disturbances in psychosis. Previous studies have shown a decreased influence of CD signals on visual perception in individuals with schizophrenia-particularly in those with more severe positive symptoms. We therefore hypothesized that altered CD may be a trans-diagnostic mechanism of psychosis. STUDY DESIGN We examined oculomotor CD (using the blanking task) in 49 participants with schizophrenia or schizoaffective disorder (SZ), 36 bipolar participants with psychosis (BPP), and 40 healthy controls (HC). Participants made a saccade to a visual target. Upon saccade initiation, the target disappeared and reappeared at a horizontally displaced position. Participants indicated the direction of displacement. With intact CD, participants can make accurate perceptual judgements. Otherwise, participants may use saccade landing site as a proxy of pre-saccadic target to inform perception. Thus, multi-level modeling was used to examine the influence of target displacement and saccade landing site on displacement judgements. STUDY RESULTS SZ and BPP were equally less sensitive to target displacement than HC. Moreover, regardless of diagnosis, SZ and BPP with more severe positive symptoms were more likely to rely on saccade landing site. CONCLUSIONS These results suggest that altered CD may be a trans-diagnostic mechanism of psychosis.
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Affiliation(s)
- Beier Yao
- Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Martin Rolfs
- Department of Psychology, Humboldt University, Berlin, Germany
| | - Rachael Slate
- Department of Psychology, Brigham Young University, Provo, UT, USA
| | - Dominic Roberts
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Jessica Fattal
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Eric D Achtyes
- Cherry Health, Grand Rapids, MI, USA
- Department of Psychiatry, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA
| | - Ivy F Tso
- Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH, USA
| | - Vaibhav A Diwadkar
- Department of Psychiatry and Behavioral Neuroscience, Wayne State University, Detroit, MI, USA
| | - Deborah Kashy
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Jacqueline Bao
- Department of Psychology, Michigan State University, East Lansing, MI, USA
- Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
| | - Katharine N Thakkar
- Department of Psychology, Michigan State University, East Lansing, MI, USA
- Department of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA
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Andreassen AK, Lambek R, Greve A, Hemager N, Knudsen CB, Veddum L, Birk M, Søndergaard A, Brandt JM, Gregersen M, Falkenberg-Krantz M, Spang KS, Ohland J, Burton BK, Jepsen JRM, Thorup AAE, Nordentoft M, Mors O, Bliksted VF. The development in rating-based executive functions in children at familial high risk of schizophrenia or bipolar disorder from age 7 to age 11: the Danish high risk and resilience study. Eur Child Adolesc Psychiatry 2024; 33:549-560. [PMID: 36881155 DOI: 10.1007/s00787-023-02177-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 02/23/2023] [Indexed: 03/08/2023]
Abstract
Executive functions (EF) deficits are well documented in children at familial high risk of schizophrenia (FHR-SZ), and to a lesser degree in children at familial high risk of bipolar disorder (FHR-BP). The aim of this study was to assess EF development in preadolescent children at FHR-SZ, FHR-BP and population-based controls (PBC) using a multi-informant rating scale. A total of 519 children (FHR-SZ, n = 201; FHR-BP, n = 119; PBC, n = 199) participated at age 7, at age 11 or at both time points. Caregivers and teachers completed the Behavior Rating Inventory of Executive Functions (BRIEF). The developmental pattern from age 7 to age 11, did not differ between groups. At age 11, caregivers and teachers rated children at FHR-SZ as having widespread EF deficits. A higher proportion of children at FHR-SZ had clinically significant scores on the General executive composite (GEC) and all BRIEF indices compared to PBC. According to the caregivers, children at FHR-BP had significantly more EF deficits than PBC on 9 out of 13 BRIEF scales, whereas according to teachers, they only had significantly more deficits on one subdomain (Initiate). Likewise, caregivers rated a significantly higher proportion of children at FHR-BP above the clinical cut-off on the GEC and Metacognition index, compared to PBC, whereas there were no significant differences according to teachers. This study highlights the relevance of including multi-informant rating scales in the assessment of EF in children at FHR-SZ and FHR-BP. The results imply a need to identify children at high risk who would benefit from targeted intervention.
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Affiliation(s)
- Anna Krogh Andreassen
- Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark.
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark.
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
| | - Rikke Lambek
- Department of Psychology and Behavioral Sciences, Aarhus University, Aarhus, Denmark
| | - Aja Greve
- Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
| | - Nicoline Hemager
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Child and Adolescent Mental Health Center, Capital Region of Denmark, Copenhagen, Denmark
| | - Christina Bruun Knudsen
- Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Lotte Veddum
- Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Merete Birk
- Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
| | - Anne Søndergaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Julie Marie Brandt
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maja Gregersen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mette Falkenberg-Krantz
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Child and Adolescent Mental Health Center, Capital Region of Denmark, Copenhagen, Denmark
| | - Katrine Søborg Spang
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Child and Adolescent Mental Health Center, Capital Region of Denmark, Copenhagen, Denmark
| | - Jessica Ohland
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
| | - Birgitte Klee Burton
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Child and Adolescent Mental Health Center, Capital Region of Denmark, Copenhagen, Denmark
| | - Jens Richardt Møllegaard Jepsen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Child and Adolescent Mental Health Center, Capital Region of Denmark, Copenhagen, Denmark
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Services in the Capital Region of Denmark, Copenhagen, Denmark
| | - Anne Amalie Elgaard Thorup
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Child and Adolescent Mental Health Center, Capital Region of Denmark, Copenhagen, Denmark
| | - Merete Nordentoft
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region of Denmark, Mental Health Centre Copenhagen, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole Mors
- Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
| | - Vibeke Fuglsang Bliksted
- Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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5
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Haatveit B, Westlye LT, Vaskinn A, Flaaten CB, Mohn C, Bjella T, Sæther LS, Sundet K, Melle I, Andreassen OA, Alnæs D, Ueland T. Intra- and inter-individual cognitive variability in schizophrenia and bipolar spectrum disorder: an investigation across multiple cognitive domains. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:89. [PMID: 38110366 PMCID: PMC10728206 DOI: 10.1038/s41537-023-00414-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 11/17/2023] [Indexed: 12/20/2023]
Abstract
There is substantial cognitive heterogeneity among patients with schizophrenia (SZ) and bipolar disorders (BD). More knowledge about the magnitude and clinical correlates of performance variability could improve our understanding of cognitive impairments. Using double generalized linear models (DGLMs) we investigated cognitive mean and variability differences between patients with SZ (n = 905) and BD spectrum disorders (n = 522), and healthy controls (HC, n = 1170) on twenty-two variables. The analysis revealed significant case-control differences on 90% of the variables. Compared to HC, patients showed larger intra-individual (within subject) variability across tests and larger inter-individual (between subject) variability in measures of fine-motor speed, mental processing speed, and inhibitory control (SZ and BD), and in verbal learning and memory and intellectual functioning (SZ). In SZ, we found that lager intra -and inter (on inhibitory control and speed functions) individual variability, was associated with lower functioning and more negative symptoms. Inter-individual variability on single measures of memory and intellectual function was additionally associated with disorganized and positive symptoms, and use of antidepressants. In BD, there were no within-subject associations with symptom severity. However, greater inter-individual variability (primarily on inhibitory control and speeded functions) was associated with lower functioning, more negative -and disorganized symptoms, earlier age at onset, longer duration of illness, and increased medication use. These results highlight larger individual differences in patients compared to controls on various cognitive domains. Further investigations of the causes and correlates of individual differences in cognitive function are warranted.
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Affiliation(s)
- Beathe Haatveit
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Anja Vaskinn
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Research and Education in Forensic Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Camilla Bärthel Flaaten
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Christine Mohn
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Thomas Bjella
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Linn Sofie Sæther
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kjetil Sundet
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Torill Ueland
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
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6
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Mishra VC, Solanki G, Singh D, Goyal MK. Prevalence and clinical correlates of co-morbid attention deficit hyperactivity disorder in euthymic adults with bipolar disorder: A cross-sectional study. Indian J Psychiatry 2023; 65:1129-1136. [PMID: 38249150 PMCID: PMC10795658 DOI: 10.4103/indianjpsychiatry.indianjpsychiatry_647_23] [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: 08/24/2023] [Revised: 10/30/2023] [Accepted: 11/07/2023] [Indexed: 01/23/2024] Open
Abstract
Background Bipolar disorders (BDs) are co-morbid with attention deficit hyperactivity disorder (ADHD), making diagnosis and management more difficult and associated with poorer outcomes. So, this study was planned to find the prevalence and clinical implication of co-morbid ADHD in BD. Materials and Methods In this cross-sectional study, a total of 110 euthymic BD patients were taken. They were screened for childhood ADHD symptoms and adult ADHD symptoms using the Wender Utah Rating Scale for ADHD and Adult ADHD Self-Report Screening Scale for DSM-5. Those were divided into three groups: Group A included BD patients without ADHD, Group B included bipolar patients with co-morbid adult ADHD (BD-aADHD), and Group C included bipolar patients who had a diagnosis of childhood ADHD (BD-cADHD). Results The ADHD prevalence of 27% was found in bipolar patients. The age of onset of an episode of BD was significantly earlier and the total duration of illness was significantly higher in BD-aADHD and BD-cADHD compared to the BD without ADHD. The BD-aADHD and BD-cADHD groups showed a significantly higher number of total, manic and major depressive episodes as compared to the BD without ADHD group. BD-aADHD showed a significant greater number of hypomanic episodes as compared to BD without ADHD. Conclusions The present study concludes that ADHD is a lifetime co-morbid condition in adults with BD. These patients have a more chronic and disabling course of BD which underscores the need to understand the potential benefit of controlling ADHD symptoms in this population.
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Affiliation(s)
- Vikash C. Mishra
- Department of Psychiatry, Katihar Medical College, Katihar, Bihar, India
| | - Gunjan Solanki
- Department of Psychiatry, SMS Medical College, Jaipur, Rajasthan, India
| | - Dharmdeep Singh
- Department of Psychiatry, SMS Medical College, Jaipur, Rajasthan, India
| | - Manish K. Goyal
- Department of Psychiatry, SMS Medical College, Jaipur, Rajasthan, India
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7
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Kesler SR, Henneghan AM, Prinsloo S, Palesh O, Wintermark M. Neuroimaging based biotypes for precision diagnosis and prognosis in cancer-related cognitive impairment. Front Med (Lausanne) 2023; 10:1199605. [PMID: 37720513 PMCID: PMC10499624 DOI: 10.3389/fmed.2023.1199605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 08/15/2023] [Indexed: 09/19/2023] Open
Abstract
Cancer related cognitive impairment (CRCI) is commonly associated with cancer and its treatments, yet the present binary diagnostic approach fails to capture the full spectrum of this syndrome. Cognitive function is highly complex and exists on a continuum that is poorly characterized by dichotomous categories. Advanced statistical methodologies applied to symptom assessments have demonstrated that there are multiple subclasses of CRCI. However, studies suggest that relying on symptom assessments alone may fail to account for significant differences in the neural mechanisms that underlie a specific cognitive phenotype. Treatment plans that address the specific physiologic mechanisms involved in an individual patient's condition is the heart of precision medicine. In this narrative review, we discuss how biotyping, a precision medicine framework being utilized in other mental disorders, could be applied to CRCI. Specifically, we discuss how neuroimaging can be used to determine biotypes of CRCI, which allow for increased precision in prediction and diagnosis of CRCI via biologic mechanistic data. Biotypes may also provide more precise clinical endpoints for intervention trials. Biotyping could be made more feasible with proxy imaging technologies or liquid biomarkers. Large cross-sectional phenotyping studies are needed in addition to evaluation of longitudinal trajectories, and data sharing/pooling is highly feasible with currently available digital infrastructures.
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Affiliation(s)
- Shelli R. Kesler
- Division of Adult Health, School of Nursing, The University of Texas at Austin, Austin, TX, United States
- Department of Diagnostic Medicine, Dell School of Medicine, The University of Texas at Austin, Austin, TX, United States
- Department of Oncology, Dell School of Medicine, The University of Texas at Austin, Austin, TX, United States
| | - Ashley M. Henneghan
- Division of Adult Health, School of Nursing, The University of Texas at Austin, Austin, TX, United States
- Department of Oncology, Dell School of Medicine, The University of Texas at Austin, Austin, TX, United States
| | - Sarah Prinsloo
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Oxana Palesh
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
| | - Max Wintermark
- Department of Neuroradiology, The University of Texas MD Anderson Cancer, Houston, TX, United States
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8
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Misiak B, Samochowiec J, Kowalski K, Gaebel W, Bassetti CLA, Chan A, Gorwood P, Papiol S, Dom G, Volpe U, Szulc A, Kurimay T, Kärkkäinen H, Decraene A, Wisse J, Fiorillo A, Falkai P. The future of diagnosis in clinical neurosciences: Comparing multiple sclerosis and schizophrenia. Eur Psychiatry 2023; 66:e58. [PMID: 37476977 PMCID: PMC10486256 DOI: 10.1192/j.eurpsy.2023.2432] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/12/2023] [Accepted: 06/14/2023] [Indexed: 07/22/2023] Open
Abstract
The ongoing developments of psychiatric classification systems have largely improved reliability of diagnosis, including that of schizophrenia. However, with an unknown pathophysiology and lacking biomarkers, its validity still remains low, requiring further advancements. Research has helped establish multiple sclerosis (MS) as the central nervous system (CNS) disorder with an established pathophysiology, defined biomarkers and therefore good validity and significantly improved treatment options. Before proposing next steps in research that aim to improve the diagnostic process of schizophrenia, it is imperative to recognize its clinical heterogeneity. Indeed, individuals with schizophrenia show high interindividual variability in terms of symptomatic manifestation, response to treatment, course of illness and functional outcomes. There is also a multiplicity of risk factors that contribute to the development of schizophrenia. Moreover, accumulating evidence indicates that several dimensions of psychopathology and risk factors cross current diagnostic categorizations. Schizophrenia shares a number of similarities with MS, which is a demyelinating disease of the CNS. These similarities appear in the context of age of onset, geographical distribution, involvement of immune-inflammatory processes, neurocognitive impairment and various trajectories of illness course. This article provides a critical appraisal of diagnostic process in schizophrenia, taking into consideration advancements that have been made in the diagnosis and management of MS. Based on the comparison between the two disorders, key directions for studies that aim to improve diagnostic process in schizophrenia are formulated. All of them converge on the necessity to deconstruct the psychosis spectrum and adopt dimensional approaches with deep phenotyping to refine current diagnostic boundaries.
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Affiliation(s)
- Błażej Misiak
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
| | - Jerzy Samochowiec
- Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland
| | | | - Wolfgang Gaebel
- Department of Psychiatry and Psychotherapy, LVR-Klinikum Düsseldorf, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
- WHO Collaborating Centre on Quality Assurance and Empowerment in Mental Health, DEU-131, Düsseldorf, Germany
| | - Claudio L. A. Bassetti
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Switzerland
- Interdisciplinary Sleep-Wake-Epilepsy-Center, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Andrew Chan
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Switzerland
| | - Philip Gorwood
- Université Paris Cité, INSERM, U1266 (Institute of Psychiatry and Neuroscience of Paris), Paris, France
- CMME, GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte-Anne, Paris, France
| | - Sergi Papiol
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University, Munich, Germany
| | - Geert Dom
- Collaborative Antwerp Psychiatric Research Institute, University of Antwerp, B-2610Antwerp, Belgium
- Multiversum Psychiatric Hospital, B-2530Boechout, Belgium
| | - Umberto Volpe
- Unit of Clinical Psychiatry, Department of Clinical Neurosciences/DIMSC, Polytechnic University of Marche, 60126Ancona, Italy
| | - Agata Szulc
- Department of Psychiatry, Medical University of Warsaw, Warsaw, Poland
| | - Tamas Kurimay
- Department of Psychiatry, St. Janos Hospital, Budapest, Hungary
| | | | - Andre Decraene
- European Federation of Associations of Families of People with Mental Illness (EUFAMI), Leuven, Belgium
| | - Jan Wisse
- Century House, Wargrave Road, Henley-on-Thames, OxfordshireRG9 2LT, UK
| | - Andrea Fiorillo
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336Munich, Germany
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9
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Seitz-Holland J, Nägele FL, Kubicki M, Pasternak O, Cho KIK, Hough M, Mulert C, Shenton ME, Crow TJ, James ACD, Lyall AE. Shared and distinct white matter abnormalities in adolescent-onset schizophrenia and adolescent-onset psychotic bipolar disorder. Psychol Med 2023; 53:4707-4719. [PMID: 35796024 PMCID: PMC11119277 DOI: 10.1017/s003329172200160x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND While adolescent-onset schizophrenia (ADO-SCZ) and adolescent-onset bipolar disorder with psychosis (psychotic ADO-BPD) present a more severe clinical course than their adult forms, their pathophysiology is poorly understood. Here, we study potentially state- and trait-related white matter diffusion-weighted magnetic resonance imaging (dMRI) abnormalities along the adolescent-onset psychosis continuum to address this need. METHODS Forty-eight individuals with ADO-SCZ (20 female/28 male), 15 individuals with psychotic ADO-BPD (7 female/8 male), and 35 healthy controls (HCs, 18 female/17 male) underwent dMRI and clinical assessments. Maps of extracellular free-water (FW) and fractional anisotropy of cellular tissue (FAT) were compared between individuals with psychosis and HCs using tract-based spatial statistics and FSL's Randomise. FAT and FW values were extracted, averaged across all voxels that demonstrated group differences, and then utilized to test for the influence of age, medication, age of onset, duration of illness, symptom severity, and intelligence. RESULTS Individuals with adolescent-onset psychosis exhibited pronounced FW and FAT abnormalities compared to HCs. FAT reductions were spatially more widespread in ADO-SCZ. FW increases, however, were only present in psychotic ADO-BPD. In HCs, but not in individuals with adolescent-onset psychosis, FAT was positively related to age. CONCLUSIONS We observe evidence for cellular (FAT) and extracellular (FW) white matter abnormalities in adolescent-onset psychosis. Although cellular white matter abnormalities were more prominent in ADO-SCZ, such alterations may reflect a shared trait, i.e. neurodevelopmental pathology, present across the psychosis spectrum. Extracellular abnormalities were evident in psychotic ADO-BPD, potentially indicating a more dynamic, state-dependent brain reaction to psychosis.
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Affiliation(s)
- Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Felix L. Nägele
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kang Ik K. Cho
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Morgan Hough
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
- Highfield Unit, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Christoph Mulert
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
- Centre for Psychiatry and Psychotherapy, Justus-Liebig-University, Giessen, Germany
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Timothy J. Crow
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Anthony C. D. James
- SANE POWIC, University Department of Psychiatry, Warneford Hospital, Oxford, UK
- Highfield Unit, University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - Amanda E. Lyall
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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10
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Rokham H, Falakshahi H, Fu Z, Pearlson G, Calhoun VD. Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (dFNC) via deep learning classification. Hum Brain Mapp 2023; 44:3180-3195. [PMID: 36919656 PMCID: PMC10171526 DOI: 10.1002/hbm.26273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 02/20/2023] [Accepted: 02/27/2023] [Indexed: 03/16/2023] Open
Abstract
The validity and reliability of diagnoses in psychiatry is a challenging topic in mental health. The current mental health categorization is based primarily on symptoms and clinical course and is not biologically validated. Among multiple ongoing efforts, neurological observations alongside clinical evaluations are considered to be potential solutions to address diagnostic problems. The Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) has published multiple papers attempting to reclassify psychotic illnesses based on biological rather than symptomatic measures. However, the effort to investigate the relationship between this new categorization approach and other neuroimaging techniques, including resting-state fMRI data, is still limited. This study focused on investigating the relationship between different psychotic disorders categorization methods and resting-state fMRI-based measures called dynamic functional network connectivity (dFNC) using state-of-the-art artificial intelligence (AI) approaches. We applied our method to 613 subjects, including individuals with psychosis and healthy controls, which were classified using both the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and the B-SNIP biomarker-based (Biotype) approach. Statistical group differences and cross-validated classifiers were performed within each framework to assess how different categories. Results highlight interesting differences in occupancy in both DSM-IV and Biotype categorizations compared to healthy individuals, which are distributed across specific transient connectivity states. Biotypes tended to show less distinctiveness in occupancy level and included fewer cellwise differences. Classification accuracy obtained by DSM-IV and Biotype categories were both well above chance. Results provided new insights and highlighted the benefits of both DSM-IV and biology-based categories while also emphasizing the importance of future work in this direction, including employing further data types.
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Affiliation(s)
- Hooman Rokham
- Department of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
| | - Haleh Falakshahi
- Department of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
| | - Zening Fu
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
| | - Godfrey Pearlson
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
- Department of NeuroscienceYale UniversityNew HavenConnecticutUSA
- Olin Neuropsychiatry Research CenterHartford HospitalHartfordConnecticutUSA
| | - Vince D. Calhoun
- Department of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
- Department of Computer ScienceGeorgia State UniversityAtlantaGeorgiaUSA
- Department of PsychologyGeorgia State UniversityAtlantaGeorgiaUSA
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11
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Smith LM, Yolland C, Rossell SL, Toh WL. The phenomenology of auditory verbal hallucinations in bipolar disorder. Psychol Psychother 2023; 96:399-409. [PMID: 36748805 PMCID: PMC10952547 DOI: 10.1111/papt.12446] [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: 10/21/2022] [Accepted: 12/29/2022] [Indexed: 02/08/2023]
Abstract
OBJECTIVES At least one in four persons with bipolar disorder (BD) are estimated to have experienced auditory verbal hallucinations (AVH) or heard voices at some point. Yet few studies have investigated AVH in detail in this population. This preliminary study examined the phenomenology of AVH in BD to identify commonalities and differences relative to other psychiatric disorders where AVH are commonly reported. METHOD Twenty-one participants diagnosed with BD were recruited across two international sites in the UK and Australia. All participants underwent a structured clinical interview to verify psychiatric diagnosis and completed standardised measures of symptomatology, including mood states. Phenomenological information of AVH was gathered using select questions from the comprehensive Mental Health Research Institute Unusual Perceptual Schedule (MUPS). RESULTS AVH experienced by this BD sample were broadly similar in form and content to characterisations reported in the schizophrenia spectrum disorders (SSD) in prior literature, with some exceptions including frequency, duration and the changeability of tone and content. CONCLUSIONS The study highlights possibly subtle differences in the experience of AVH in BD, including the potential influence of mood congruence as a pertinent clinical feature. Further research into these differences might inform adaptations to existing AVH interventions to ensure they are relevant for BD.
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Affiliation(s)
- Lindsay M Smith
- National and Specialist CAMHS, At‐Risk and Forensic Service, South London and Maudsley NHS Foundation Trust, Michael Rutter CentreMaudsley HospitalLondonUK
- Department of Psychology, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
| | - Caitlin Yolland
- Centre for Mental HealthSwinburne University of TechnologyMelbourneVictoriaAustralia
| | - Susan L. Rossell
- Centre for Mental HealthSwinburne University of TechnologyMelbourneVictoriaAustralia
- Department of PsychiatrySt Vincent's HospitalMelbourneVictoriaAustralia
| | - Wei Lin Toh
- Centre for Mental HealthSwinburne University of TechnologyMelbourneVictoriaAustralia
- Department of PsychiatrySt Vincent's HospitalMelbourneVictoriaAustralia
- Department of PsychologyAlfred HospitalMelbourneVictoriaAustralia
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12
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Pinto D, Martins R, Macedo A, Castelo Branco M, Valente Duarte J, Madeira N. Brain Hemispheric Asymmetry in Schizophrenia and Bipolar Disorder. J Clin Med 2023; 12:jcm12103421. [PMID: 37240527 DOI: 10.3390/jcm12103421] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/01/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND This study aimed to compare brain asymmetry in patients with schizophrenia (SCZ), bipolar disorder (BPD), and healthy controls to test whether asymmetry patterns could discriminate and set boundaries between two partially overlapping severe mental disorders. METHODS We applied a fully automated voxel-based morphometry (VBM) approach to assess structural brain hemispheric asymmetry in magnetic resonance imaging (MRI) anatomical scans in 60 participants (SCZ = 20; BP = 20; healthy controls = 20), all right-handed and matched for gender, age, and education. RESULTS Significant differences in gray matter asymmetry were found between patients with SCZ and BPD, between SCZ patients and healthy controls (HC), and between BPD patients and HC. We found a higher asymmetry index (AI) in BPD patients when compared to SCZ in Brodmann areas 6, 11, and 37 and anterior cingulate cortex and an AI higher in SCZ patients when compared to BPD in the cerebellum. CONCLUSION Our study found significant differences in brain asymmetry between patients with SCZ and BPD. These promising results could be translated to clinical practice, given that structural brain changes detected by MRI are good candidates for exploration as biological markers for differential diagnosis, besides helping to understand disease-specific abnormalities.
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Affiliation(s)
- Diogo Pinto
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
| | - Ricardo Martins
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
| | - António Macedo
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
- Department of Psychiatry, Centro Hospitalar e Universitário de Coimbra (CHUC), 3000-075 Coimbra, Portugal
| | - Miguel Castelo Branco
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
| | - João Valente Duarte
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
| | - Nuno Madeira
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
- Department of Psychiatry, Centro Hospitalar e Universitário de Coimbra (CHUC), 3000-075 Coimbra, Portugal
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13
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Shamanna V, Mehta UM, Naik SS, Basavaraju R, Thirthalli J. Transdiagnostic investigation into the relationship between mirror neuron system activity, echo-phenomena, and theory of mind in major psychoses. Asian J Psychiatr 2023; 82:103504. [PMID: 36801552 DOI: 10.1016/j.ajp.2023.103504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 02/02/2023] [Accepted: 02/04/2023] [Indexed: 02/11/2023]
Abstract
The association between social cognition and putative mirror neuron system (MNS)-activity in major psychoses might be contingent upon frontal dysregulation. We used a transdiagnostic ecological approach to enrich a specific behavioral phenotype (echophenomena or hyper-imitative states) across clinical diagnoses (mania and schizophrenia) to compare behavioral and physiological markers of social cognition and frontal disinhibition. We examined 114 participants with schizophrenia (N = 53) and mania (N = 61) for the presence and severity of echo-phenomena (echopraxia, incidental, and induced echolalia) using an ecological paradigm to simulate real-life social communication. Symptom severity, frontal release reflexes, and theory of mind performance were also assessed. In a proportion of these participants with (N = 20) and without (N = 20) echo-phenomena, we compared motor resonance (motor evoked potential facilitation during action observation compared to static image viewing) and cortical silent period (CSP) as putative markers of MNS-activity and frontal disinhibition, respectively, using Transcranial Magnetic Stimulation. While the prevalence of echo-phenomena was similar between mania and schizophrenia, incidental echolalia was more severe in mania. Participants with echo-phenomena (compared to those without) had significantly greater motor resonance with singlepulse (not with paired-pulse) stimuli, poorer theory of mind scores, higher frontal release reflexes but similar CSP, and greater symptom severity. None of these parameters significantly differed between participants with mania and schizophrenia. We observed relatively better phenotypic and neurophysiological characterization of major psychoses by categorizing participants based on the presence of echophenomena than clinical diagnoses. Higher putative MNS-activity was associated with poorer theory of mind in a hyper-imitative behavioral state.
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Affiliation(s)
- Varsha Shamanna
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru 560029, India
| | - Urvakhsh Meherwan Mehta
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru 560029, India.
| | - Shalini S Naik
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru 560029, India
| | - Rakshathi Basavaraju
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru 560029, India
| | - Jagadisha Thirthalli
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru 560029, India
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14
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Levit JD, Meyers JL, Georgakopoulos P, Pato MT. Risk for alcohol use problems in severe mental illness: Interactions with sex and racial/ethnic minority status. J Affect Disord 2023; 325:329-336. [PMID: 36587907 PMCID: PMC9942932 DOI: 10.1016/j.jad.2022.12.140] [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: 05/16/2022] [Revised: 12/22/2022] [Accepted: 12/25/2022] [Indexed: 01/01/2023]
Abstract
BACKGROUND Alcohol use disorder (AUD) is exceedingly common among individuals with bipolar disorder and schizophrenia. However, studies on alcohol use in psychiatric illness rely largely on population surveys with limited representation of severe mental illness (SMI); schizophrenia and bipolar disorder. METHODS Using data from the Genomic Psychiatry Cohort (GPC) (Pato MT, 2013), associations of bipolar disorder and schizophrenia with alcohol use problems were examined in a diverse US based sample, considering the influence of self-described race (African Ancestry (AA), European Ancestry (EA), or Latinx Ancestry (LA)), sex, and tobacco use. Participants answered alcohol use problem items derived from the CAGE instrument, yielding a summed "probable" alcohol use disorder (pAUD) risk score. RESULTS This study included 1952 individuals with bipolar disorder with psychosis (BDwP), 409 with bipolar disorder without psychosis (BD), 9218 with schizophrenia (SCZ), and 10,416 unaffected individuals. We found that SMI (BDwP, BD, SCZ) was associated with elevated AUD risk scores (B = 0.223, p < 0.001), an association which was strongest in females, particularly those of AA and LA, and in tobacco users. Schizophrenia was associated with the greatest increase in pAUD score (B = 0.141, p < 0.001). pAUD risk scores were increased among participants with bipolar disorder, with greater increases in BDwP (B = 0.125, p < 0.001) than in BD without psychosis (B = 0.027, p < 0.001). LIMITATIONS Limitations include reliance on self-report data, screening items for AUD, voluntary recruitment bias, and differences in race/sex distribution between groups, which were statistically adjusted for in analytic models. CONCLUSIONS SMI is associated with risk for AUD, particularly among females from racial minority groups, smokers, and those with psychotic disorders.
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Affiliation(s)
- Jeremy D Levit
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Jacquelyn L Meyers
- Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | | | - Michele T Pato
- Department of Psychiatry, Rutgers University, Piscataway, NJ, USA.
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15
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Associations of neurodevelopmental risk factors with psychosis proneness: Findings from a non-clinical sample of young adults. Compr Psychiatry 2023; 123:152385. [PMID: 36931184 DOI: 10.1016/j.comppsych.2023.152385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 03/02/2023] [Accepted: 03/09/2023] [Indexed: 03/19/2023] Open
Abstract
Psychotic disorders often develop as the continuum of subclinical symptoms that include hallucination-like and delusion-like experiences, and are commonly referred to as psychotic-like experiences (PLEs). To date, a number of neurodevelopmental risk factors of psychosis have been detected, yet their mutual interplay remains unknown. Therefore, we aimed to investigate the additive association of childhood trauma history, reading disabilities and symptoms of attention-deficit/hyperactivity disorder (ADHD) with psychosis proneness. A total of 3000 young adults (58.3% females, aged 18-35 years) with a negative history of psychiatric treatment were recruited to the cross-sectional study through computer-assisted web interview. Self-reports were administered to measure childhood trauma history, ADHD symptoms and reading disabilities. Linear regression analyses revealed significant main associations of childhood trauma history and reading disabilities with higher levels of PLEs. There were no significant main associations of ADHD with the level of PLEs. However, the associations of all possible interactions between neurodevelopmental risk factors with the level of PLEs were significant. Our findings suggest that childhood trauma history and reading disabilities may additively increase a risk of psychosis. The present findings bring new implications for early intervention strategies in psychosis and posit the rationale of recording the accumulation of neurodevelopmental vulnerabilities in clinical practice.
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16
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Keane BP, Krekelberg B, Mill RD, Silverstein SM, Thompson JL, Serody MR, Barch DM, Cole MW. Dorsal attention network activity during perceptual organization is distinct in schizophrenia and predictive of cognitive disorganization. Eur J Neurosci 2023; 57:458-478. [PMID: 36504464 DOI: 10.1111/ejn.15889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 12/02/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022]
Abstract
Visual shape completion is a canonical perceptual organization process that integrates spatially distributed edge information into unified representations of objects. People with schizophrenia show difficulty in discriminating completed shapes, but the brain networks and functional connections underlying this perceptual difference remain poorly understood. Also unclear is whether brain network differences in schizophrenia occur in related illnesses or vary with illness features transdiagnostically. To address these topics, we scanned (functional magnetic resonance imaging, fMRI) people with schizophrenia, bipolar disorder, or no psychiatric illness during rest and during a task in which they discriminated configurations that formed or failed to form completed shapes (illusory and fragmented condition, respectively). Multivariate pattern differences were identified on the cortical surface using 360 predefined parcels and 12 functional networks composed of such parcels. Brain activity flow mapping was used to evaluate the likely involvement of resting-state connections for shape completion. Illusory/fragmented task activation differences ('modulations') in the dorsal attention network (DAN) could distinguish people with schizophrenia from the other groups (AUCs > .85) and could transdiagnostically predict cognitive disorganization severity. Activity flow over functional connections from the DAN could predict secondary visual network modulations in each group, except in schizophrenia. The secondary visual network was strongly and similarly modulated in each group. Task modulations were dispersed over more networks in patients compared to controls. In summary, DAN activity during visual perceptual organization is distinct in schizophrenia, symptomatically relevant, and potentially related to improper attention-related feedback into secondary visual areas.
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Affiliation(s)
- Brian P Keane
- University Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
| | - Bart Krekelberg
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey, USA
| | - Ravi D Mill
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey, USA
| | - Steven M Silverstein
- University Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, New York, USA
| | - Judy L Thompson
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
- Department of Psychiatric Rehabilitation and Counseling Professions, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Megan R Serody
- University Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
| | - Deanna M Barch
- Departments of Psychological & Brain Sciences, Psychiatry, and Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Michael W Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey, USA
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David FS, Stein F, Andlauer TFM, Streit F, Witt SH, Herms S, Hoffmann P, Heilmann-Heimbach S, Opel N, Repple J, Jansen A, Nenadić I, Papiol S, Heilbronner U, Kalman JL, Schaupp SK, Senner F, Schulte EC, Falkai PG, Schulze TG, Dannlowski U, Kircher T, Rietschel M, Nöthen MM, Krug A, Forstner AJ. Genetic contributions to transdiagnostic symptom dimensions in patients with major depressive disorder, bipolar disorder, and schizophrenia spectrum disorders. Schizophr Res 2023; 252:161-171. [PMID: 36652833 DOI: 10.1016/j.schres.2023.01.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 12/22/2022] [Accepted: 01/02/2023] [Indexed: 01/18/2023]
Abstract
Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorders (SZ) exhibit considerable phenotypic and genetic overlap. However, the contribution of genetic factors to their shared psychopathological symptom dimensions remains unclear. The present exploratory study investigated genetic contributions to the symptom dimensions "Depression", "Negative syndrome", "Positive formal thought disorder", "Paranoid-hallucinatory syndrome", and "Increased appetite" in a transdiagnostic subset of the German FOR2107 cohort (n = 1042 patients with MDD, BD, or SZ). As replication cohort, a subset of the German/Austrian PsyCourse study (n = 816 patients with MDD, BD, or SZ) was employed. First, the relationship between symptom dimensions and common variants associated with MDD, BD, and SZ was investigated via polygenic risk score (PRS) association analyses, with disorder-specific PRS as predictors and symptom dimensions as outcomes. In the FOR2107 study sample, PRS for BD and SZ were positively associated with "Positive formal thought disorder", the PRS for SZ was positively associated with "Paranoid-hallucinatory syndrome", and the PRS for BD was negatively associated with "Depression". The effects of PRS for SZ were replicated in PsyCourse. No significant associations were observed for the MDD PRS. Second, genome-wide association studies (GWAS) were performed for the five symptom dimensions. No genome-wide significant associations and no replicable suggestive associations (p < 1e-6 in the GWAS) were identified. In summary, our results suggest that, similar to diagnostic categories, transdiagnostic psychiatric symptom dimensions are attributable to polygenic contributions with small effect sizes. Further studies in larger thoroughly phenotyped psychiatric cohorts are required to elucidate the genetic factors that shape psychopathological symptom dimensions.
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Affiliation(s)
- Friederike S David
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany; Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany; Center for Innovative Psychiatry and Psychotherapy Research, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Stefan Herms
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany; Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany; Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany; Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Sergi Papiol
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Janos L Kalman
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Sabrina K Schaupp
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Fanny Senner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Eva C Schulte
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Peter G Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany; Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany; Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany; Department of Psychiatry und Psychotherapy, 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.
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18
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Ardesch DJ, Libedinsky I, Scholtens LH, Wei Y, van den Heuvel MP. Convergence of brain transcriptomic and neuroimaging patterns in schizophrenia, bipolar disorder, autism spectrum disorder and major depression disorder. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023. [DOI: 10.1016/j.bpsc.2022.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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19
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Oliveira-Saraiva D, Ferreira HA. Normative model detects abnormal functional connectivity in psychiatric disorders. Front Psychiatry 2023; 14:1068397. [PMID: 36873218 PMCID: PMC9975396 DOI: 10.3389/fpsyt.2023.1068397] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/23/2023] [Indexed: 02/17/2023] Open
Abstract
INTRODUCTION The diagnosis of psychiatric disorders is mostly based on the clinical evaluation of the patient's signs and symptoms. Deep learning binary-based classification models have been developed to improve the diagnosis but have not yet reached clinical practice, in part due to the heterogeneity of such disorders. Here, we propose a normative model based on autoencoders. METHODS We trained our autoencoder on resting-state functional magnetic resonance imaging (rs-fMRI) data from healthy controls. The model was then tested on schizophrenia (SCZ), bipolar disorder (BD), and attention-deficit hyperactivity disorder (ADHD) patients to estimate how each patient deviated from the norm and associate it with abnormal functional brain networks' (FBNs) connectivity. Rs-fMRI data processing was conducted within the FMRIB Software Library (FSL), which included independent component analysis and dual regression. Pearson's correlation coefficients between the extracted blood oxygen level-dependent (BOLD) time series of all FBNs were calculated, and a correlation matrix was generated for each subject. RESULTS AND DISCUSSION We found that the functional connectivity related to the basal ganglia network seems to play an important role in the neuropathology of BD and SCZ, whereas in ADHD, its role is less evident. Moreover, the abnormal connectivity between the basal ganglia network and the language network is more specific to BD. The connectivity between the higher visual network and the right executive control and the connectivity between the anterior salience network and the precuneus networks are the most relevant in SCZ and ADHD, respectively. The results demonstrate that the proposed model could identify functional connectivity patterns that characterize different psychiatric disorders, in agreement with the literature. The abnormal connectivity patterns from the two independent SCZ groups of patients were similar, demonstrating that the presented normative model was also generalizable. However, the group-level differences did not withstand individual-level analysis implying that psychiatric disorders are highly heterogeneous. These findings suggest that a precision-based medical approach, focusing on each patient's specific functional network changes may be more beneficial than the traditional group-based diagnostic classification.
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Affiliation(s)
- Duarte Oliveira-Saraiva
- Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal
| | - Hugo Alexandre Ferreira
- Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal
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20
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Chen Y, Zhou C, Yu H, Wu W, Wang Y, Liu L, Hu G, Li B, Peng Z, Wang H. Gut microbial signatures and differences in bipolar disorder and schizophrenia of emerging adulthood. CNS Neurosci Ther 2022. [DOI: 10.1111/cns.14044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 11/09/2022] [Accepted: 11/16/2022] [Indexed: 12/09/2022] Open
Affiliation(s)
- Yi‐huan Chen
- Department of Psychiatry Xijing Hospital, Air Force Medical University Xi'an China
| | - Cui‐hong Zhou
- Department of Psychiatry Xijing Hospital, Air Force Medical University Xi'an China
| | - Huan Yu
- Department of Psychiatry Xijing Hospital, Air Force Medical University Xi'an China
| | - Wen‐jun Wu
- Department of Psychiatry Xijing Hospital, Air Force Medical University Xi'an China
| | - Ying‐wei Wang
- Department of Ophthalmology Xijing Hospital, Air Force Medical University Xi'an China
| | - Ling Liu
- Institution of Neuroscience Air Force Medical University Xi'an China
| | - Guang‐tao Hu
- Department of Psychiatry Southwest Hospital, Army Medical University Chongqing China
| | - Bao‐juan Li
- School of Biomedical Engineering Air Force Medical University Xi'an China
| | - Zheng‐wu Peng
- Department of Psychiatry Xijing Hospital, Air Force Medical University Xi'an China
| | - Hua‐ning Wang
- Department of Psychiatry Xijing Hospital, Air Force Medical University Xi'an China
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21
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Ramain J, Conus P, Golay P. Grouping affective psychoses in early intervention: Justification for specific treatment guidelines. Psychiatry Res 2022; 314:114690. [PMID: 35753221 DOI: 10.1016/j.psychres.2022.114690] [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: 03/07/2022] [Revised: 06/15/2022] [Accepted: 06/18/2022] [Indexed: 11/26/2022]
Abstract
The concept of affective psychosis regroups psychotic disorders with mood syndrome. Previous studies provided evidence to support a dichotomy between affective and non-affective psychoses although questions remain regarding the utility and validity of such a category to develop clinical guidelines. The aim of this study is to explore similarities and differences within affective psychoses to question whether strategies would apply to all the diagnoses falling under this umbrella term. Using Bayesian model comparison methods, we explored the homogeneity of the characteristics of first-episode affective patients (N = 77) treated in a specialized 3-year early intervention in psychosis programme. Our analysis revealed affective psychoses display many similarities regarding socio-demographic variables, the course of positive and manic symptoms over three years, and outcome at discharge. Our results did not support the heterogeneous model. However, despite no significant differences in the course of symptoms with the major depressive disorder group, the schizoaffective disorder group displayed a more severe clinical picture at the beginning of the programme and a poorer functional outcome than the two other groups. Absence of clear boundaries and the several similarities within affective psychoses suggest they can usefully be grouped to define treatment strategies that are easily legible by clinicians.
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Affiliation(s)
- Julie Ramain
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne), Lausanne University Hospital and University of Lausanne, Place Chauderon 18, Lausanne 1003, Switzerland.
| | - Philippe Conus
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne), Lausanne University Hospital and University of Lausanne, Place Chauderon 18, Lausanne 1003, Switzerland
| | - Philippe Golay
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne), Lausanne University Hospital and University of Lausanne, Place Chauderon 18, Lausanne 1003, Switzerland; Institute of Psychology, Faculty of Social and Political Sciences, University of Lausanne, Place Chauderon 18, Lausanne 1003, Switzerland
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22
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Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series. Schizophr Res 2022; 245:141-150. [PMID: 33676821 PMCID: PMC8413409 DOI: 10.1016/j.schres.2021.02.007] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 02/11/2021] [Accepted: 02/12/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Psychiatric disorders are categorized using self-report and observational information rather than biological data. There is also considerable symptomatic overlap between different types of psychiatric disorders, which makes diagnostic categorization and multi-class classification challenging. METHODS In this work, we propose a unified framework for supervised classification and unsupervised clustering of psychotic disorders using brain imaging data. A new multi-scale recurrent neural network (MsRNN) model was developed and applied to fMRI time courses (TCs) for multi-class classification. The high-level representations of the original TCs were then submitted to a tSNE clustering model for visualizing the group differences between disorders. A leave-one-feature-out approach was used for disorder-related biomarker identification. RESULTS When studying fMRI from schizophrenia, psychotic bipolar disorder, schizoaffective disorder, and healthy individuals, the accuracy of a 4-class classification reached 46%, significantly above chance. The hippocampus, supplementary motor area and paracentral lobule were discovered as the most contributing regional TCs in the multi-class classification. Beyond this, visualization of the tSNE clustering suggested that the disease severity can be captured and schizoaffective disorder (SAD) may be separated into two subtypes. SAD cluster1 has significantly higher Positive And Negative Syndrome Scale (PANSS) scores than SAD cluster2 in PANSS negative2 (emotional withdrawal), general2 (anxiety), general3 (guilt feelings), general4 (tension). CONCLUSIONS The proposed deep classification and clustering framework is not only able to identify psychiatric disorders with high accuracy, but also interpret the correlation between brain networks and specific psychiatric disorders, and reveal the relationship between them. This work provides a promising way to investigate a spectrum of similar disorders using neuroimaging-based measures.
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23
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DeRamus TP, Wu L, Qi S, Iraji A, Silva R, Du Y, Pearlson G, Mayer A, Bustillo JR, Stromberg SF, Calhoun VD. Multimodal data fusion of cortical-subcortical morphology and functional network connectivity in psychotic spectrum disorder. Neuroimage Clin 2022; 35:103056. [PMID: 35709557 PMCID: PMC9207350 DOI: 10.1016/j.nicl.2022.103056] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/18/2022] [Accepted: 05/21/2022] [Indexed: 11/20/2022]
Abstract
Overlap has been noted disorders which fall on the psychotic spectrum. Univariate studies may miss joint brain features across diagnostic categories. mCCA with jICA is paired with features across the psychotic spectrum to produce joint components. One joint component displayed a significant relationship with cognitive scores. The replicate trends of cortical-subcortical irregularity in psychotic spectrum disorders.
Multiple authors have noted overlapping symptoms and alterations across clinical, anatomical, and functional brain features in schizophrenia (SZ), schizoaffective disorder (SZA), and bipolar disorder (BPI). However, regarding brain features, few studies have approached this line of inquiry using analytical techniques optimally designed to extract the shared features across anatomical and functional information in a simultaneous manner. Univariate studies of anatomical or functional alterations across these disorders can be limited and run the risk of omitting small but potentially crucial overlapping or joint neuroanatomical (e.g., structural images) and functional features (e.g., fMRI-based features) which may serve as informative clinical indicators of across multiple diagnostic categories. To address this limitation, we paired an unsupervised multimodal canonical correlation analysis (mCCA) together with joint independent component analysis (jICA) to identify linked spatial gray matter (GM), resting-state functional network connectivity (FNC), and white matter fractional anisotropy (FA) features across these diagnostic categories. We then calculated associations between the identified linked features and trans-diagnostic behavioral measures (MATRICs Consensus Cognitive Battery, MCCB). Component number 4 of the 13 identified displayed a statistically significant relationship with overall MCCB scores across GM, resting-state FNC, and FA. These linked modalities of component 4 consisted primarily of positive correlations within subcortical structures including the caudate and putamen in the GM maps with overall MCCB, sparse negative correlations within subcortical and cortical connection tracts (e.g., corticospinal tract, superior longitudinal fasciculus) in the FA maps with overall MCCB, and negative relationships with MCCB values and loading parameters with FNC matrices displaying increased FNC in subcortical-cortical regions with auditory, somatomotor, and visual regions.
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Affiliation(s)
- T P DeRamus
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA.
| | - L Wu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - S Qi
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - A Iraji
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - R Silva
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Y Du
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA; School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - G Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - A Mayer
- The Mind Research Network, Lovelace Biomedical and Environmental Research Institute, Albuquerque, USA
| | - J R Bustillo
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - S F Stromberg
- Psychiatry and Behavioral Health Clinical Program, Presbyterian Healthcare System, Albuquerque, NM, USA
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA; The Mind Research Network, Lovelace Biomedical and Environmental Research Institute, Albuquerque, USA; Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA; Department of Computer Science, Georgia State University, Atlanta, USA; Department of Psychology, Georgia State University, Atlanta, USA
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24
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Wang B, Zhang S, Yu X, Niu Y, Niu J, Li D, Zhang S, Xiang J, Yan T, Yang J, Wu J, Liu M. Alterations in white matter network dynamics in patients with schizophrenia and bipolar disorder. Hum Brain Mapp 2022; 43:3909-3922. [PMID: 35567336 PMCID: PMC9374889 DOI: 10.1002/hbm.25892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 03/17/2022] [Accepted: 04/08/2022] [Indexed: 11/12/2022] Open
Abstract
Emerging evidence suggests white matter network abnormalities in patients with schizophrenia (SZ) and bipolar disorder (BD), but the alterations in dynamics of the white matter network in patients with SZ and BD are largely unknown. The white matter network of patients with SZ (n = 45) and BD (n = 47) and that of healthy controls (HC, n = 105) were constructed. We used dynamics network control theory to quantify the dynamics metrics of the network, including controllability and synchronizability, to measure the ability to transfer between different states. Experiments show that the patients with SZ and BD showed decreasing modal controllability and synchronizability and increasing average controllability. The correlations between the average controllability and synchronizability of patients were broken, especially for those with SZ. The patients also showed alterations in brain regions with supercontroller roles and their distribution in the cognitive system. Finally, we were able to accurately discriminate and predict patients with SZ and BD. Our findings provide novel dynamic metrics evidence that patients with SZ and BD are characterized by a selective disruption of brain network controllability, potentially leading to reduced brain state transfer capacity, and offer new guidance for the clinical diagnosis of mental illness.
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Affiliation(s)
- Bin Wang
- Department of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Shanshan Zhang
- Department of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Xuexue Yu
- Department of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Yan Niu
- Department of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Jinliang Niu
- Department of Medical Imaging, The Second Hospital of Shanxi Medical University, Taiyuan, China
| | - Dandan Li
- Department of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Shan Zhang
- Department of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Jie Xiang
- Department of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Ting Yan
- Teranslational Medicine Research Center, Shanxi Medical University, Taiyuan, China
| | - Jiajia Yang
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama, Japan
| | - Jinglong Wu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama, Japan
| | - Miaomiao Liu
- School of Psychology, Shenzhen University, Shenzhen, China
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25
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Real-time facial emotion recognition deficits across the psychosis spectrum: A B-SNIP Study. Schizophr Res 2022; 243:489-499. [PMID: 34887147 PMCID: PMC9236198 DOI: 10.1016/j.schres.2021.11.027] [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: 06/22/2021] [Revised: 11/15/2021] [Accepted: 11/17/2021] [Indexed: 11/24/2022]
Abstract
Affective and non-affective psychotic disorders are associated with variable levels of impairment in affective processing, but this domain typically has been examined via presentation of static facial images. We compared performance on a dynamic facial expression identification task across six emotions (sad, fear, surprise, disgust, anger, happy) in individuals with psychotic disorders (bipolar with psychotic features [PBD] = 113, schizoaffective [SAD] = 163, schizophrenia [SZ] = 181) and healthy controls (HC; n = 236) derived from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP). These same individuals with psychotic disorders were also grouped by B-SNIP-derived Biotype (Biotype 1 [B1] = 115, Biotype 2 [B2] = 132, Biotype 3 [B3] = 158), derived from a cluster analysis applied to a large biomarker panel that did not include the current data. Irrespective of the depicted emotion, groups differed in accuracy of emotion identification (P < 0.0001). The SZ group demonstrated lower accuracy versus HC and PBD groups; the SAD group was less accurate than the HC group (Ps < 0.02). Similar overall group differences were evident in speed of identifying emotional expressions. Controlling for general cognitive ability did not eliminate most group differences on accuracy but eliminated almost all group differences on reaction time for emotion identification. Results from the Biotype groups indicated that B1 and B2 had more severe deficits in emotion recognition than HC and B3, meanwhile B3 did not show significant deficits. In sum, this characterization of facial emotion recognition deficits adds to our emerging understanding of social/emotional deficits across the psychosis spectrum.
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Premorbid characteristics of patients with DSM-IV psychotic disorders. Compr Psychiatry 2022; 115:152310. [PMID: 35385814 DOI: 10.1016/j.comppsych.2022.152310] [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: 09/29/2021] [Accepted: 03/09/2022] [Indexed: 11/22/2022] Open
Abstract
INTRODUCTION Psychotic disorder not otherwise specified (PNOS) is considered part of the psychosis spectrum, together with schizophrenia spectrum disorders (SSD) and psychotic bipolar spectrum disorders (PBD). The atypical clinical presentations of PNOS conditions may lead to uncertainty regarding treatment choices and expected outcomes. PNOS is understudied, and little is known about patients' premorbid characteristics including premorbid adjustment, prevalence of early cannabis use and childhood trauma. Knowledge about early illness phases can increase our understanding of this diagnostic group. METHODS We included 1099 participants from the Norwegian TOP-study; 688 with narrow SSD diagnoses (schizophrenia, schizoaffective disorder, schizophreniform disorder), 274 with PBD (psychotic bipolar 1 and bipolar NOS) and 137 with PNOS diagnosed with the SCID-I for DSM-IV. Participants were assessed with the Premorbid Adjustment Scale (PAS) divided into the areas of premorbid academic and social functioning. We obtained information on age at first exposure to cannabis and use of cannabis before the age of 16. The participants also provided information regarding early traumatic experiences using the Childhood Trauma Questionnaire (CTQ). RESULTS Participants with PNOS and SSD had poorer premorbid academic functioning than those with PBD (F2, 1029 = 7.81, p < 0.001, pη2 = 0.015). Premorbid social adjustment was significantly worse in the SSD group compared to the PBD group (F2, 1024 = 3.10, p = 0.045, pη2 = 0.006), with PNOS in the middle position. Significantly more of the participants with PNOS (17.5%) and SSD (11.5%) used cannabis before the age of 16 compared with PBD (5.3%, Wald χ2 = 6.86, p = 0.03). There were no significant differences between the three groups regarding mean CTQ scores or in the proportion of participants who had experienced at least one type of childhood adversity. CONCLUSIONS Participants with PNOS appear as more similar to participants with SSD than to those with PBD regarding early premorbid adjustment and early cannabis use. The results indicate that many conditions classified as PNOS have functional impairments and problematic substance use from an early age. The prevalence of childhood adversities are high in all three groups.
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Gershon ES, Lee SH, Zhou X, Sweeney JA, Tamminga C, Pearlson GA, Clementz BA, Keshavan MS, Alliey-Rodriguez N, Hudgens-Haney M, Keedy SK, Glahn DC, Asif H, Lencer R, Hill SK. An opportunity for primary prevention research in psychotic disorders. Schizophr Res 2022; 243:433-439. [PMID: 34315649 PMCID: PMC8784565 DOI: 10.1016/j.schres.2021.07.001] [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: 01/21/2021] [Revised: 04/29/2021] [Accepted: 07/01/2021] [Indexed: 10/20/2022]
Abstract
An opportunity has opened for research into primary prevention of psychotic disorders, based on progress in endophenotypes, genetics, and genomics. Primary prevention requires reliable prediction of susceptibility before any symptoms are present. We studied a battery of measures where published data supports abnormalities of these measurements prior to appearance of initial psychosis symptoms. These neurobiological and behavioral measurements included cognition, eye movement tracking, Event Related Potentials, and polygenic risk scores. They generated an acceptably precise separation of healthy controls from outpatients with a psychotic disorder. METHODS: The Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) measured this battery in an ancestry-diverse series of consecutively recruited adult outpatients with a psychotic disorder and healthy controls. Participants include all genders, 16 to 50 years of age, 261 with psychotic disorders (Schizophrenia (SZ) 109, Bipolar with psychosis (BPP) 92, Schizoaffective disorder (SAD) 60), 110 healthy controls. Logistic Regression, and an extension of the Linear Mixed Model to include analysis of pairwise interactions between measures (Environmental kernel Relationship Matrices (ERM)) with multiple iterations, were performed to predict case-control status. Each regression analysis was validated with four-fold cross-validation. RESULTS AND CONCLUSIONS: Sensitivity, specificity, and Area Under the Curve of Receiver Operating Characteristic of 85%, 62%, and 86%, respectively, were obtained for both analytic methods. These prediction metrics demonstrate a promising diagnostic distinction based on premorbid risk variables. There were also statistically significant pairwise interactions between measures in the ERM model. The strong prediction metrics of both types of analytic model provide proof-of-principle for biologically-based laboratory tests as a first step toward primary prevention studies. Prospective studies of adolescents at elevated risk, vs. healthy adolescent controls, would be a next step toward development of primary prevention strategies.
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Affiliation(s)
- Elliot S Gershon
- University of Chicago, Department of Psychiatry, United States of America; University of Chicago, Department of Human Genetics, United States of America.
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA 5000, Australia; UniSA: Allied Health and Human Performance, University of South Australia, Adelaide, SA 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia 5000, Australia.
| | - Xuan Zhou
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA 5000, Australia; UniSA: Allied Health and Human Performance, University of South Australia, Adelaide, SA 5000, Australia; South Australian Health and Medical Research Institute, Adelaide, South Australia 5000, Australia.
| | - John A Sweeney
- University of Cincinnati, Department of Psychiatry United States of America, Sichuan University, Hauxi Center for MR Research, China.
| | - Carol Tamminga
- University of Texas Southwestern, United States of America.
| | | | | | | | | | | | | | - David C Glahn
- Harvard Medical School, Boston Children's Hospital, United States of America.
| | - Huma Asif
- University of Chicago, United States of America.
| | - Rebekka Lencer
- University of Muenster, Muenster, Germany; Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany.
| | - S Kristian Hill
- Rosalind Franklin University of Medicine and Science, United States of America.
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28
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Navarra-Ventura G, Vicent-Gil M, Serra-Blasco M, Cobo J, Fernández-Gonzalo S, Goldberg X, Jodar M, Crosas JM, Palao D, Lahera G, Vieta E, Cardoner N. Higher order theory of mind in patients with bipolar disorder and schizophrenia/schizoaffective disorder. Eur Arch Psychiatry Clin Neurosci 2022; 272:497-507. [PMID: 33948693 DOI: 10.1007/s00406-021-01265-9] [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: 11/15/2020] [Accepted: 04/22/2021] [Indexed: 02/07/2023]
Abstract
Some evidence suggests that patients with bipolar disorder (BD) have better Theory of Mind (ToM) skills than patients with schizophrenia/schizoaffective disorder (SCH). However, this difference is not consistently reported across studies, so rather than being global, it may be restricted to specific aspects of ToM. Our primary objective was to compare higher order ToM performance between BD and SCH patients using the Hinting Task (HT). Ninety-four remitted patients were recruited (BD = 47, SCH = 47). Intelligence quotient (IQ), attention, memory, executive functions, and processing speed were also assessed. Patients with BD performed better on the HT than patients with SCH, even when the analysis was adjusted for IQ and neurocognition (p < 0.001, [Formula: see text] = 0.144). Regression analysis in the total sample showed that a diagnosis of SCH and lower IQ were associated with lower HT scores (R2 = 0.316, p < 0.001). In the BD group, verbal memory and processing speed were the main predictors of HT performance (R2 = 0.344, p < 0.001). In the SCH group, no variable was significant in explaining HT performance. In the context of previous studies that found no significant differences in the most basic aspects of ToM (e.g., understand other people's thoughts/beliefs), our results suggest that differences between the two disorders might be limited to the more challenging aspects (e.g., understand the intended meaning of indirect requests). No causal inferences can be made in this cross-sectional study. However, regression analyses show that whereas in BD patients, ToM functioning would be partially modulated by neurocognitive performance, in SCH patients, it could be largely independent of the well-known neurocognitive impairment.
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Affiliation(s)
- Guillem Navarra-Ventura
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain.,Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, International Excellence Campus, Cerdanyola del Vallès, Bellaterra, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
| | - Muriel Vicent-Gil
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain
| | - Maria Serra-Blasco
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Jesús Cobo
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Sol Fernández-Gonzalo
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, International Excellence Campus, Cerdanyola del Vallès, Bellaterra, Catalonia, Spain
| | - Ximena Goldberg
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Mercè Jodar
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, International Excellence Campus, Cerdanyola del Vallès, Bellaterra, Catalonia, Spain.,Department of Neurology, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain
| | - Josep Maria Crosas
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain
| | - Diego Palao
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain.,Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, International Excellence Campus, Cerdanyola del Vallès, Bellaterra, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Guillermo Lahera
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Faculty of Medicine and Health Sciences, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria, Madrid, Spain
| | - Eduard Vieta
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Institute of Neuroscience, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Narcís Cardoner
- Department of Mental Health, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Catalonia, Spain. .,Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, International Excellence Campus, Cerdanyola del Vallès, Bellaterra, Catalonia, Spain. .,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
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29
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Ramain J, Conus P, Golay P. Exploring the clinical relevance of a dichotomy between affective and non-affective psychosis: Results from a first-episode psychosis cohort study. Early Interv Psychiatry 2022; 16:168-177. [PMID: 33751798 DOI: 10.1111/eip.13143] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 02/03/2021] [Accepted: 03/06/2021] [Indexed: 12/29/2022]
Abstract
AIM Defining diagnosis is complex in early psychosis, which may delay the introduction of an appropriate treatment. The dichotomy of affective and non-affective psychosis is used in clinical setting but remains questioned on a scientific basis. In this study, we explore the clinical relevance of this dichotomy on the basis of clinical variables in a sample of first-episode psychosis patients. METHOD We conducted a prospective study in a sample of 330 first-episode psychosis treated at an early intervention program. Affective and non-affective psychosis patients were compared on premorbid history, baseline data, outcomes and course of symptoms over the 3 years of treatment. RESULTS Affective psychosis patients (22.42%) were more likely to be female, and had a shorter duration of untreated psychosis. The longitudinal analyses revealed that positive symptoms remained higher over the entire follow-up in the non-affective sub-group. A higher degree of variability of manic symptoms and a significantly better insight after 6 months were observed in the affective sub-group. No difference was observed regarding depressive and negative symptoms. At discharge, only the environmental quality of life and insight recovery were better in affective psychosis. CONCLUSIONS Our study suggests that despite marginal differences at baseline presentation, these sub-groups differ regarding outcome, which may require differentiation of treatment and supports the utility of this dichotomy.
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Affiliation(s)
- Julie Ramain
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philippe Conus
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Philippe Golay
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Faculty of Social and Political Sciences, Institute of Psychology, University of Lausanne, Lausanne, Switzerland
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30
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Lynham AJ, Cleaver SL, Jones IR, Walters JTR. A meta-analysis comparing cognitive function across the mood/psychosis diagnostic spectrum. Psychol Med 2022; 52:323-331. [PMID: 32624022 DOI: 10.1017/s0033291720002020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND The nature and degree of cognitive impairments in schizoaffective disorder is not well established. The aim of this meta-analysis was to characterise cognitive functioning in schizoaffective disorder and compare it with cognition in schizophrenia and bipolar disorder. Schizoaffective disorder was considered both as a single category and as its two diagnostic subtypes, bipolar and depressive disorder. METHODS Following a thorough literature search (468 records identified), we included 31 studies with a total of 1685 participants with schizoaffective disorder, 3357 with schizophrenia and 1095 with bipolar disorder. Meta-analyses were conducted for seven cognitive variables comparing performance between participants with schizoaffective disorder and schizophrenia, and between schizoaffective disorder and bipolar disorder. RESULTS Participants with schizoaffective disorder performed worse than those with bipolar disorder (g = -0.30) and better than those with schizophrenia (g = 0.17). Meta-analyses of the subtypes of schizoaffective disorder showed cognitive impairments in participants with the depressive subtype are closer in severity to those seen in participants with schizophrenia (g = 0.08), whereas those with the bipolar subtype were more impaired than those with bipolar disorder (g = -0.23) and less impaired than those with schizophrenia (g = 0.29). Participants with the depressive subtype had worse performance than those with the bipolar subtype but this was not significant (g = 0.25, p = 0.05). CONCLUSION Cognitive impairments increase in severity from bipolar disorder to schizoaffective disorder to schizophrenia. Differences between the subtypes of schizoaffective disorder suggest combining the subtypes of schizoaffective disorder may obscure a study's results and hamper efforts to understand the relationship between this disorder and schizophrenia or bipolar disorder.
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Affiliation(s)
- Amy J Lynham
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Siân L Cleaver
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Ian R Jones
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - James T R Walters
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
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31
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Couttas TA, Jieu B, Rohleder C, Leweke FM. Current State of Fluid Lipid Biomarkers for Personalized Diagnostics and Therapeutics in Schizophrenia Spectrum Disorders and Related Psychoses: A Narrative Review. Front Psychiatry 2022; 13:885904. [PMID: 35711577 PMCID: PMC9197191 DOI: 10.3389/fpsyt.2022.885904] [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: 02/28/2022] [Accepted: 04/27/2022] [Indexed: 11/22/2022] Open
Abstract
Schizophrenia spectrum disorders (SSD) are traditionally diagnosed and categorized through clinical assessment, owing to their complex heterogeneity and an insufficient understanding of their underlying pathology. However, disease progression and accurate clinical diagnosis become problematic when differentiating shared aspects amongst mental health conditions. Hence, there is a need for widely accessible biomarkers to identify and track the neurobiological and pathophysiological development of mental health conditions, including SSD. High-throughput omics applications involving the use of liquid chromatography-mass spectrometry (LC-MS) are driving a surge in biological data generation, providing systems-level insight into physiological and pathogenic conditions. Lipidomics is an emerging subset of metabolomics, largely underexplored amongst the omics systems. Lipid profiles in the brain are highly enriched with well-established functions, including maintenance, support, and signal transduction of neuronal signaling pathways, making them a prospective and exciting source of biological material for neuropsychiatric research. Importantly, changes in the lipid composition of the brain appear to extend into the periphery, as there is evidence that circulating lipid alterations correlate with alterations of psychiatric condition(s). The relative accessibility of fluid lipids offers a unique source to acquire a lipidomic "footprint" of molecular changes, which may support reliable diagnostics even at early disease stages, prediction of treatment response and monitoring of treatment success (theranostics). Here, we summarize the latest fluid lipidomics discoveries in SSD-related research, examining the latest strategies to integrate information into multi-systems overviews that generate new perspectives of SSD-related psychosis identification, development, and treatment.
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Affiliation(s)
- Timothy A Couttas
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Beverly Jieu
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Cathrin Rohleder
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - F Markus Leweke
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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32
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The central executive network and executive function in healthy and persons with schizophrenia groups: a meta-analysis of structural and functional MRI. Brain Imaging Behav 2021; 16:1451-1464. [PMID: 34775552 DOI: 10.1007/s11682-021-00589-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2021] [Indexed: 10/19/2022]
Abstract
This meta-analysis evaluated the extent to which executive function can be understood with structural and functional magnetic resonance imaging. Studies included structural in schizophrenia (k = 8; n = 241) and healthy controls (k = 12; n = 1660), and functional in schizophrenia (k = 4; n = 104) and healthy controls (k = 12; n = 712). Results revealed a positive association in the brain behavior relationship when pooled across schizophrenia and control samples for structural (pr = 0.27) and functional (pr = 0.29) modalities. Subgroup analyses revealed no significant difference for functional neuroimaging (pr = .43, 95%CI = -.08-.77, p = .088) but with structural neuroimaging (pr = .37, 95%CI = -.08-.69, p = .015) the association to executive functions is lower in the control group. Subgroup analyses also revealed no significant differences in the strength of the brain-behavior relationship in the schizophrenia group (pr = .59, 95%CI = .58-.61, p = .881) or the control group (pr = 0.19, 95%CI = 0.18-0.19, p = 0.920), suggesting concordance.
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33
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Genetic Overlap Profiles of Cognitive Ability in Psychotic and Affective Illnesses: A Multisite Study of Multiplex Pedigrees. Biol Psychiatry 2021; 90:373-384. [PMID: 33975707 PMCID: PMC8403107 DOI: 10.1016/j.biopsych.2021.03.012] [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: 09/08/2020] [Revised: 01/08/2021] [Accepted: 03/10/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Cognitive impairment is a key feature of psychiatric illness, making cognition an important tool for exploring of the genetics of illness risk. It remains unclear which measures should be prioritized in pleiotropy-guided research. Here, we generate profiles of genetic overlap between psychotic and affective disorders and cognitive measures in Caucasian and Hispanic groups. METHODS Data were from 4 samples of extended pedigrees (N = 3046). Coefficient of relationship analyses were used to estimate genetic overlap between illness risk and cognitive ability. Results were meta-analyzed. RESULTS Psychosis was characterized by cognitive impairments on all measures with a generalized profile of genetic overlap. General cognitive ability shared greatest genetic overlap with psychosis risk (average endophenotype ranking value [ERV] across samples from a random-effects meta-analysis = 0.32), followed by verbal memory (ERV = 0.24), executive function (ERV = 0.22), and working memory (ERV = 0.21). For bipolar disorder, there was genetic overlap with processing speed (ERV = 0.05) and verbal memory (ERV = 0.11), but these were confined to select samples. Major depressive disorder was characterized by enhanced working and face memory performance, as reflected in significant genetic overlap in 2 samples. CONCLUSIONS There is substantial genetic overlap between risk for psychosis and a range of cognitive abilities (including general intelligence). Most of these effects are largely stable across of ascertainment strategy and ethnicity. Genetic overlap between affective disorders and cognition, on the other hand, tends to be specific to ascertainment strategy, ethnicity, and cognitive test battery.
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34
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Interrelationships between depressive symptoms and positive and negative symptoms of recent onset schizophrenia spectrum disorders: A network analytical approach. J Psychiatr Res 2021; 140:373-380. [PMID: 34144441 DOI: 10.1016/j.jpsychires.2021.05.038] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 05/10/2021] [Accepted: 05/20/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE There is a need to better understand the interrelationships between positive and negative symptoms of recent-onset schizophrenia spectrum disorders (SSD) and co-occurring depressive symptoms. Aims were to determine: (1) whether depressive symptoms are best conceptualised as distinct from, or intrinsic to, positive and negative symptoms; and (2) bridging symptoms. METHODS Network analysis was applied to data from 198 individuals with depressive and psychotic symptoms in SSD from the Psychosis Recent Onset GRoningen Survey (PROGR-S). Measures were: Montgomery-Åsberg Depression Rating Scale and Positive and Negative Syndrome Scale. RESULTS Positive symptoms were just as likely to be associated with depressive and negative symptoms, and had more strong associations with depressive than negative symptoms. Negative symptoms were more likely to be associated with depressive than positive symptoms, and had more strong associations with depressive than positive symptoms. Suspiciousness and stereotyped thinking bridged between positive and depressive symptoms, and apparent sadness and lassitude between negative and depressive symptoms. CONCLUSIONS Depressive symptoms might be best conceptualised as intrinsic to positive and negative symptoms pertaining to deficits in motivation and interest in the psychotic phase of SSD. Treatments targeting bridges between depressive and positive symptoms, and depressive and such negative symptoms, might prevent or improve co-occurring depressive symptoms, or vice-versa, in the psychotic phase of SSD.
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35
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Ji JL, Helmer M, Fonteneau C, Burt JB, Tamayo Z, Demšar J, Adkinson BD, Savić A, Preller KH, Moujaes F, Vollenweider FX, Martin WJ, Repovš G, Murray JD, Anticevic A. Mapping brain-behavior space relationships along the psychosis spectrum. eLife 2021; 10:66968. [PMID: 34313219 PMCID: PMC8315806 DOI: 10.7554/elife.66968] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 06/14/2021] [Indexed: 12/29/2022] Open
Abstract
Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 PSD patients spanning several diagnoses, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results with current sample sizes. However, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and neural gene expression maps derived from the Allen Human Brain Atlas. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.
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Affiliation(s)
- Jie Lisa Ji
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States.,Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, United States
| | - Markus Helmer
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States
| | - Clara Fonteneau
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States
| | | | - Zailyn Tamayo
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States
| | - Jure Demšar
- Department of Psychology, University of Ljubljana, Ljubljana, Slovenia.,Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
| | - Brendan D Adkinson
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States.,Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, United States
| | | | - Katrin H Preller
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital for Psychiatry Zurich, Zurich, Switzerland
| | - Flora Moujaes
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital for Psychiatry Zurich, Zurich, Switzerland
| | - Franz X Vollenweider
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital for Psychiatry Zurich, Zurich, Switzerland
| | - William J Martin
- The Janssen Pharmaceutical Companies of Johnson and Johnson, San Francisco, United States
| | - Grega Repovš
- Department of Psychiatry, University of Zagreb, Zagreb, Croatia
| | - John D Murray
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States.,Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, United States.,Department of Physics, Yale University, New Haven, United States
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States.,Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, United States.,Department of Psychology, Yale University School of Medicine, New Haven, United States
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36
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Tokuda T, Yamashita O, Sakai Y, Yoshimoto J. Clustering of Multiple Psychiatric Disorders Using Functional Connectivity in the Data-Driven Brain Subnetwork. Front Psychiatry 2021; 12:683280. [PMID: 34483983 PMCID: PMC8416352 DOI: 10.3389/fpsyt.2021.683280] [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: 03/20/2021] [Accepted: 07/26/2021] [Indexed: 12/04/2022] Open
Abstract
Recently, the dimensional approach has attracted much attention, bringing a paradigm shift to a continuum of understanding of different psychiatric disorders. In line with this new paradigm, we examined whether there was common functional connectivity related to various psychiatric disorders in an unsupervised manner without explicitly using diagnostic label information. To this end, we uniquely applied a newly developed network-based multiple clustering method to resting-state functional connectivity data, which allowed us to identify pairs of relevant brain subnetworks and subject cluster solutions accordingly. Thus, we identified four subject clusters, which were characterized as major depressive disorder (MDD), young healthy control (young HC), schizophrenia (SCZ)/bipolar disorder (BD), and autism spectrum disorder (ASD), respectively, with the relevant brain subnetwork represented by the cerebellum-thalamus-pallidum-temporal circuit. The clustering results were validated using independent datasets. This study is the first cross-disorder analysis in the framework of unsupervised learning of functional connectivity based on a data-driven brain subnetwork.
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Affiliation(s)
- Tomoki Tokuda
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan.,Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Okito Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan.,Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan
| | - Yuki Sakai
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Junichiro Yoshimoto
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan.,Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan
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Abo Hamza EG, Kéri S, Csigó K, Bedewy D, Moustafa AA. Pareidolia in Schizophrenia and Bipolar Disorder. Front Psychiatry 2021; 12:746734. [PMID: 34955913 PMCID: PMC8702957 DOI: 10.3389/fpsyt.2021.746734] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 11/12/2021] [Indexed: 11/13/2022] Open
Abstract
While there are many studies on pareidolia in healthy individuals and patients with schizophrenia, to our knowledge, there are no prior studies on pareidolia in patients with bipolar disorder. Accordingly, in this study, we, for the first time, measured pareidolia in patients with bipolar disorder (N = 50), and compared that to patients with schizophrenia (N = 50) and healthy controls (N = 50). We have used (a) the scene test, which consists of 10 blurred images of natural scenes that was previously found to produce illusory face responses and (b) the noise test which had 32 black and white images consisting of visual noise and 8 images depicting human faces; participants indicated whether a face was present on these images and to point to the location where they saw the face. Illusory responses were defined as answers when observers falsely identified objects that were not on the images in the scene task (maximum illusory score: 10), and the number of noise images in which they reported the presence of a face (maximum illusory score: 32). Further, we also calculated the total pareidolia score for each task (the sum number of images with illusory responses in the scene and noise tests). The responses were scored by two independent raters with an excellent congruence (kappa > 0.9). Our results show that schizophrenia patients scored higher on pareidolia measures than both healthy controls and patients with bipolar disorder. Our findings are agreement with prior findings on more impaired cognitive processes in schizophrenia than in bipolar patients.
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Affiliation(s)
- Eid G Abo Hamza
- Psychology Department, College of Humanities and Sciences, Ajman University, Ajman, United Arab Emirates.,College of Education, Tanta University, Tanta, Egypt
| | - Szabolcs Kéri
- National Institute of Psychiatry and Addictions, Budapest, Hungary.,Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary.,Department of Physiology, University of Szeged, Szeged, Hungary
| | - Katalin Csigó
- National Institute of Psychiatry and Addictions, Budapest, Hungary
| | - Dalia Bedewy
- Psychology Department, College of Humanities and Sciences, Ajman University, Ajman, United Arab Emirates.,College of Education, Tanta University, Tanta, Egypt
| | - Ahmed A Moustafa
- Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa.,School of Psychology & Marcs Institute for Brain and Behaviour, Western Sydney University, Sydney, NSW, Australia
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Distinct Associations of Cognitive Impairments and Reduced Gray Matter Volumes in Remitted Patients with Schizophrenia and Bipolar Disorder. Neural Plast 2020; 2020:8859388. [PMID: 33381163 PMCID: PMC7748913 DOI: 10.1155/2020/8859388] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 11/04/2020] [Accepted: 11/30/2020] [Indexed: 12/12/2022] Open
Abstract
Background Cognitive impairments are documented in schizophrenia (SZ) and bipolar disorder (BD) and may be related to gray matter volumes (GMVs). Thus, this study is aimed at exploring whether the association between cognitive impairments and GMV alterations is similar in patients with SZ and BD and understanding the underlying neurobiological mechanisms. Methods A total of 137 adult subjects (46 with SZ, 35 with BD, and 56 age-, sex-, and education-matched healthy controls (HC)) completed the MATRICS Consensus Cognitive Battery (MCCB) and structural magnetic resonance imaging scanning. We performed group comparisons of the cognitive impairments, the GMV alterations, and the association between them. Results Compared with HC, the patients with SZ and BD showed shared deficits in 4 cognitive domains (i.e., processing speed, working memory, problem solving, and social cognition) and the composite. SZ and BD had commonly decreased GMVs, mainly in the insula, superior temporal pole, amygdala, anterior cingulate, and frontal cortices (superior, middle, opercular inferior, and orbital frontal gyrus). No correlation between MCCB scores and GMVs was detected in SZ. However, for BD, working memory was relevant to the right hemisphere (i.e., right insula, amygdala, superior temporal pole, and medial and dorsolateral superior frontal gyrus). Limitations. The major limitations were that not all patients were the first-episode status and no medication. Conclusions The association was mainly limited to the BD group. Thus, the underlying pathophysiology of the cognitive deficits, in terms of GMV alterations, may be diverse between two disorders.
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Zangani C, Casetta C, Saunders AS, Donati F, Maggioni E, D’Agostino A. Sleep abnormalities across different clinical stages of Bipolar Disorder: A review of EEG studies. Neurosci Biobehav Rev 2020; 118:247-257. [DOI: 10.1016/j.neubiorev.2020.07.031] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 06/20/2020] [Accepted: 07/27/2020] [Indexed: 12/17/2022]
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Gotra MY, Hill SK, Gershon ES, Tamminga CA, Ivleva EI, Pearlson GD, Keshavan MS, Clementz BA, McDowell JE, Buckley PF, Sweeney JA, Keedy SK. Distinguishing patterns of impairment on inhibitory control and general cognitive ability among bipolar with and without psychosis, schizophrenia, and schizoaffective disorder. Schizophr Res 2020; 223:148-157. [PMID: 32674921 PMCID: PMC7704797 DOI: 10.1016/j.schres.2020.06.033] [Citation(s) in RCA: 8] [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] [Received: 04/17/2020] [Revised: 06/25/2020] [Accepted: 06/28/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND Deficits in inhibitory control on a Stop Signal Task (SST) were previously observed to be of similar magnitude across schizophrenia, schizoaffective, and bipolar disorder with psychosis, despite variation in general cognitive ability. Understanding different patterns of performance on the SST may elucidate different pathways to the impaired inhibitory control each group displayed. Comparing nonpsychotic bipolar disorder to the psychosis groups on SST may also expand our understanding of the shared neurobiology of this illness spectrum. METHODS We tested schizophrenia (n = 220), schizoaffective (n = 216), bipolar disorder with (n = 192) and without psychosis (n = 67), and 280 healthy comparison participants with a SST and the Brief Assessment of Cognition in Schizophrenia (BACS), a measure of general cognitive ability. RESULTS All patient groups had a similar degree of impaired inhibitory control over prepotent responses. However, bipolar groups differed from schizophrenia and schizoaffective groups in showing speeded responses and inhibition errors that were not accounted for by general cognitive ability. Schizophrenia and schizoaffective groups had a broader set of deficits on inhibition and greater general cognitive deficit, which fully accounted for the inhibition deficits. No differences were found between the clinically well-matched bipolar with and without psychosis groups, including for inhibitory control or general cognitive ability. CONCLUSIONS We conclude that 1) while impaired inhibitory control on a SST is of similar magnitude across the schizo-bipolar spectrum, including nonpsychotic bipolar, different mechanisms may underlie the impairments, and 2) history of psychosis in bipolar disorder does not differentially impact inhibitory behavioral control or general cognitive abilities.
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Affiliation(s)
- Milena Y Gotra
- Department of Psychology, Rosalind Franklin University, North Chicago, IL, United States
| | - Scot K Hill
- Department of Psychology, Rosalind Franklin University, North Chicago, IL, United States
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Carol A Tamminga
- Department of Psychiatry, UT-Southwestern Medical Center, Dallas, TX, United States
| | - Elena I Ivleva
- Department of Psychiatry, UT-Southwestern Medical Center, Dallas, TX, United States
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, United States; Institute of Living, Hartford Hospital, Hartford, CT, United States
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconness Medical Center and Harvard Medical School, Boston, MA, United States
| | - Brett A Clementz
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, United States
| | - Jennifer E McDowell
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, United States
| | - Peter F Buckley
- School of Medicine, Virginia Commonwealth University, Richmond, VA, United States
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States.
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Auditory brainstem response (ABR) profiling in schizoaffective disorder. Acta Neuropsychiatr 2020; 32:214-217. [PMID: 32063251 DOI: 10.1017/neu.2020.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The aim of the study was to assess whether the auditory brainstem response (ABR) profiling test for schizophrenia (SZ) would recognise schizoaffective disorder (SZA) patients as SZ or not. METHOD Male and female SZA patients (n = 16) from the psychosis unit at Uppsala University Hospital were investigated. Coded sets of randomised ABR recordings intermingled with patients with SZ, adult attention-deficit hyperactivity disorder (ADHD) and healthy controls were analysed by an independent party blinded to clinical diagnoses. RESULTS The ABR profiling test for SZ was positive in 5/16 patients (31%) and negative in 11/16 patients (69%) with SZA. A surprising finding was that 4/16 (25%) SZA patients were positive for the ABR profiling test for ADHD. CONCLUSION With the ABR profiling test, a minority of patients with SZA tested positive for SZ. In contrast, a majority (85%) of patients with SZ in a previous study tested positive. These preliminary results leave us ignorant whether SZA should be regarded as a SZ-like disorder or a psychotic mood disorder and add to the questions regarding the validity of this diagnostic entity. However, the ABR profiling method is still in its infancy and its exploration in a range of psychiatric disorders is warranted.
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Okuneye VT, Meda S, Pearlson GD, Clementz BA, Keshavan MS, Tamminga CA, Ivleva E, Sweeney JA, Gershon ES, Keedy SK. Resting state auditory-language cortex connectivity is associated with hallucinations in clinical and biological subtypes of psychotic disorders. NEUROIMAGE-CLINICAL 2020; 27:102358. [PMID: 32745995 PMCID: PMC7398970 DOI: 10.1016/j.nicl.2020.102358] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 07/16/2020] [Accepted: 07/20/2020] [Indexed: 01/16/2023]
Abstract
Transdiagnostic evidence for neural disruption in psychotic hallucinations. Hallucinations associated increased connectivity in auditory association cortex. Brain regions for auditory-verbal language comprehension linked to hallucinations. Interhemispheric connectivity alterations related to subgroup-specific findings. Hallucinations link to auditory rs-connectivity tested in 243 psychosis patients.
Background Auditory hallucinations are prevalent across the major psychotic disorders, but their underlying mechanism is poorly understood. Limited prior work supports a hypothesis of altered auditory/language brain systems. To more definitively assess this, we examined whether alterations in resting state connectivity of auditory and language cortices are associated with hallucination severity in a large sample of individuals in the schizo-bipolar spectrum. Methods Whole brain resting state connectivity of auditory and language cortex (primary auditory cortex, unimodal auditory association cortex, Wernicke’s area [speech and heteromodal association cortex] and Broca’s area [speech production motor]) was evaluated for 243 subjects with schizophrenia, schizoaffective, or bipolar disorder with psychosis and 186 healthy controls from the Bipolar Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Regression analyses were conducted to evaluate whether resting state connectivity of auditory and language cortex was a significant predictor of current overall hallucination severity (information about specific modality of hallucinations experienced was not available). Results Increased connectivity between lower and higher order regions of left temporal-parietal auditory/language processing cortex was associated with worse hallucination severity for all psychosis patients. Additionally, within bipolar subjects, increased interhemispheric connectivity between higher order temporal-parietal auditory/language regions was related to greater hallucination severity. When patients were categorized by B-SNIP biomarker-based Biotype groups, interhemispheric connectivity between left auditory association cortex and right core auditory cortex was related to greater hallucination severity for Biotype 1 patients. Exploratory analyses resulted in different patterns of connectivity of auditory/language cortex in patients and controls, unrelated to current hallucination severity. Conclusions Although the findings cannot be precisely attributed to auditory hallucination severity or possible differences in such experiences between groups, increased connectivity among the left hemisphere auditory and receptive language cortex may represent a significant factor contributing to hallucination severity across psychotic disorders, and additional subgroup specific connectivity alterations may also be present.
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Affiliation(s)
- Victoria T Okuneye
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, IL, USA
| | | | | | | | | | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, TX, USA
| | - Elena Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, TX, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, OH, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, IL, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, IL, USA.
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The Association of Bipolar Spectrum Psychopathology with Psychotic-Like and Schizotypic Symptoms. JOURNAL OF PSYCHOPATHOLOGY AND BEHAVIORAL ASSESSMENT 2020. [DOI: 10.1007/s10862-020-09805-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Mundt AP, Baranyi G, Fazel S. Incomplete discussion of bipolar disorder and comorbid substance use disorder - Authors' reply. LANCET GLOBAL HEALTH 2020; 7:e847. [PMID: 31200887 DOI: 10.1016/s2214-109x(19)30226-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 05/03/2019] [Indexed: 11/19/2022]
Affiliation(s)
- Adrian P Mundt
- Medical Faculty, Universidad Diego Portales, Santiago, Chile; Medical School, Universidad San Sebastián, Puerto Montt, Chile.
| | - Gergő Baranyi
- Centre for Research on Environment, Society, and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
| | - Seena Fazel
- Department of Psychiatry, University of Oxford, Oxford, UK
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The effects of age and sex on cognitive impairment in schizophrenia: Findings from the Consortium on the Genetics of Schizophrenia (COGS) study. PLoS One 2020; 15:e0232855. [PMID: 32401791 PMCID: PMC7219730 DOI: 10.1371/journal.pone.0232855] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 04/22/2020] [Indexed: 01/05/2023] Open
Abstract
Recently emerging evidence indicates accelerated age-related changes in the structure and function of the brain in schizophrenia, raising a question about its potential consequences on cognitive function. Using a large sample of schizophrenia patients and controls and a battery of tasks across multiple cognitive domains, we examined whether patients show accelerated age-related decline in cognition and whether an age-related effect differ between females and males. We utilized data of 1,415 schizophrenia patients and 1,062 healthy community collected by the second phase of the Consortium on the Genetics of Schizophrenia (COGS-2). A battery of cognitive tasks included the Letter-Number Span Task, two forms of the Continuous Performance Test, the California Verbal Learning Test, Second Edition, the Penn Emotion Identification Test and the Penn Facial Memory Test. The effect of age and gender on cognitive performance was examined with a general linear model. We observed age-related changes on most cognitive measures, which was similar between males and females. Compared to controls, patients showed greater deterioration in performance on attention/vigilance and greater slowness of processing social information with increasing age. However, controls showed greater age-related changes in working memory and verbal memory compared to patients. Age-related changes (η2p of 0.001 to .008) were much smaller than between-group differences (η2p of 0.005 to .037). This study found that patients showed continued decline of cognition on some domains but stable impairment or even less decline on other domains with increasing age. These findings indicate that age-related changes in cognition in schizophrenia are subtle and not uniform across multiple cognitive domains.
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47
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Madeira N, Duarte JV, Martins R, Costa GN, Macedo A, Castelo-Branco M. Morphometry and gyrification in bipolar disorder and schizophrenia: A comparative MRI study. NEUROIMAGE-CLINICAL 2020; 26:102220. [PMID: 32146321 PMCID: PMC7063231 DOI: 10.1016/j.nicl.2020.102220] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Revised: 01/20/2020] [Accepted: 02/17/2020] [Indexed: 12/31/2022]
Abstract
Increased right globus pallidus is a consistent marker in schizophrenia (SCZ). Left supramarginal gyrification increases in bipolar disorder (BPD) in contrast with SCZ. Gyrification analysis may help distinguish early phases of BPD and SCZ.
Schizophrenia is believed to be a neurodevelopmental disease with high heritability. Differential diagnosis is often challenging, especially in early phases, namely with other psychotic disorders or even mood disorders. such as bipolar disorder with psychotic symptoms. Key pathophysiological changes separating these two classical psychoses remain poorly understood, and current evidence favors a more dimensional than categorical differentiation between schizophrenia and bipolar disorder. While established biomarkers like cortical thickness and grey matter volume are heavily influenced by post-onset changes and thus provide limited possibility of accessing early pathologies, gyrification is assumed to be more specifically determined by genetic and early developmental factors. The aim of our study was to compare both classical and novel morphometric features in these two archetypal psychiatric disorders. We included 20 schizophrenia patients, 20 bipolar disorder patients and 20 age- and gender-matched healthy controls. Data analyses were performed with CAT12/SPM12 applying general linear models for four morphometric measures: gyrification and cortical thickness (surface-based morphometry), and whole-brain grey matter/grey matter volume (voxel-based morphometry - VBM). Group effects were tested using age and gender as covariates (and total intracranial volume for VBM). Voxel-based morphometry analysis revealed a schizophrenia vs. control group effect on regional grey matter volume (p < 0.05, familywise error correction) in the right globus pallidus. There was no group effect on white matter volume when correcting for multiple comparisons neither on cortical thickness. Gyrification changes in clinical samples were found in the left supramarginal gyrus (BA40) – increased and reduced gyrification, respectively, in BPD and SCZ patients - and in the right inferior frontal gyrus (BA47), with a reduction in gyrification of the SCZ group when compared with controls. The joint analysis of different morphometric features, namely measures such as gyrification, provides a promising strategy for the elucidation of distinct phenotypes in psychiatric disorders. Different morphological change patterns, highlighting specific disease trajectories, could potentially generate neuroimaging-derived biomarkers, helping to discriminate schizophrenia from bipolar disorder in early phases, such as first-episode psychosis patients.
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Affiliation(s)
- Nuno Madeira
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - João Valente Duarte
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - Ricardo Martins
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - Gabriel Nascimento Costa
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - António Macedo
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Psychological Medicine, Faculty of Medicine, University of Coimbra, Portugal; Department of Psychiatry, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal.
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Smucny J, Iosif AM, Eaton NR, Lesh TA, Ragland JD, Barch DM, Gold JM, Strauss ME, MacDonald AW, Silverstein SM, Carter CS. Latent Profiles of Cognitive Control, Episodic Memory, and Visual Perception Across Psychiatric Disorders Reveal a Dimensional Structure. Schizophr Bull 2020; 46:154-162. [PMID: 30953588 PMCID: PMC6942157 DOI: 10.1093/schbul/sbz025] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Although meta-analyses suggest that schizophrenia (SZ) is associated with a more severe neurocognitive phenotype than mood disorders such as bipolar disorder, considerable between-subject heterogeneity exists in the phenotypic presentation of these deficits across mental illnesses. Indeed, it is unclear whether the processes that underlie cognitive dysfunction in these disorders are unique to each disease or represent a common neurobiological process that varies in severity. Here we used latent profile analysis (LPA) across 3 distinct cognitive domains (cognitive control, episodic memory, and visual integration; using data from the CNTRACS consortium) to identify distinct profiles of patients across psychotic illnesses. LPA was performed on a sample of 223 psychosis patients (59 with Type I bipolar disorder, 88 with SZ, and 76 with schizoaffective disorder). Seventy-three healthy control participants were included for comparison but were not included in sample LPA. Three latent profiles ("Low," "Moderate," and "High" ability) were identified as the underlying covariance across the 3 domains. The 3-profile solution provided highly similar fit to a single continuous factor extracted by confirmatory factor analysis, supporting a unidimensional structure. Diagnostic ratios did not significantly differ between profiles, suggesting that these profiles cross diagnostic boundaries (an exception being the Low ability profile, which had only one bipolar patient). Profile membership predicted Brief Psychiatric Rating Scale and Young Mania Rating Scale symptom severity as well as everyday communication skills independent of diagnosis. Biological, clinical and methodological implications of these findings are discussed.
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Affiliation(s)
- Jason Smucny
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA
| | - Ana-Maria Iosif
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA
| | - Nicholas R Eaton
- Department of Psychology, State University of New York Stony Brook, Stony Brook, NY
| | - Tyler A Lesh
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA
| | - J Daniel Ragland
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA
| | - Deanna M Barch
- Department of Psychology, Washington University in St. Louis, St. Louis, MO
| | - James M Gold
- Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, MD
| | - Milton E Strauss
- Department of Psychology, University of New Mexico, Albuquerque, NM
| | | | - Steven M Silverstein
- Departments of Psychiatry and Ophthalmology, Rutgers – The State University of New Jersey, New Brunswick, NJ
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA
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Fekete K, Török E, Makkos Z, Kelemen O, Csigó K, Kéri S. Mentalization across the psychosis spectrum. Schizophr Res 2020; 215:471-472. [PMID: 31471247 DOI: 10.1016/j.schres.2019.08.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 05/26/2019] [Accepted: 08/19/2019] [Indexed: 11/24/2022]
Affiliation(s)
- Kata Fekete
- Nyírő Gyula National Institute of Psychiatry and Addictions, Budapest, Hungary
| | - Edina Török
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
| | - Zoltán Makkos
- Nyírő Gyula National Institute of Psychiatry and Addictions, Budapest, Hungary
| | - Oguz Kelemen
- Department of Behavioral Science, University of Szeged, Szeged, Hungary
| | - Katalin Csigó
- Nyírő Gyula National Institute of Psychiatry and Addictions, Budapest, Hungary
| | - Szabolcs Kéri
- Nyírő Gyula National Institute of Psychiatry and Addictions, Budapest, Hungary; Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary; Department of Physiology, University of Szeged, Szeged, Hungary.
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Trotti RL, Parker DA, Sabatinelli D, Tamminga CA, Gershon ES, Keedy SK, Keshavan MS, Pearlson GD, Sweeney JA, McDowell JE, Clementz BA. Electrophysiological correlates of emotional scene processing in bipolar disorder. J Psychiatr Res 2020; 120:83-90. [PMID: 31634753 PMCID: PMC10499256 DOI: 10.1016/j.jpsychires.2019.10.005] [Citation(s) in RCA: 6] [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] [Received: 06/20/2019] [Revised: 08/12/2019] [Accepted: 10/03/2019] [Indexed: 12/19/2022]
Abstract
Emotional dysfunction is a core feature of bipolar I disorder (BD). Behavioral data suggest that emotional processing may differ based on history of psychosis, but physiological studies frequently disregard this differentiating feature. Face processing studies indicate that emotion-related components of event-related potentials (ERPs) are abnormal in BD, but fMRI data using emotional scenes are mixed. The current study used ERPs to examine emotional scene perception in BD with and without a history of psychosis (BDP, BDNP). 386 participants from the PARDIP consortium (HC = 181, BDP = 130, BDNP = 75) viewed neutral, pleasant, and unpleasant scenes from the International Affective Picture System (IAPS) during continuous EEG recording. The early posterior negativity (EPN) and late positive potential (LPP) were examined for group and stimulus effects. Analyses were conducted for groups on and off medications to examine associations between medication status, psychosis, and ERP response. Group differences were found between HC and BD in emotional modulation of the EPN and between HC and BDP in the LPP to pleasant images. There was a significant interaction between psychosis history and anticonvulsant status in the EPN, but no other medication associations were found. The relationship between neural/self-reported emotional responses and clinical symptoms were examined with canonical correlations, but no significant associations were found. Results from this large well characterized sample indicate mild deviations in neural reactivity related to medication, mood, and psychosis history. However, processing of emotional scenes appears mostly intact in individuals with BD regardless of symptom severity.
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Affiliation(s)
- Rebekah L Trotti
- Department of Psychology and Neuroscience, University of Georgia, 500 DW Brooks Drive, Athens, GA, 30606, USA
| | - David A Parker
- Department of Psychology and Neuroscience, University of Georgia, 500 DW Brooks Drive, Athens, GA, 30606, USA
| | - Dean Sabatinelli
- Department of Psychology and Neuroscience, University of Georgia, 500 DW Brooks Drive, Athens, GA, 30606, USA
| | - Carol A Tamminga
- University of Texas Southwestern Medical Center, 2201 Inwood Rd., NE5.110, Dallas, TX, 75390, USA
| | - Elliot S Gershon
- University of Chicago, 5841 S. Maryland Ave, Chicago, IL, 60637, USA
| | - Sarah K Keedy
- University of Chicago, 5841 S. Maryland Ave, Chicago, IL, 60637, USA
| | | | - Godfrey D Pearlson
- Institute of Living, Hartford Hospital, 200 Retreat Ave., Hartford, CT, 06106, USA
| | - John A Sweeney
- University of Texas Southwestern Medical Center, 2201 Inwood Rd., NE5.110, Dallas, TX, 75390, USA
| | - Jennifer E McDowell
- Department of Psychology and Neuroscience, University of Georgia, 500 DW Brooks Drive, Athens, GA, 30606, USA
| | - Brett A Clementz
- Department of Psychology and Neuroscience, University of Georgia, 500 DW Brooks Drive, Athens, GA, 30606, USA.
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