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Yorca-Ruiz Á, Magdaleno Herrero R, Ortiz García de la Foz V, Murillo-García N, Ayesa-Arriola R. Breaking down processing speed: Motor and cognitive insights in first-episode psychosis and unaffected first-degree relatives. SPANISH JOURNAL OF PSYCHIATRY AND MENTAL HEALTH 2024:S2950-2853(24)00036-X. [PMID: 38908403 DOI: 10.1016/j.sjpmh.2024.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 04/17/2024] [Accepted: 06/16/2024] [Indexed: 06/24/2024]
Abstract
INTRODUCTION Processing speed (PS) deficits represent a fundamental aspect of cognitive impairment, evident not only in schizophrenia but also in individuals undergoing their first episode of psychosis (FEP) and their unaffected first-degree relatives. Heterogeneity in tests assessing PS reflects the participation of motor and cognitive subcomponents to varying degrees. We aim to explore differences in performance of the subcomponents of PS in FEP patients, parents, siblings, and controls. MATERIALS AND METHODS Results from tests, including Trail Making Test part A and part B, Digit Symbol Coding Test, Grooved Pegboard Test, and Stroop Word and Stroop Color subtests, were obtained from 133 FEP patients, 146 parents, and 202 controls. Exploratory factor analysis (EFA) was employed in controls to establish the structure, followed by confirmatory factor analysis (CFA) to verify if the other groups share this structure. RESULTS EFA revealed a two-factor model: Factor 1 for the motor subcomponent and Factor 2 for the cognitive subcomponent. Subsequently, CFA indicated a good fit for the remaining groups with differences in the relationship between the factors. CONCLUSIONS Differences in the relationships of factors within a common structure suggest the involvement of different compensatory strategies among groups, providing insights into the underlying mechanisms of PS deficits in patients and relatives.
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Affiliation(s)
- Ángel Yorca-Ruiz
- Department of Molecular Biology, Faculty of Medicine, University of Cantabria, Santander, Spain; Department of Psychiatry, Valdecilla Biomedical Research Institute, Santander, Spain
| | - Rebeca Magdaleno Herrero
- Department of Molecular Biology, Faculty of Medicine, University of Cantabria, Santander, Spain; Department of Psychiatry, Valdecilla Biomedical Research Institute, Santander, Spain
| | - Víctor Ortiz García de la Foz
- Department of Psychiatry, Valdecilla Biomedical Research Institute, Santander, Spain; Biomedical Research Networking Center for Mental Health (CIBERSAM), Madrid, Spain
| | - Nancy Murillo-García
- Department of Molecular Biology, Faculty of Medicine, University of Cantabria, Santander, Spain; Department of Psychiatry, Valdecilla Biomedical Research Institute, Santander, Spain
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, Valdecilla Biomedical Research Institute, Santander, Spain; Faculty of Psychology, National University of Distance Education (UNED), Madrid, Spain; Biomedical Research Networking Center for Mental Health (CIBERSAM), Madrid, Spain.
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Chen F, Mihaljevic M, Hou Z, Li Y, Lu H, Mori S, Sawa A, Faria AV. Relation between white matter integrity, perfusion, and processing speed in early-stage schizophrenia. J Psychiatr Res 2023; 163:166-171. [PMID: 37210835 DOI: 10.1016/j.jpsychires.2023.05.049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 05/23/2023]
Abstract
OBJECTIVE Cerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Several studies report CBF and white matter structural alterations individually. However, whether and how these pathological changes relate to each other remains elusive. By using our cohort of individuals with early-stage schizophrenia, we investigated the relationship between CBF and white matter structure. METHOD We studied 51 early-stage schizophrenia patients and age- and sex-matched healthy controls. We investigated the relationship among tissue structure (assessed with diffusion weighted imaging), perfusion (accessed by pseudo-continuous arterial labeling imaging), and neuropsychological indices (focusing on processing speed). We focused on the corpus callosum, due to its major role in associative functions and directness on revealing the architecture of a major white matter bundle. We performed mediation analysis to identify the possible mechanism underlay the relationship among cognition and white matter integrity and perfusion. RESULTS The CBF and the fractional anisotropy (FA) were inversely correlated in the corpus callosum of early-stage schizophrenia patients. While CBF negatively correlated with processing speed, FA correlated positively with this cognitive measure. These results were not observed in controls. Mediation analysis revealed that the effect of FA on processing speed was mediated via the CBF. CONCLUSIONS We provide evidence of a relationship between brain perfusion and white matter integrity in the corpus callosum in early-stage schizophrenia. These findings may shed the light on underlying metabolic support for structural changes with cognitive impact in schizophrenia.
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Affiliation(s)
- Feng Chen
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, 570311, China
| | - Marina Mihaljevic
- Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhipeng Hou
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Yang Li
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, 570311, China
| | - Hanzhang Lu
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Susumu Mori
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Akira Sawa
- Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Psychiatry, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, The Whiting School of Engineering, Baltimore, MD, USA; Department of Mental Health, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Andreia V Faria
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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Millgate E, Smart SE, Pardiñas AF, Kravariti E, Ajnakina O, Kępińska AP, Andreassen OA, Barnes TRE, Berardi D, Crespo-Facorro B, D'Andrea G, Demjaha A, Di Forti M, Doody GA, Kassoumeri L, Ferchiou A, Guidi L, Joyce EM, Lastrina O, Melle I, Pignon B, Richard JR, Simonsen C, Szöke A, Tarricone I, Tortelli A, Vázquez-Bourgon J, Murray RM, Walters JTR, MacCabe JH. Cognitive performance at first episode of psychosis and the relationship with future treatment resistance: Evidence from an international prospective cohort study. Schizophr Res 2023; 255:173-181. [PMID: 37001392 PMCID: PMC10390338 DOI: 10.1016/j.schres.2023.03.020] [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: 10/24/2021] [Revised: 01/26/2023] [Accepted: 03/11/2023] [Indexed: 05/13/2023]
Abstract
BACKGROUND Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases. METHODS Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up. RESULTS On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049). CONCLUSIONS Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions.
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Affiliation(s)
- Edward Millgate
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sophie E Smart
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Eugenia Kravariti
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Adrianna P Kępińska
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | | | - Domenico Berardi
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, Hospital Universitario Virgen del Rocio, IBiS, Universidad de Sevilla, Spain; Centro de Investigacion en Red Salud Mental (CIBERSAM), Sevilla, Spain
| | - Giuseppe D'Andrea
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Marta Di Forti
- Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; South London and Maudsley NHS Mental Health Foundation Trust, London, UK
| | - Gillian A Doody
- Department of Medical Education, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, UK
| | - Laura Kassoumeri
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Aziz Ferchiou
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; AP-HP, Hôpitaux Universitaires H. Mondor, DMU IMPACT, FHU ADAPT, Creteil, France
| | - Lorenzo Guidi
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team (BoTPT), Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Eileen M Joyce
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ornella Lastrina
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team (BoTPT), Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Baptiste Pignon
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; AP-HP, Hôpitaux Universitaires H. Mondor, DMU IMPACT, FHU ADAPT, Creteil, France
| | - Jean-Romain Richard
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France
| | - Carmen Simonsen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Early Intervention in Psychosis Advisory Unit for South East Norway (TIPS Sør-Øst), Division of Mental Health and Addiction, Oslo University Hospital, Norway
| | - Andrei Szöke
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; AP-HP, Hôpitaux Universitaires H. Mondor, DMU IMPACT, FHU ADAPT, Creteil, France
| | - Ilaria Tarricone
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team (BoTPT), Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Andrea Tortelli
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; Groupe Hospitalier Universitaire Psychiatrie Neurosciences Paris, Pôle Psychiatrie Précarité, Paris, France
| | - Javier Vázquez-Bourgon
- Centro de Investigacion en Red Salud Mental (CIBERSAM), Sevilla, Spain; Department of Psychiatry, University Hospital Marques de Valdecilla - Instituto de Investigación Marques de Valdecilla (IDIVAL), Santander, Spain; Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander, Spain
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - James H MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; South London and Maudsley NHS Mental Health Foundation Trust, London, UK.
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Gordillo D, da Cruz JR, Chkonia E, Lin WH, Favrod O, Brand A, Figueiredo P, Roinishvili M, Herzog MH. The EEG multiverse of schizophrenia. Cereb Cortex 2022; 33:3816-3826. [PMID: 36030389 PMCID: PMC10068296 DOI: 10.1093/cercor/bhac309] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 07/15/2022] [Accepted: 07/15/2022] [Indexed: 11/14/2022] Open
Abstract
Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. One tacit assumption of these "deep rooting" approaches is that paradigms tap into common and representative aspects of the disorder. Here, we analyzed the resting-state electroencephalogram (EEG) of 121 schizophrenia patients and 75 controls. Using multiple signal processing methods, we extracted 194 EEG features. Sixty-nine out of the 194 EEG features showed a significant difference between patients and controls, indicating that these features detect an important aspect of schizophrenia. Surprisingly, the correlations between these features were very low. We discuss several explanations to our results and propose that complementing "deep" with "shallow" rooting approaches might help in understanding the underlying mechanisms of the disorder.
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Affiliation(s)
- Dario Gordillo
- Corresponding author: Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.
| | | | - Eka Chkonia
- Department of Psychiatry, Tbilisi State Medical University (TSMU), 0186 Tbilisi, Georgia
- Institute of Cognitive Neurosciences, Free University of Tbilisi, 0159 Tbilisi, Georgia
| | - Wei-Hsiang Lin
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Ophélie Favrod
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Andreas Brand
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Patrícia Figueiredo
- Institute for Systems and Robotics – Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal
| | - Maya Roinishvili
- Institute of Cognitive Neurosciences, Free University of Tbilisi, 0159 Tbilisi, Georgia
- Laboratory of Vision Physiology, Ivane Beritashvili Centre of Experimental Biomedicine, 0160 Tbilisi, Georgia
| | - Michael H Herzog
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
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Yang KC, Hsieh WC, Chou YH. Cognitive factor structure and measurement invariance between healthy controls and patients with major depressive disorder. J Psychiatr Res 2022; 151:598-605. [PMID: 35636038 DOI: 10.1016/j.jpsychires.2022.05.029] [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: 12/05/2021] [Revised: 05/03/2022] [Accepted: 05/20/2022] [Indexed: 02/01/2023]
Abstract
Cognitive impairments are crucial in functional outcomes of major depressive disorder (MDD). The effectiveness of currently available treatment methods for cognitive deficits is suboptimal. A cognitive test battery is often applied to evaluate cognition with multiple interrelated and difficult-to-interpret outcomes. Generating cognitive factor scores after the confirmation of a common cognitive structure and measurement invariance between healthy controls (HCs) and patients may aid in understanding cognition further. This methodology has been applied for several neuropsychiatric disorders, but not for MDD. Therefore, we conducted a series of exploratory factor analyses (EFA), confirmatory factor analyses (CFA), and multiple groups CFA (MGCFA) for a cognitive test battery in HCs and patients with MDD. The initial EFA of 106 HCs yielded a three-factor model-comprising attention, memory, and executive function. The CFA confirmed the initial model in other 94 HCs with revisions, which reasonably fit the cognitive data of 54 patients with MDD. MGCFA supported the measurement invariance of the determined model between HCs and patients with MDD. The associations of cognitive factor scores with age or education and the effect sizes of group differences in cognitive factor scores externally validated the determined model. In conclusion, this is the first study to demonstrate the measurement invariance of a cognitive model between HCs and patients with MDD using MGCFA. The measurement invariance substantiated valid group comparisons of factor scores and their relationships with other markers. The current results may be applicable for the development of improved treatment strategies for cognitive impairments in MDD.
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Affiliation(s)
- Kai-Chun Yang
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Department of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wen-Chih Hsieh
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yuan-Hwa Chou
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Department of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Center for Quality Management, Taipei Veterans General Hospital, Taipei, Taiwan.
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Lemvigh CK, Brouwer RM, Pantelis C, Jensen MH, Hilker RW, Legind CS, Anhøj SJ, Robbins TW, Sahakian BJ, Glenthøj BY, Fagerlund B. Heritability of specific cognitive functions and associations with schizophrenia spectrum disorders using CANTAB: a nation-wide twin study. Psychol Med 2022; 52:1101-1114. [PMID: 32779562 DOI: 10.1017/s0033291720002858] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Many cognitive functions are under strong genetic control and twin studies have demonstrated genetic overlap between some aspects of cognition and schizophrenia. How the genetic relationship between specific cognitive functions and schizophrenia is influenced by IQ is currently unknown. METHODS We applied selected tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) to examine the heritability of specific cognitive functions and associations with schizophrenia liability. Verbal and performance IQ were estimated using The Wechsler Adult Intelligence Scale-III and the Danish Adult Reading Test. In total, 214 twins including monozygotic (MZ = 32) and dizygotic (DZ = 22) pairs concordant or discordant for a schizophrenia spectrum disorder, and healthy control pairs (MZ = 29, DZ = 20) were recruited through the Danish national registers. Additionally, eight twins from affected pairs participated without their sibling. RESULTS Significant heritability was observed for planning/spatial span (h2 = 25%), self-ordered spatial working memory (h2 = 64%), sustained attention (h2 = 56%), and movement time (h2 = 47%), whereas only unique environmental factors contributed to set-shifting, reflection impulsivity, and thinking time. Schizophrenia liability was associated with planning/spatial span (rph = -0.34), self-ordered spatial working memory (rph = -0.24), sustained attention (rph = -0.23), and set-shifting (rph = -0.21). The association with planning/spatial span was not driven by either performance or verbal IQ. The remaining associations were shared with performance, but not verbal IQ. CONCLUSIONS This study provides further evidence that some cognitive functions are heritable and associated with schizophrenia, suggesting a partially shared genetic etiology. These functions may constitute endophenotypes for the disorder and provide a basis to explore genes common to cognition and schizophrenia.
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Affiliation(s)
- Cecilie K Lemvigh
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Department of Psychology, Faculty of Social Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rachel M Brouwer
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Christos Pantelis
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - Maria H Jensen
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Child and Adolescent Mental Health Center, Mental Health Services, Capital Region of Denmark
| | - Rikke W Hilker
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian S Legind
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Mental Health Center North Zealand, Hilleroed, Denmark
| | - Simon J Anhøj
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Department of Psychiatry Svendborg, Baagoes Alle 25, 5700 Svendborg, Denmark
| | - Trevor W Robbins
- Department of Psychology, University of Cambridge, Cambridge, UK
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Barbara J Sahakian
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Birte Y Glenthøj
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Birgitte Fagerlund
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
- Department of Psychology, Faculty of Social Sciences, University of Copenhagen, Copenhagen, Denmark
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7
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Page SC, Sripathy SR, Farinelli F, Ye Z, Wang Y, Hiler DJ, Pattie EA, Nguyen CV, Tippani M, Moses RL, Chen HY, Tran MN, Eagles NJ, Stolz JM, Catallini JL, Soudry OR, Dickinson D, Berman KF, Apud JA, Weinberger DR, Martinowich K, Jaffe AE, Straub RE, Maher BJ. Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance. Proc Natl Acad Sci U S A 2022; 119:e2109395119. [PMID: 35017298 PMCID: PMC8784142 DOI: 10.1073/pnas.2109395119] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 11/10/2021] [Indexed: 12/11/2022] Open
Abstract
Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRSs) for schizophrenia (SCZ) and a clinical diagnosis of SCZ, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures in the patient-derived neurons that implicated altered Na+ channel function, action potential interspike interval, and gamma-aminobutyric acid-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these SCZ patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.
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Affiliation(s)
| | | | | | - Zengyou Ye
- Lieber Institute for Brain Development, Baltimore, MD 21205
| | - Yanhong Wang
- Lieber Institute for Brain Development, Baltimore, MD 21205
| | - Daniel J Hiler
- Lieber Institute for Brain Development, Baltimore, MD 21205
| | | | | | | | | | - Huei-Ying Chen
- Lieber Institute for Brain Development, Baltimore, MD 21205
| | - Matthew Nguyen Tran
- Lieber Institute for Brain Development, Baltimore, MD 21205
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205
| | | | - Joshua M Stolz
- Lieber Institute for Brain Development, Baltimore, MD 21205
| | - Joseph L Catallini
- Lieber Institute for Brain Development, Baltimore, MD 21205
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | | | - Dwight Dickinson
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, NIH, Bethesda, MD 20892
| | - Karen F Berman
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, NIH, Bethesda, MD 20892
| | - Jose A Apud
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, NIH, Bethesda, MD 20892
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Baltimore, MD 21205
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21205
| | - Keri Martinowich
- Lieber Institute for Brain Development, Baltimore, MD 21205
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Baltimore, MD 21205
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | | | - Brady J Maher
- Lieber Institute for Brain Development, Baltimore, MD 21205;
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205
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Vita A, Gaebel W, Mucci A, Sachs G, Barlati S, Giordano GM, Nibbio G, Nordentoft M, Wykes T, Galderisi S. European Psychiatric Association guidance on treatment of cognitive impairment in schizophrenia. Eur Psychiatry 2022; 65:e57. [PMID: 36059103 PMCID: PMC9532218 DOI: 10.1192/j.eurpsy.2022.2315] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Background Although cognitive impairment is a core symptom of schizophrenia related to poorer outcomes in different functional domains, it still remains a major therapeutic challenge. To date, no comprehensive treatment guidelines for cognitive impairment in schizophrenia are implemented. Methods The aim of the present guidance paper is to provide a comprehensive meta-review of the current available evidence-based treatments for cognitive impairment in schizophrenia. The guidance is structured into three sections: pharmacological treatment, psychosocial interventions, and somatic treatments. Results Based on the reviewed evidence, this European Psychiatric Association guidance recommends an appropriate pharmacological management as a fundamental starting point in the treatment of cognitive impairment in schizophrenia. In particular, second-generation antipsychotics are recommended for their favorable cognitive profile compared to first-generation antipsychotics, although no clear superiority of a single second-generation antipsychotic has currently been found. Anticholinergic and benzodiazepine burdens should be kept to a minimum, considering the negative impact on cognitive functioning. Among psychosocial interventions, cognitive remediation and physical exercise are recommended for the treatment of cognitive impairment in schizophrenia. Noninvasive brain stimulation techniques could be taken into account as add-on therapy. Conclusions Overall, there is definitive progress in the field, but further research is needed to develop specific treatments for cognitive impairment in schizophrenia. The dissemination of this guidance paper may promote the development of shared guidelines concerning the treatment of cognitive functions in schizophrenia, with the purpose to improve the quality of care and to achieve recovery in this population.
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9
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Vita A, Gaebel W, Mucci A, Sachs G, Erfurth A, Barlati S, Zanca F, Giordano GM, Birkedal Glenthøj L, Nordentoft M, Galderisi S. European Psychiatric Association guidance on assessment of cognitive impairment in schizophrenia. Eur Psychiatry 2022; 65:e58. [PMID: 36059109 PMCID: PMC9532219 DOI: 10.1192/j.eurpsy.2022.2316] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Background Impairment in a wide range of cognitive abilities has been consistently reported in individuals with schizophrenia. Both neurocognitive and social cognitive deficits are thought to underlie severe functional disabilities associated with schizophrenia. Despite the key role in schizophrenia outcome, cognition is still poorly assessed in both research and clinical settings. Methods In this guidance paper, we provide a systematic review of the scientific literature and elaborate several recommendations for the assessment of cognitive functions in schizophrenia both in research settings and in real-world clinical practice. Results Expert consensus and systematic reviews provided guidance for the optimal assessment of cognitive functions in schizophrenia. Based on the reviewed evidence, we recommend a comprehensive and systematic assessment of neurocognitive and social cognitive domains in schizophrenia, in all phases of the disorder, as well as in subjects at risk to develop psychosis. This European Psychiatric Association guidance recommends not only the use of observer reports but also self-reports and interview-based cognitive assessment tools. The guidance also provides a systematic review of the state of the art of assessment in the first episode of psychosis patients and in individuals at risk for psychosis. Conclusion The comprehensive review of the evidence and the recommendations might contribute to advance the field, allowing a better cognitive assessment, and avoiding overlaps with other psychopathological dimensions. The dissemination of this guidance paper may promote the development of shared guidelines concerning the assessment of cognitive functions in schizophrenia, with the purpose to improve the quality of care and to obtain recovery.
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A network analysis and empirical validation of executive deficits in patients with psychosis and their healthy siblings. Schizophr Res 2021; 237:122-130. [PMID: 34521039 DOI: 10.1016/j.schres.2021.09.008] [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: 10/08/2020] [Revised: 04/19/2021] [Accepted: 09/06/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND Psychopathological symptoms and cognitive impairment are core features of patients with psychotic disorders. Executive dysfunctions are commonly observed and typically assessed using tests like the Wisconsin Card Sorting Test (WCST). However, the structure of executive deficits remains unclear, and the underlying processes may be different. This study aimed to explore and compare the network structure of WCST measures in patients with psychosis and their unaffected siblings and to empirically validate the resulting network structure of the patients. METHODS The subjects were 298 patients with a DSM 5 diagnosis of a psychotic disorder and 89 of their healthy siblings. The dimensionality and network structure of the WCST were examined by means of exploratory graph analysis (EGA) and network centrality parameters. RESULTS The WCST network structure comprised 4 dimensions: perseveration (PER), inefficient sorting (IS), failure to maintain set (FMS) and learning (LNG). The patient and sibling groups showed a similar network structure, which was reliably estimated. PER and IS showed common and strong associations with antecedent, concurrent and outcome validators. The LNG dimension was also moderately associated with these validators, but FMS did not show significant associations. CONCLUSIONS Four cognitive processes underlying WCST performance were identified by the network analysis. PER, IS and LNG were associated with and shared common antecedent, concurrent and outcome validators, while FMS was not associated with external validators. These four underlying dysfunctions might help disentangle the neurofunctional basis of executive deficits in psychosis.
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11
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A generative-discriminative framework that integrates imaging, genetic, and diagnosis into coupled low dimensional space. Neuroimage 2021; 238:118200. [PMID: 34118398 DOI: 10.1016/j.neuroimage.2021.118200] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 04/08/2021] [Accepted: 05/22/2021] [Indexed: 11/21/2022] Open
Abstract
We propose a novel optimization framework that integrates imaging and genetics data for simultaneous biomarker identification and disease classification. The generative component of our model uses a dictionary learning framework to project the imaging and genetic data into a shared low dimensional space. We have coupled both the data modalities by tying the linear projection coefficients to the same latent space. The discriminative component of our model uses logistic regression on the projection vectors for disease diagnosis. This prediction task implicitly guides our framework to find interpretable biomarkers that are substantially different between a healthy and disease population. We exploit the interconnectedness of different brain regions by incorporating a graph regularization penalty into the joint objective function. We also use a group sparsity penalty to find a representative set of genetic basis vectors that span a low dimensional space where subjects are easily separable between patients and controls. We have evaluated our model on a population study of schizophrenia that includes two task fMRI paradigms and single nucleotide polymorphism (SNP) data. Using ten-fold cross validation, we compare our generative-discriminative framework with canonical correlation analysis (CCA) of imaging and genetics data, parallel independent component analysis (pICA) of imaging and genetics data, random forest (RF) classification, and a linear support vector machine (SVM). We also quantify the reproducibility of the imaging and genetics biomarkers via subsampling. Our framework achieves higher class prediction accuracy and identifies robust biomarkers. Moreover, the implicated brain regions and genetic variants underlie the well documented deficits in schizophrenia.
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12
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Evermann U, Gaser C, Besteher B, Langbein K, Nenadić I. Cortical Gyrification, Psychotic-Like Experiences, and Cognitive Performance in Nonclinical Subjects. Schizophr Bull 2020; 46:1524-1534. [PMID: 32691058 PMCID: PMC7707080 DOI: 10.1093/schbul/sbaa068] [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] [Indexed: 01/04/2023]
Abstract
BACKGROUND Psychotic-like experiences (PLE) are present in nonclinical populations, yet their association with brain structural variation, especially markers of early neurodevelopment, is poorly understood. We tested the hypothesis that cortical surface gyrification, a putative marker of early brain development, is associated with PLE in healthy subjects. METHODS We analyzed gyrification from 3 Tesla MRI scans (using CAT12 software) and PLE (positive, negative, and depressive symptom dimensions derived from the Community Assessment of Psychic Experiences, CAPE) in 103 healthy participants (49 females, mean age 29.13 ± 9.37 years). A subsample of 63 individuals completed tasks from the Wechsler Adult Intelligence Scale and Controlled Oral Word Association Test. Estimated IQ and a composite neuropsychological score were used to explore mediation pathways via cognition. RESULTS Positive PLE distress was negatively associated with gyrification of the left precuneus. PLE depression dimension showed a negative association with gyrification in the right supramarginal and temporal region. There was no significant mediating effect of cognition on these associations. CONCLUSION Our results support a neurobiological psychosis spectrum, for the first time linking an early developmental imaging marker (rather than volume) to dimensional subclinical psychotic symptoms. While schizophrenia risk, neurodevelopment, and cognitive function might share genetic risk factors, additional mediation analyses did not confirm a mediating effect of cognition on the gyrification-psychopathology correlation.
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Affiliation(s)
- Ulrika Evermann
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Bianca Besteher
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Kerstin Langbein
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Igor Nenadić
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Marburg University Hospital – UKGM, Marburg, Germany
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Associations between facial affect recognition and neurocognition in subjects at ultra-high risk for psychosis: A case-control study. Psychiatry Res 2020; 290:112969. [PMID: 32450415 DOI: 10.1016/j.psychres.2020.112969] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 03/28/2020] [Accepted: 03/29/2020] [Indexed: 12/22/2022]
Abstract
The nature of facial affect recognition (FAR) deficits in subjects at ultra-high risk (UHR) for psychosis remains unclear. In schizophrenia, associations between FAR impairment and poor neurocognition have been demonstrated meta-analytically, but this potential link is understudied in the UHR population. Our study investigated a cross-sectional sample of UHR subjects (n = 22) and healthy controls (n = 50), with the Degraded Facial Affect Recognition (DFAR) Task and a neurocognitive test battery. Our primary aims were 1. to examine associations between FAR and neurocognition in UHR subjects and 2. to examine if associations differed between cases and controls. The secondary aim was to examine group differences in FAR and neurocognitive performance. In UHR subjects, FAR was significantly associated with working memory, a neurocognitive composite score and intelligence, and at trend level with most other assessed neurocognitive domains, with moderate to large effect sizes. There were no significant associations in controls. Associations between FAR and working memory and the neurocognitive composite score differed significantly between cases and controls. UHR subjects did not differ from controls on DFAR Task performance but showed significant deficits in three of six neurocognitive domains. Results may suggest that FAR is associated with working memory in UHR subjects, possibly reflecting a neurocognitive compensatory mechanism.
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Andersen R, Fagerlund B, Rasmussen H, Ebdrup B, Aggernaes B, Gade A, Oranje B, Glenthoj B. The influence of impaired processing speed on cognition in first-episode antipsychotic-naïve schizophrenic patients. Eur Psychiatry 2020; 28:332-9. [DOI: 10.1016/j.eurpsy.2012.06.003] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2012] [Revised: 06/05/2012] [Accepted: 06/08/2012] [Indexed: 12/30/2022] Open
Abstract
AbstractBackground:Impaired cognition is a prominent feature of schizophrenia. To what extent the heterogeneous cognitive impairments can be accounted for by considering only a single underlying impairment or a small number of core impairments remains elusive. This study examined whether cognitive impairments in antipsychotic-naïve, first-episode schizophrenia patients may be determined by a relative slower speed of information processing.Method:Forty-eight antipsychotic-naïve patients with first-episode schizophrenia and 48 matched healthy controls were administered a comprehensive battery of neuropsychological tests to assess domains of cognitive impairments in schizophrenia. Composite scores were calculated, grouping tests into cognitive domains.Results:There were significant differences between patients and healthy controls on global cognition and all cognitive domains, including verbal intelligence, processing speed, sustained attention, working memory, reasoning and problem solving, verbal learning and memory, visual learning and memory, and reaction time. All these significant differences, except for verbal intelligence and global cognition, disappeared when processing speed was included as a covariate.Conclusion:At the first stage of illness, antipsychotic-naïve patients with schizophrenia display moderate/severe impairments in all the cognitive domains assessed. The results support the contention of a global cognitive dysfunction in schizophrenia that to some extent may be determined by impaired processing speed.
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Dickinson D, Zaidman SR, Giangrande EJ, Eisenberg DP, Gregory MD, Berman KF. Distinct Polygenic Score Profiles in Schizophrenia Subgroups With Different Trajectories of Cognitive Development. Am J Psychiatry 2020; 177:298-307. [PMID: 31838871 PMCID: PMC9627722 DOI: 10.1176/appi.ajp.2019.19050527] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
OBJECTIVE Different cognitive development histories in schizophrenia may reflect variation across dimensions of genetic influence. The authors derived and characterized cognitive development trajectory subgroups within a schizophrenia sample and profiled the subgroups across polygenic scores (PGSs) for schizophrenia, cognition, educational attainment, and attention deficit hyperactivity disorder (ADHD). METHODS Demographic, clinical, and genetic data were collected at the National Institute of Mental Health from 540 schizophrenia patients, 247 unaffected siblings, and 844 control subjects. Cognitive trajectory subgroups were derived through cluster analysis using estimates of premorbid and current IQ. PGSs were generated using standard methods. Associations were tested using general linear models and logistic regression. RESULTS Cluster analyses identified three cognitive trajectory subgroups in the schizophrenia group: preadolescent cognitive impairment (19%), adolescent disruption of cognitive development (44%), and cognitively stable adolescent development (37%). Together, the four PGSs significantly predicted 7.9% of the variance in subgroup membership. Subgroup characteristics converged with genetic patterns. Cognitively stable individuals had the best adult clinical outcomes and differed from control subjects only in schizophrenia PGSs. Those with adolescent disruption of cognitive development showed the most severe symptoms after diagnosis and were cognitively impaired. This subgroup had the highest schizophrenia PGSs and had disadvantageous cognitive PGSs relative to control subjects and cognitively stable individuals. Individuals showing preadolescent impairment in cognitive and academic performance and poor adult outcome exhibited a generalized PGS disadvantage relative to control subjects and were the only subgroup to differ significantly in education and ADHD PGSs. CONCLUSIONS Subgroups derived from patterns of premorbid and current IQ showed different premorbid and clinical characteristics, which converged with broad genetic profiles. Simultaneous analysis of multiple PGSs may contribute to useful clinical stratification in schizophrenia.
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Affiliation(s)
- Dwight Dickinson
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, NIH
| | - Sofia R. Zaidman
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, NIH
| | - Evan J. Giangrande
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, NIH
| | - Daniel P. Eisenberg
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, NIH
| | - Michael D. Gregory
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, NIH
| | - Karen F. Berman
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, NIH
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16
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Richards AL, Pardiñas AF, Frizzati A, Tansey KE, Lynham AJ, Holmans P, Legge SE, Savage JE, Agartz I, Andreassen OA, Blokland GAM, Corvin A, Cosgrove D, Degenhardt F, Djurovic S, Espeseth T, Ferraro L, Gayer-Anderson C, Giegling I, van Haren NE, Hartmann AM, Hubert JJ, Jönsson EG, Konte B, Lennertz L, Olde Loohuis LM, Melle I, Morgan C, Morris DW, Murray RM, Nyman H, Ophoff RA, van Os J, Petryshen TL, Quattrone D, Rietschel M, Rujescu D, Rutten BPF, Streit F, Strohmaier J, Sullivan PF, Sundet K, Wagner M, Escott-Price V, Owen MJ, Donohoe G, O’Donovan MC, Walters JTR. The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia. Schizophr Bull 2020; 46:336-344. [PMID: 31206164 PMCID: PMC7442352 DOI: 10.1093/schbul/sbz061] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases. METHODS We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases. RESULTS PRS for both population IQ (P = 4.39 × 10-28) and EA (P = 1.27 × 10-26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS. CONCLUSIONS Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors.
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Affiliation(s)
- Alexander L Richards
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Aura Frizzati
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Katherine E Tansey
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Amy J Lynham
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Peter Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Legge
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Jeanne E Savage
- Complex Trait Genetics Lab, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
| | - Ole A Andreassen
- CoE NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gabriella A M Blokland
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands,Department of Psychiatry, Harvard Medical School, Boston, MA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland
| | - Donna Cosgrove
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging and Cognitive Genomics Center, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Franziska Degenhardt
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany,Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Srdjan Djurovic
- CoE NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Thomas Espeseth
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Laura Ferraro
- Department of Experimental Biomedicine and Clinical Neuroscience, University of Palermo, Palermo, Italy
| | - Charlotte Gayer-Anderson
- Department of Health Service and Population Research, Institute of Psychiatry, King’s College London, London, UK
| | - Ina Giegling
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Neeltje E van Haren
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands,Department of Child and Adolescent Psychiatry/Psychology, Sophia Children’s Hospital, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Annette M Hartmann
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - John J Hubert
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Erik G Jönsson
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden,CoE NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Bettina Konte
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Leonhard Lennertz
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA
| | - Ingrid Melle
- CoE NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Craig Morgan
- National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College, London, UK
| | - Derek W Morris
- Centre for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
| | - Robin M Murray
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Håkan Nyman
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Roel A Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA
| | | | - Jim van Os
- Department of Psychiatry and Medical Psychology, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands,Department of Psychiatry, Utrecht University Medical Centre, Utrecht, The Netherlands,King’s Health Partners Department of Psychosis Studies, King’s College London, Institute of Psychiatry, London, UK
| | | | | | - Tracey L Petryshen
- Department of Psychiatry, Harvard Medical School, Boston, MA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Diego Quattrone
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Dan Rujescu
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, South Limburg Mental Health Research and Teaching Network, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Fabian Streit
- Central Institute of Mental Health, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany
| | - Jana Strohmaier
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Patrick F Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Kjetil Sundet
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Michael Wagner
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Valentina Escott-Price
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
| | - Michael C O’Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK,To whom correspondence should be addressed; tel: 44 (0)29-20688-434, fax: 44 (0)29-20687-068, e-mail:
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Frimodt-Møller KE, Møllegaard Jepsen JR, Feldt-Rasmussen U, Krogh J. Hippocampal Volume, Cognitive Functions, Depression, Anxiety, and Quality of Life in Patients With Cushing Syndrome. J Clin Endocrinol Metab 2019; 104:4563-4577. [PMID: 31215997 DOI: 10.1210/jc.2019-00749] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 06/13/2019] [Indexed: 12/29/2022]
Abstract
CONTEXT Cushing syndrome (CS) is associated with hippocampal atrophy and psychopathology. OBJECTIVE The primary objective of this systematic review was to assess hippocampal volume (HV) in patients with CS. The secondary objectives were to assess patients' cognitive functioning, depressive and anxiety symptoms, and quality of life. DATA SOURCES PubMed, Embase, Cochrane, LILACs, and Scopus databases were searched for relevant studies until 1 May 2019. STUDY SELECTION Case-control studies comparing patients with CS with healthy control subjects, or studies assessing patients with CS before and after surgery were included. The initial search resulted in 18 studies fulfilling the inclusion criteria. DATA EXTRACTION Data extraction regarding all outcomes was performed independently by two reviewers. Quality assessment was assessed with the Newcastle-Ottawa Scale for case-control studies. DATA SYNTHESIS Meta-analysis was performed using a random effect model. The right-side HV in patients with CS was reduced by a standard mean difference of 0.68 (95% CI, -1.12 to -0.24; P = 0.002; I2 = 0%) compared with healthy control subjects, but with no increase in HV after surgery. Patients had more depressive symptoms, impaired cognitive functions, and reduced health-related QoL (HRQoL), which all responded favorably to surgery. The data did not support the presence of anxiety in patients with CS. CONCLUSION An overall reduction of HV in patients with CS was not suggested by the study findings. However, most cognitive domains were significantly affected and responded favorably to surgery. Depressive symptoms and reduced HRQoL were present in patients with CS and improved after surgery.
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Affiliation(s)
| | - Jens Richardt Møllegaard Jepsen
- Centre for Neuropsychiatric Schizophrenia Research & Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Glostrup, Denmark
- Child and Adolescent Mental Health Centre, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark
| | - Ulla Feldt-Rasmussen
- Department of Endocrinology, Rigshospitalet, Copenhagen University, Copenhagen, Denmark
| | - Jesper Krogh
- Department of Endocrinology, Rigshospitalet, Copenhagen University, Copenhagen, Denmark
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Toulopoulou T, Zhang X, Cherny S, Dickinson D, Berman KF, Straub RE, Sham P, Weinberger DR. Polygenic risk score increases schizophrenia liability through cognition-relevant pathways. Brain 2019; 142:471-485. [PMID: 30535067 DOI: 10.1093/brain/awy279] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 09/19/2018] [Indexed: 02/02/2023] Open
Abstract
Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.
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Affiliation(s)
- Timothea Toulopoulou
- Department of Psychology, Bilkent University, Bilkent, Ankara, Turkey.,The State Key Laboratory of Brain and Cognitive Sciences, the University of Hong Kong, Hong Kong SAR, China.,Department of Psychology, the University of Hong Kong, Hong Kong SAR, China.,Department of Basic and Clinical Neuroscience, Institute of Psychiatry Psychology and Neuroscience at King's College London, London, UK
| | - Xiaowei Zhang
- Department of Psychiatry, The University of Hong Kong, Hong Kong SAR, China
| | - Stacey Cherny
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry Psychology and Neuroscience at King's College London, London, UK.,Department of Psychiatry, The University of Hong Kong, Hong Kong SAR, China
| | - Dwight Dickinson
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, USA
| | - Karen F Berman
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health, USA
| | - Richard E Straub
- Lieber Institute for Brain Development, Johns Hopkins University, USA
| | - Pak Sham
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry Psychology and Neuroscience at King's College London, London, UK.,Department of Psychiatry, The University of Hong Kong, Hong Kong SAR, China
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins University, USA.,Departments of Psychiatry, Neurology, Neuroscience, The McKusick Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Johns Hopkins University, USA
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19
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Biagianti B, Fisher M, Brandrett B, Schlosser D, Loewy R, Nahum M, Vinogradov S. Development and testing of a web-based battery to remotely assess cognitive health in individuals with schizophrenia. Schizophr Res 2019; 208:250-257. [PMID: 30733167 PMCID: PMC6544475 DOI: 10.1016/j.schres.2019.01.047] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 01/21/2019] [Accepted: 01/26/2019] [Indexed: 01/06/2023]
Abstract
Cognitive impairment in schizophrenia is often severe, enduring, and contributes significantly to chronic disability. A standardized platform for identifying cognitive impairments and measuring treatment effects in cognition is a critical aspect of comprehensive evaluation and treatment for individuals with schizophrenia. In this project, we developed and tested a suite of ten web-based, neuroscience-informed cognitive assessments that are designed to enable the interpretation of specific deficits that could signal that an individual is experiencing cognitive difficulties. The assessment suite assays speed of processing, sustained attention, executive functioning, learning and socio-affective processing in the auditory and visual modalities. We have obtained data from 283 healthy individuals who were recruited online and 104 individuals with schizophrenia who also completed formal neuropsychological testing. Our data show that the assessments 1) are acceptable and tolerable to users, with successful completion in an average of under 40 min; 2) reliably measure the distinct theoretical cognitive constructs they were designed to assess; 3) can discriminate schizophrenia patients from healthy controls with a fair degree of accuracy (AUROC > 0.70); and 4) have promising construct, convergent, and external validity. Further optimization and validation work is in progress to finalize the evaluation process prior to promoting the dissemination of these assessments in real-world settings.
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Affiliation(s)
| | | | | | - Danielle Schlosser
- Department of Psychiatry, University of California, San Francisco,Verily Life Sciences
| | - Rachel Loewy
- Department of Psychiatry, University of California, San Francisco
| | - Mor Nahum
- School of Occupational Therapy, Hebrew University of Jerusalem
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20
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Role of gamma-amino-butyric acid in the dorsal anterior cingulate in age-associated changes in cognition. Neuropsychopharmacology 2018; 43:2285-2291. [PMID: 30050047 PMCID: PMC6135795 DOI: 10.1038/s41386-018-0134-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 05/13/2018] [Accepted: 06/18/2018] [Indexed: 11/08/2022]
Abstract
GABAergic mechanisms have been shown to contribute to cognitive aging in animal models, but there is currently limited in vivo evidence to support this relationship in humans. It is also unclear whether aging is associated with changes in GABA levels measured with proton magnetic resonance spectroscopy (MRS). Spectral-editing MRS at 3 T was used to measure GABA in the dorsal anterior cingulate cortex (dACC) for a large sample of healthy volunteers (N = 229) aged 18-55. In a subset of 171 participants, age effects on several cognitive tasks were studied. We formally tested whether the MRS measures mediated the relationship between age and cognition. Robust associations of age with performance were found for the Wisconsin Card Sorting Test ([WCST], p < 0.0001). Age was also significantly associated with declining levels of GABA in the dACC (p < 0.001), and GABA levels significantly predicted WCST performance (p < 0.0004). Mediation analysis revealed that GABA in the dACC mediated the effect of age on WCST performance (p < 0.01). Other metabolites were similarly associated with age, but only GABA and creatine levels were significantly associated with WCST performance. No association with age or cognitive performance was found in a frontal white matter control region in a subset of participants. The association of GABA with WCST performance was not related to the amount of brain atrophy associated with aging as measured by the proportion of CSF, gray, and white matter in the MRS voxel. These results implicate GABAergic and possibly energetic metabolism in the dACC as mechanisms of age effects in executive function.
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21
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Lam M, Lee J, Rapisarda A, See YM, Yang Z, Lee SA, Abdul-Rashid NA, Kraus M, Subramaniam M, Chong SA, Keefe RSE. Longitudinal Cognitive Changes in Young Individuals at Ultrahigh Risk for Psychosis. JAMA Psychiatry 2018; 75:929-939. [PMID: 30046827 PMCID: PMC6142925 DOI: 10.1001/jamapsychiatry.2018.1668] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
IMPORTANCE Cognitive deficits are a key feature of risk for psychosis. Longitudinal changes in cognitive architecture may be associated with the social and occupational functioning in young people. OBJECTIVES To examine longitudinal profiles of cognition in individuals at ultrahigh risk (UHR) for psychosis, compared with healthy controls, and to investigate the association of cognition with functioning. DESIGN, SETTING, AND PARTICIPANTS This study has a multiple-group prospective design completed in 24 months and was conducted from January 1, 2009, to November 11, 2012, as part of the Longitudinal Youth at-Risk Study conducted in Singapore. Participants either were recruited from psychiatric outpatient clinics, educational institutions, and community mental health agencies or self-referred. Follow-up assessments were performed every 6 months for 2 years or until conversion to psychosis. Individuals with medical causes for psychosis, current illicit substance use, or color blindness were excluded. Data analysis was conducted from June 2014 to May 2018. MAIN OUTCOMES AND MEASURES Neuropsychological, perceptual, and social cognitive tasks; semi-structured interviews, and the Structured Clinical Interview for DSM-IV Axis I disorders were administered every 6 months. The UHR status of nonconverters, converters, remitters, and nonremitters was monitored. Cognitive domain scores and functioning were investigated longitudinally. RESULTS In total, 384 healthy controls and 173 UHR individuals between ages 14 and 29 years were evaluated prospectively. Of the 384 healthy controls, 153 (39.8%) were female and 231 (60.2%) were male with a mean (SD) age of 21.69 (3.26) years. Of the 173 individuals at UHR for psychosis, 56 (32.4%) were female and 117 (67.6%) were male with a mean (SD) age of 21.27 (3.52) years). After 24 months of follow-up, 383 healthy controls (99.7%) and 122 individuals at UHR for psychosis (70.5%) remained. Baseline cognitive deficits were associated with psychosis conversion later (mean odds ratio [OR], 1.66; combined 95% CI, 1.08-2.83; P = .04) and nonremission of UHR status (mean OR, 1.67; combined 95% CI, 1.09-2.95; P = .04). Five cognitive components-social cognition, attention, verbal fluency, general cognitive function, and perception-were obtained from principal components analysis. Longitudinal component structure change was observed in general cognitive function (maximum vertical deviation = 0.59; χ2 = 8.03; P = .01). Group-by-time interaction on general cognitive function (F = 12.23; η2 = 0.047; P < .001) and perception (F = 8.33; η2 = 0.032; P < .001) was present. Changes in attention (F = 5.65; η2 = 0.013; P = .02) and general cognitive function (F = 7.18; η2 = 0.014; P = .01) accounted for longitudinal changes in social and occupational functioning. CONCLUSIONS AND RELEVANCE Individuals in this study who met the UHR criteria appeared to demonstrate cognitive deficits, and those whose UHR status remitted were seen to recover cognitively. Cognition appeared as poor in nonremitters and appeared to be associated with poor functional outcome. This study suggests that cognitive dimensions are sensitive to the identification of young individuals at risk for psychosis and to the longitudinal course of those at highest risk.
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Affiliation(s)
- Max Lam
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health,
Singapore, Singapore,Department of General Psychiatry 1, Institute of
Mental Health, Singapore, Singapore
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health,
Singapore, Singapore,Neuroscience and Behavioural Disorders, Duke-NUS
Medical School, Singapore, Singapore
| | - Yuen Mei See
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Zixu Yang
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Sara-Ann Lee
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | | | - Michael Kraus
- Department of Psychiatry and Behavioral Sciences, Duke
University Medical Center, Durham, North Carolina
| | | | - Siow-Ann Chong
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Richard S. E. Keefe
- Department of Psychiatry and Behavioral Sciences, Duke
University Medical Center, Durham, North Carolina
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22
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Vargas T, Dean DJ, Osborne KJ, Gupta T, Ristanovic I, Ozturk S, Turner J, van Erp TGM, Mittal VA. Hippocampal Subregions Across the Psychosis Spectrum. Schizophr Bull 2018; 44:1091-1099. [PMID: 29272467 PMCID: PMC6101630 DOI: 10.1093/schbul/sbx160] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
INTRODUCTION Converging evidence suggests that hippocampal subregions subserve different functions, and are differentially affected by psychosis illness progression. Despite this fact, studies have not often studied subregions cross-sectionally across the psychosis spectrum. Furthermore, little is known about associations between subregion volumes and hippocampus-mediated cognition. METHODS A total of 222 participants (61 ultra high risk [UHR], 91 schizophrenia [SCZ], and 70 healthy volunteers) underwent a 3T MRI scan, as well as structured clinical interviews and a cognitive battery. Hippocampal subfield analysis was conducted with Freesurfer. We compared subregion volumes across groups, controlling for age, gender, and intracranial volume. We also examined associations in the UHR and SCZ groups between hippocampal subregion volumes and verbal learning, visual learning, and working memory. RESULTS We found a dose-dependent relationship such that the SCZ group showed significantly greater subfield volume reductions than the UHR group, which in turn showed significantly greater subfield volume reductions than the healthy volunteer group. We also found associations between subregion volume and cognitive performance in the visual memory, verbal memory, and working memory domains. DISCUSSION Our study examined hippocampal subregion volumes cross-sectionally in a large sample across the psychosis spectrum, as well as links with hippocampus-mediated cognitive function. Our findings suggest that hippocampal abnormalities emerge before first psychosis episode onset, and may be etiologically informative.
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Affiliation(s)
- Teresa Vargas
- Department of Psychology, Northwestern University, IL,To whom correspondence should be addressed; tel: 847-467-3880, fax: 847-491-7859, e-mail:
| | - Derek J Dean
- Department of Psychology and Neuroscience, University of Colorado Boulder
| | | | - Tina Gupta
- Department of Psychology, Northwestern University, IL
| | | | - Sekine Ozturk
- Department of Psychology, Northwestern University, IL
| | | | - Theo G M van Erp
- Psychiatry & Human Behavior Department, University of California Irvine
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23
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McCarthy NS, Badcock JC, Clark ML, Knowles EEM, Cadby G, Melton PE, Morgan VA, Blangero J, Moses EK, Glahn DC, Jablensky A. Assessment of Cognition and Personality as Potential Endophenotypes in the Western Australian Family Study of Schizophrenia. Schizophr Bull 2018; 44:908-921. [PMID: 29040798 PMCID: PMC6007328 DOI: 10.1093/schbul/sbx141] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Phenotypic heterogeneity is a major barrier to understanding the genetic architecture underlying schizophrenia. Incorporating endophenotypes is one way to reduce heterogeneity and facilitate more powerful genetic analysis. Candidate endophenotypes require systematic assessment against endophenotype criteria, and a ranking of their potential utility for genetic analysis. In this study we assess 20 cognitive and personality measures in a sample of 127 families with at least 2 cases of schizophrenia per family (n = 535) plus a set of 30 control families (n = 121) against 4 endophenotype criteria: (a) be associated with the illness but not be a part of its diagnosis, (b) be heritable, (c) co-segregate with the illness in families, and (d) be found in unaffected relatives at a higher rate than in the general population. The endophenotype ranking score (endophenotype ranking variable [ERV]) was used to rank candidate endophenotypes based on their heritability and genetic correlation with schizophrenia. Finally, we used factor analysis to explore latent factors underlying the cognitive and personality measures. Evidence for personality measures as endophenotypes was at least equivalent to that of the cognitive measures. Factor analysis indicated that personality and cognitive traits contribute to independent latent dimensions. The results suggest for this first time that a number of cognitive and personality measures are independent and informative endophenotypes. Use of these endophenotypes in genetic studies will likely improve power and facilitate novel aetiological insights.
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Affiliation(s)
- Nina S McCarthy
- Centre for Genetic Origins of Health and Disease, Faculty of Medicine, Dentistry & Health Sciences, The University of Western Australia and Faculty of Health Sciences, Curtin University, Perth, Australia
- Centre for Clinical Research in Neuropsychiatry, Division of Psychiatry, Medical School, University of Western Australia, Perth, Australia
- Cooperative Research Centre for Mental Health, Carlton South, Australia
| | - Johanna C Badcock
- Centre for Clinical Research in Neuropsychiatry, Division of Psychiatry, Medical School, University of Western Australia, Perth, Australia
- Cooperative Research Centre for Mental Health, Carlton South, Australia
| | - Melanie L Clark
- Centre for Clinical Research in Neuropsychiatry, Division of Psychiatry, Medical School, University of Western Australia, Perth, Australia
| | - Emma E M Knowles
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT
| | - Gemma Cadby
- Centre for Genetic Origins of Health and Disease, Faculty of Medicine, Dentistry & Health Sciences, The University of Western Australia and Faculty of Health Sciences, Curtin University, Perth, Australia
| | - Phillip E Melton
- Centre for Genetic Origins of Health and Disease, Faculty of Medicine, Dentistry & Health Sciences, The University of Western Australia and Faculty of Health Sciences, Curtin University, Perth, Australia
| | - Vera A Morgan
- Centre for Clinical Research in Neuropsychiatry, Division of Psychiatry, Medical School, University of Western Australia, Perth, Australia
- Neuropsychiatric Epidemiology Research Unit, Division of Psychiatry, Medical School, University of Western Australia, Perth, Australia
| | - John Blangero
- South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley, Brownsville, TX
| | - Eric K Moses
- Centre for Genetic Origins of Health and Disease, Faculty of Medicine, Dentistry & Health Sciences, The University of Western Australia and Faculty of Health Sciences, Curtin University, Perth, Australia
| | - David C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital, Hartford, CT
| | - Assen Jablensky
- Centre for Clinical Research in Neuropsychiatry, Division of Psychiatry, Medical School, University of Western Australia, Perth, Australia
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24
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Sarter M, Phillips KB. The neuroscience of cognitive-motivational styles: Sign- and goal-trackers as animal models. Behav Neurosci 2018; 132:1-12. [PMID: 29355335 DOI: 10.1037/bne0000226] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Cognitive-motivational styles describe predominant patterns of processing or biases that broadly influence human cognition and performance. Here we focus on the impact of cognitive-motivational styles on the response to cues predicting the availability of food or addictive drugs. An individual may preferably conduct an analysis of the motivational significance of reward cues, with the result that such cues per se are perceived as rewarding and worth approaching and working for. Alternatively, a propensity for a "cold" analysis of the behavioral utility of a reward cue may yield search behavior for food or drugs but not involve cue approach. Animal models for studying the neuronal mechanisms mediating such styles have originated from research concerning behavioral indices that predict differential vulnerability to addiction-like behaviors. Rats classified as sign- or goal-trackers (STs, GTs) were found to have opposed attentional biases (bottom-up or cue-driven attention vs. top-down or goal-driven attentional control) that are mediated primarily via relatively unresponsive versus elevated levels of cholinergic neuromodulation in the cortex. The capacity for cholinergic neuromodulation in STs is limited by a neuronal choline transporter (CHT) that fails to support increases in cholinergic activity. Moreover, in contrast to STs, the frontal dopamine system in GTs does not respond to the presence of drug cues and, thus, biases against cue-oriented behavior. The opponent cognitive-motivational styles that are indexed by sign- and goal-tracking bestow different cognitive-behavioral vulnerabilities that may contribute to the manifestation of a wide range of neuropsychiatric disorders. (PsycINFO Database Record
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Affiliation(s)
- Martin Sarter
- Department of Psychology and Neuroscience Program, University of Michigan
| | - Kyra B Phillips
- Department of Psychology and Neuroscience Program, University of Michigan
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25
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Dickinson D, Pratt DN, Giangrande EJ, Grunnagle M, Orel J, Weinberger DR, Callicott JH, Berman KF. Attacking Heterogeneity in Schizophrenia by Deriving Clinical Subgroups From Widely Available Symptom Data. Schizophr Bull 2018; 44:101-113. [PMID: 28369611 PMCID: PMC5768050 DOI: 10.1093/schbul/sbx039] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Previous research has identified (1) a "deficit" subtype of schizophrenia characterized by enduring negative symptoms and diminished emotionality and (2) a "distress" subtype associated with high emotionality-including anxiety, depression, and stress sensitivity. Individuals in deficit and distress categories differ sharply in development, clinical course and behavior, and show distinct biological markers, perhaps signaling different etiologies. We tested whether deficit and distress subtypes would emerge from a simple but novel data-driven subgrouping analysis, based on Positive and Negative Syndrome Scale (PANSS) negative and distress symptom dimensions, and whether subgrouping was informative regarding other facets of behavior and brain function. PANSS data, and other assessments, were available for 549 people with schizophrenia diagnoses. Negative and distress symptom composite scores were used as indicators in 2-step cluster analyses, which divided the sample into low symptom (n = 301), distress (n = 121), and deficit (n = 127) subgroups. Relative to the low-symptom group, the deficit and distress subgroups had comparably higher total PANSS symptoms (Ps < .001) and were similarly functionally impaired (eg, global functioning [GAF] Ps < .001), but showed markedly different patterns on symptom, cognitive and personality variables, among others. Initial analyses of functional magnetic resonance imaging (fMRI) data from a 182-participant subset of the full sample also suggested distinct patterns of neural recruitment during working memory. The field seeks more neuroscience-based systems for classifying psychiatric conditions, but these are inescapably behavioral disorders. More effective parsing of clinical and behavioral traits could identify homogeneous target groups for further neural system and molecular studies, helping to integrate clinical and neuroscience approaches.
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Affiliation(s)
- Dwight Dickinson
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD,To whom correspondence should be addressed; 10 Center Drive, Building 10, Room 3c-115, Bethesda, MD 20814, US; tel: 301-451-2123, fax: 301-480-7795, e-mail:
| | - Danielle N Pratt
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - Evan J Giangrande
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - MeiLin Grunnagle
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - Jennifer Orel
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - Daniel R Weinberger
- The Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD
| | - Joseph H Callicott
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - Karen F Berman
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
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26
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PKBγ/AKT3 loss-of-function causes learning and memory deficits and deregulation of AKT/mTORC2 signaling: Relevance for schizophrenia. PLoS One 2017; 12:e0175993. [PMID: 28467426 PMCID: PMC5414975 DOI: 10.1371/journal.pone.0175993] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 04/04/2017] [Indexed: 12/17/2022] Open
Abstract
Psychiatric genetic studies have identified genome-wide significant loci for schizophrenia. The AKT3/1q44 locus is a principal risk region and gene-network analyses identify AKT3 polymorphisms as a constituent of several neurobiological pathways relevant to psychiatric risk; the neurobiological mechanisms remain unknown. AKT3 shows prenatal enrichment during human neocortical development and recurrent copy number variations involving the 1q43-44 locus are associated with cortical malformations and intellectual disability, implicating an essential role in early brain development. Here, we investigated the role of AKT3 as it relates to aspects of learning and memory and behavioral function, relevant to schizophrenia and cognitive disability, utilizing a novel murine model of Akt3 genetic deficiency. Akt3 heterozygous (Akt3-/+) or null mice (Akt3-/-) were assessed in a comprehensive test battery. Brain biochemical studies were conducted to assess the impact of Akt3 deficiency on cortical Akt/mTOR signaling. Akt3-/+ and Akt3-/- mice exhibited selective deficits of temporal order discrimination and spatial memory, tasks critically dependent on intact prefrontal-hippocampal circuitry, but showed normal prepulse inhibition, fear conditioned learning, memory for novel objects and social function. Akt3 loss-of-function, reduced brain size and dramatically impaired cortical Akt Ser473 activation in an allele-dose dependent manner. Such changes were observed in the absence of altered Akt1 or Akt2 protein expression. Concomitant reduction of the mTORC2 complex proteins, Rictor and Sin1 identifies a potential mechanism. Our findings provide novel insight into the neurodevelopmental role of Akt3, identify a non-redundant role for Akt3 in the development of prefrontal cortical-mediated cognitive function and show that Akt3 is potentially the dominant regulator of AKT/mTOR signaling in brain.
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27
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Trampush JW, Yang MLZ, Yu J, Knowles E, Davies G, Liewald DC, Starr JM, Djurovic S, Melle I, Sundet K, Christoforou A, Reinvang I, DeRosse P, Lundervold AJ, Steen VM, Espeseth T, Räikkönen K, Widen E, Palotie A, Eriksson JG, Giegling I, Konte B, Roussos P, Giakoumaki S, Burdick KE, Payton A, Ollier W, Horan M, Chiba-Falek O, Attix DK, Need AC, Cirulli ET, Voineskos AN, Stefanis NC, Avramopoulos D, Hatzimanolis A, Arking DE, Smyrnis N, Bilder RM, Freimer NA, Cannon TD, London E, Poldrack RA, Sabb FW, Congdon E, Conley ED, Scult MA, Dickinson D, Straub RE, Donohoe G, Morris D, Corvin A, Gill M, Hariri AR, Weinberger DR, Pendleton N, Bitsios P, Rujescu D, Lahti J, Le Hellard S, Keller MC, Andreassen OA, Deary IJ, Glahn DC, Malhotra AK, Lencz T. GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium. Mol Psychiatry 2017; 22:336-345. [PMID: 28093568 PMCID: PMC5322272 DOI: 10.1038/mp.2016.244] [Citation(s) in RCA: 136] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Revised: 10/30/2016] [Accepted: 11/03/2016] [Indexed: 01/12/2023]
Abstract
The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.
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Affiliation(s)
- J W Trampush
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - M L Z Yang
- Institute of Mental Health, Singapore, Singapore
| | - J Yu
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - E Knowles
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - S Djurovic
- Department of Medical Genetics, Oslo University Hospital, University of Bergen, Oslo, Norway,NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway
| | - I Melle
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - K Sundet
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Psychology, University of Oslo, Oslo, Norway
| | - A Christoforou
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - I Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - P DeRosse
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - A J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - V M Steen
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - T Espeseth
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Psychology, University of Oslo, Oslo, Norway
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - E Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - A Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland,Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK,Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland
| | - J G Eriksson
- National Institute for Health and Welfare, Helsinki, Finland,Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland,Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland,Folkhälsan Research Centre, Helsinki, Finland
| | - I Giegling
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - B Konte
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - P Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Mental Illness Research, Education, and Clinical Center (VISN 3), James J. Peters VA Medical Center, Bronx, NY, USA
| | - S Giakoumaki
- Department of Psychology, University of Crete, Rethymno, Greece
| | - K E Burdick
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Mental Illness Research, Education, and Clinical Center (VISN 3), James J. Peters VA Medical Center, Bronx, NY, USA
| | - A Payton
- Manchester Centre for Audiology and Deafness, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK,Division of Evolution and Genomic Sciences, School of Biological Sciences, The University of Manchester, Manchester, UK
| | - W Ollier
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK
| | - M Horan
- Manchester Medical School, Institute of Brain, Behaviour, and Mental Health, University of Manchester, Manchester, UK
| | - O Chiba-Falek
- Department of Neurology, Bryan Alzheimer's Disease Research Center, and Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, USA
| | - D K Attix
- Department of Neurology, Bryan Alzheimer's Disease Research Center, and Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, USA,Division of Medical Psychology, Department of Neurology, Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - A C Need
- Division of Brain Sciences, Department of Medicine, Imperial College, London, UK
| | - E T Cirulli
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - A N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
| | - N C Stefanis
- Department of Psychiatry, University of Athens School of Medicine, Eginition Hospital, Athens, Greece,University Mental Health Research Institute, Athens, Greece,Neurobiology Research Institute, Theodor Theohari Cozzika Foundation, Athens, Greece
| | - D Avramopoulos
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA,Department of Psychiatry and McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - A Hatzimanolis
- Department of Psychiatry, University of Athens School of Medicine, Eginition Hospital, Athens, Greece,University Mental Health Research Institute, Athens, Greece,Neurobiology Research Institute, Theodor Theohari Cozzika Foundation, Athens, Greece
| | - D E Arking
- Department of Psychiatry and McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - N Smyrnis
- Department of Psychiatry, University of Athens School of Medicine, Eginition Hospital, Athens, Greece,University Mental Health Research Institute, Athens, Greece
| | - R M Bilder
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - N A Freimer
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - T D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA
| | - E London
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | - R A Poldrack
- Department of Psychology, Stanford University, Palo Alto, CA, USA
| | - F W Sabb
- Robert and Beverly Lewis Center for Neuroimaging, University of Oregon, Eugene, OR, USA
| | - E Congdon
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA
| | | | - M A Scult
- Department of Psychology & Neuroscience, Laboratory of NeuroGenetics, Duke University, Durham, NC, USA
| | - D Dickinson
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA
| | - R E Straub
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - G Donohoe
- Department of Psychology, National University of Ireland, Galway, Ireland
| | - D Morris
- Department of Psychiatry, Neuropsychiatric Genetics Research Group, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - A Corvin
- Department of Psychiatry, Neuropsychiatric Genetics Research Group, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - M Gill
- Department of Psychiatry, Neuropsychiatric Genetics Research Group, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - A R Hariri
- Department of Psychology & Neuroscience, Laboratory of NeuroGenetics, Duke University, Durham, NC, USA
| | - D R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - N Pendleton
- Centre for Integrated Genomic Medical Research, Institute of Population Health, University of Manchester, Manchester, UK,Manchester Medical School, Institute of Brain, Behaviour, and Mental Health, University of Manchester, Manchester, UK
| | - P Bitsios
- Department of Psychiatry and Behavioral Sciences, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - D Rujescu
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle, Germany
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland,Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - S Le Hellard
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - M C Keller
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO, USA
| | - O A Andreassen
- NORMENT, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - A K Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA
| | - T Lencz
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA,Division of Psychiatry Research, Zucker Hillside Hospital, 75-59 263rd Street, Glen Oaks, NY 11004, USA. E-mail:
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28
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Pu S, Nakagome K, Itakura M, Iwata M, Nagata I, Kaneko K. Association of fronto-temporal function with cognitive ability in schizophrenia. Sci Rep 2017; 7:42858. [PMID: 28205609 PMCID: PMC5311872 DOI: 10.1038/srep42858] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Accepted: 01/18/2017] [Indexed: 01/13/2023] Open
Abstract
Deficits in neuropsychological performance are common in schizophrenia, but their relationship with the fronto-temporal functional abnormalities associated with this condition remains unclear. We explored the relationship between neuropsychological performance as measured using the Brief Assessment of Cognition in Schizophrenia (BACS) and the Social Cognition Screening Questionnaire theory of mind (ToM) subscale and fronto-temporal function in 23 patients with schizophrenia and 23 age- and gender-matched healthy controls (HCs), using 52-channel near-infrared spectroscopy (NIRS). Regional hemodynamic changes were significantly smaller in the schizophrenia group than in the HCs group in the ventro-lateral prefrontal cortex and the anterior part of the temporal cortex (VLPFC/aTC) and dorso-lateral prefrontal cortex and frontopolar cortex (DLPFC/FPC) regions. To dissect the effect of variance in BACS cognitive domains from the relationship between ToM function and fronto-temporal function, we performed additional partial correlation analyses between ToM and NIRS data, using BACS composite score as a control variable. The correlation between ToM and NIRS data remained significant only in the DLPFC/FPC region. This finding is important to models of recovery, as it suggests that intervention programs focusing on enhancing fronto-temporal function may have a greater impact on social and occupational outcomes than traditional rehabilitation programs focusing on neuropsychological performance.
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Affiliation(s)
- Shenghong Pu
- Division of Neuropsychiatry, Department of Brain and Neuroscience, Tottori University Faculty of Medicine: 36-1 Nishi-cho, Yonago, Tottori 683-8504, Japan
| | - Kazuyuki Nakagome
- National Center of Neurology and Psychiatry: 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551 Japan
| | - Masashi Itakura
- Division of Neuropsychiatry, Department of Brain and Neuroscience, Tottori University Faculty of Medicine: 36-1 Nishi-cho, Yonago, Tottori 683-8504, Japan
| | - Masaaki Iwata
- Division of Neuropsychiatry, Department of Brain and Neuroscience, Tottori University Faculty of Medicine: 36-1 Nishi-cho, Yonago, Tottori 683-8504, Japan
| | - Izumi Nagata
- Division of Neuropsychiatry, Department of Brain and Neuroscience, Tottori University Faculty of Medicine: 36-1 Nishi-cho, Yonago, Tottori 683-8504, Japan
| | - Koichi Kaneko
- Division of Neuropsychiatry, Department of Brain and Neuroscience, Tottori University Faculty of Medicine: 36-1 Nishi-cho, Yonago, Tottori 683-8504, Japan
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29
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Diffusion-weighted imaging uncovers likely sources of processing-speed deficits in schizophrenia. Proc Natl Acad Sci U S A 2016; 113:13504-13509. [PMID: 27834215 DOI: 10.1073/pnas.1608246113] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Schizophrenia, a devastating psychiatric illness with onset in the late teens to early 20s, is thought to involve disrupted brain connectivity. Functional and structural disconnections of cortical networks may underlie various cognitive deficits, including a substantial reduction in the speed of information processing in schizophrenia patients compared with controls. Myelinated white matter supports the speed of electrical signal transmission in the brain. To examine possible neuroanatomical sources of cognitive deficits, we used a comprehensive diffusion-weighted imaging (DWI) protocol and characterized the white matter diffusion signals using diffusion kurtosis imaging (DKI) and permeability-diffusivity imaging (PDI) in patients (n = 74), their nonill siblings (n = 41), and healthy controls (n = 113). Diffusion parameters that showed significant patient-control differences also explained the patient-control differences in processing speed. This association was also found for the nonill siblings of the patients. The association was specific to processing-speed abnormality but not specific to working memory abnormality or psychiatric symptoms. Our findings show that advanced diffusion MRI in white matter may capture microstructural connectivity patterns and mechanisms that govern the association between a core neurocognitive measure-processing speed-and neurobiological deficits in schizophrenia that are detectable with in vivo brain scans. These non-Gaussian diffusion white matter metrics are promising surrogate imaging markers for modeling cognitive deficits and perhaps, guiding treatment development in schizophrenia.
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30
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González-Pinto A, González-Ortega I, Alberich S, Ruiz de Azúa S, Bernardo M, Bioque M, Cabrera B, Corripio I, Arango C, Lobo A, Sánchez-Torres AM, Cuesta MJ. Opposite Cannabis-Cognition Associations in Psychotic Patients Depending on Family History. PLoS One 2016; 11:e0160949. [PMID: 27513670 PMCID: PMC4981356 DOI: 10.1371/journal.pone.0160949] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 07/27/2016] [Indexed: 11/18/2022] Open
Abstract
The objective of this study is to investigate cognitive performance in a first-episode psychosis sample, when stratifying the interaction by cannabis use and familial or non-familial psychosis. Hierarchical-regression models were used to analyse this association in a sample of 268 first-episode psychosis patients and 237 controls. We found that cannabis use was associated with worse working memory, regardless of family history. However, cannabis use was clearly associated with worse cognitive performance in patients with no family history of psychosis, in cognitive domains including verbal memory, executive function and global cognitive index, whereas cannabis users with a family history of psychosis performed better in these domains. The main finding of the study is that there is an interaction between cannabis use and a family history of psychosis in the areas of verbal memory, executive function and global cognition: that is, cannabis use is associated with a better performance in patients with a family history of psychosis and a worse performance in those with no family history of psychosis. In order to confirm this hypothesis, future research should explore the actual expression of the endocannabinoid system in patients with and without a family history of psychosis.
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Affiliation(s)
- Ana González-Pinto
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Araba University Hospital, University of the Basque Country, Vitoria, Spain
| | - Itxaso González-Ortega
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Araba University Hospital, University of the Basque Country, Vitoria, Spain
| | - Susana Alberich
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Araba University Hospital, University of the Basque Country, Vitoria, Spain
| | - Sonia Ruiz de Azúa
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Araba University Hospital, University of the Basque Country, Vitoria, Spain
| | - Miguel Bernardo
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, Barcelona, Spain
- Department of Psychiatry and Clinical Psychobiology, University of Barcelona. Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Miquel Bioque
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, Barcelona, Spain
| | - Bibiana Cabrera
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, Barcelona, Spain
| | - Iluminada Corripio
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Institut d'Investigació Biomèdica-Sant Pau (IIB-SANT PAU), Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Celso Arango
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- Child and Adolescent Psychiatry Department. Gregorio Marañón General University Hospital. School of Medicine, Universidad Complutense, IiSGM, Madrid, Spain
| | - Antonio Lobo
- Centre for Biomedical Research in the Mental Health Network (CIBERSAM), Madrid, Spain
- University of Zaragoza, Zaragoza, Spain
- Aragon Institute for Health Sciences (IIS Aragón), Zaragoza, Spain
| | - Ana M. Sánchez-Torres
- Department of Psychiatry, Navarre Hospital Complex, Pamplona, Spain. IdiSNA, Navarre Institute for Health Research, Pamplona, Spain
| | - Manuel J. Cuesta
- Department of Psychiatry, Navarre Hospital Complex, Pamplona, Spain. IdiSNA, Navarre Institute for Health Research, Pamplona, Spain
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31
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Haring L, Müürsepp A, Mõttus R, Ilves P, Koch K, Uppin K, Tarnovskaja J, Maron E, Zharkovsky A, Vasar E, Vasar V. Cortical thickness and surface area correlates with cognitive dysfunction among first-episode psychosis patients. Psychol Med 2016; 46:2145-2155. [PMID: 27269478 DOI: 10.1017/s0033291716000684] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
BACKGROUND In studies using magnetic resonance imaging (MRI), some have reported specific brain structure-function relationships among first-episode psychosis (FEP) patients, but findings are inconsistent. We aimed to localize the brain regions where cortical thickness (CTh) and surface area (cortical area; CA) relate to neurocognition, by performing an MRI on participants and measuring their neurocognitive performance using the Cambridge Neuropsychological Test Automated Battery (CANTAB), in order to investigate any significant differences between FEP patients and control subjects (CS). METHOD Exploration of potential correlations between specific cognitive functions and brain structure was performed using CANTAB computer-based neurocognitive testing and a vertex-by-vertex whole-brain MRI analysis of 63 FEP patients and 30 CS. RESULTS Significant correlations were found between cortical parameters in the frontal, temporal, cingular and occipital brain regions and performance in set-shifting, working memory manipulation, strategy usage and sustained attention tests. These correlations were significantly dissimilar between FEP patients and CS. CONCLUSIONS Significant correlations between CTh and CA with neurocognitive performance were localized in brain areas known to be involved in cognition. The results also suggested a disrupted structure-function relationship in FEP patients compared with CS.
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Affiliation(s)
- L Haring
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
| | - A Müürsepp
- Radiology Clinic of Tartu University Hospital,Tartu,Estonia
| | - R Mõttus
- Department of Psychology,University of Edinburgh,Edinburgh,UK
| | - P Ilves
- Radiology Clinic of Tartu University Hospital,Tartu,Estonia
| | - K Koch
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
| | - K Uppin
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
| | - J Tarnovskaja
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
| | - E Maron
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
| | - A Zharkovsky
- Department of Pharmacology and Translational Medicine,University of Tartu,Tartu,Estonia
| | - E Vasar
- Centre of Excellence for Translational Medicine,University of Tartu,Tartu,Estonia
| | - V Vasar
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
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32
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Jewsbury PA, Bowden SC, Duff K. The Cattell–Horn–Carroll Model of Cognition for Clinical Assessment. JOURNAL OF PSYCHOEDUCATIONAL ASSESSMENT 2016. [DOI: 10.1177/0734282916651360] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The Cattell–Horn–Carroll (CHC) model is a comprehensive model of the major dimensions of individual differences that underlie performance on cognitive tests. Studies evaluating the generality of the CHC model across test batteries, age, gender, and culture were reviewed and found to be overwhelmingly supportive. However, less research is available to evaluate the CHC model for clinical assessment. The CHC model was shown to provide good to excellent fit in nine high-quality data sets involving popular neuropsychological tests, across a range of clinically relevant populations. Executive function tests were found to be well represented by the CHC constructs, and a discrete executive function factor was found not to be necessary. The CHC model could not be simplified without significant loss of fit. The CHC model was supported as a paradigm for cognitive assessment, across both healthy and clinical populations and across both nonclinical and neuropsychological tests. The results have important implications for theoretical modeling of cognitive abilities, providing further evidence for the value of the CHC model as a basis for a common taxonomy across test batteries and across areas of assessment.
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Affiliation(s)
| | - Stephen C. Bowden
- The University of Melbourne, Parkville, Australia
- St Vincent’s Hospital, Melbourne, Australia
| | - Kevin Duff
- University of Utah, Salt Lake City, UT, USA
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33
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Fujino H, Sumiyoshi C, Sumiyoshi T, Yasuda Y, Yamamori H, Ohi K, Fujimoto M, Hashimoto R, Takeda M, Imura O. Predicting employment status and subjective quality of life in patients with schizophrenia. Schizophr Res Cogn 2016; 3:20-25. [PMID: 28740804 PMCID: PMC5506698 DOI: 10.1016/j.scog.2015.10.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Revised: 10/09/2015] [Accepted: 10/15/2015] [Indexed: 11/16/2022]
Abstract
Although impaired social functioning, particularly poor employment status, is a cardinal feature of patients with schizophrenia and leads to decreased quality of life (QOL), few studies have addressed the relationship between these two clinical issues. The aim of this study was to determine whether employment status predicts subjective QOL and to evaluate a model in which functional capacity mediates the relationship between general cognitive performance and employment status. Ninety-three patients with schizophrenia were administered a comprehensive battery of cognitive tests, the UCSD Performance-based Skills Assessment-Brief version (UPSA-B), the Social Functioning Scale (SFS), and the Subjective Quality of Life Scale (SQLS). First, we evaluated a model for predicting the employment/occupation subscale score of the SFS using path analysis, and the model fitted well (χ2 (4) = 3.6, p = 0.46; CFI = 1.0; RMSEA < 0.001, with 90% CIs: 0-0.152). Employment status was predicted by negative symptoms and functional capacity, which was in turn predicted by general cognitive performance. Second, we added subjective QOL to this model. In a final path model, QOL was predicted by negative symptoms and employment status. This model also satisfied good fit criteria (χ2 (7) = 10.3, p = 0.17; CFI = 0.987; RMSEA = 0.072, with 90% CIs: 0-0.159). The UPSA-B and SFS scores were moderately correlated with most measures of cognitive performance. These results support the notion that better employment status enhances subjective QOL in patients with schizophrenia.
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Affiliation(s)
- Haruo Fujino
- Graduate School of Human Sciences, Osaka University, 1-2 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Chika Sumiyoshi
- Faculty of Human Development and Culture, Fukushima University, 1 Kanayagawa, Fukushima, Fukushima 960-1296, Japan
| | - Tomiki Sumiyoshi
- Department of Clinical Epidemiology, Translational Medical Center, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashimachi, Kodaira, Tokyo 187-8551, Japan
| | - Yuka Yasuda
- Department of Psychiatry, Osaka University Graduate School of Medicine, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Hidenaga Yamamori
- Department of Psychiatry, Osaka University Graduate School of Medicine, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Kazutaka Ohi
- Department of Psychiatry, Osaka University Graduate School of Medicine, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Michiko Fujimoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Ryota Hashimoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Masatoshi Takeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, D3, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Osamu Imura
- Graduate School of Human Sciences, Osaka University, 1-2 Yamadaoka, Suita, Osaka 565-0871, Japan
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34
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Testing relationships between firm size and perceptions of growth and profitability: An investigation into the practices of Australian ICT SMEs. JOURNAL OF MANAGEMENT & ORGANIZATION 2016. [DOI: 10.1017/jmo.2015.57] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
AbstractGibrat’s Law mandates the independence of firm size and growth, while the resource-based view of the firm implies a positive relationship between firm size and profits, to be concluded in a profit–growth trade-off. Empirical studies of entrepreneurial success however, have demonstrated firms’ ability to reach a state of high growth and profitability, despite the trade-offs encapsulated within the profit–growth nexus. Upon assessing the relationships between past profitability, current firm growth and size in Australian ICT SMEs, results demonstrate positive relationships between all three indicators. This suggests that profitability can be considered the most important precursor of entrepreneurial success, and also that successful businesses do not suffer from the trade-offs implied by theory.
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35
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Memory systems in schizophrenia: Modularity is preserved but deficits are generalized. Schizophr Res 2015; 168:223-30. [PMID: 26299707 PMCID: PMC4591239 DOI: 10.1016/j.schres.2015.08.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Revised: 08/06/2015] [Accepted: 08/10/2015] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Schizophrenia patients exhibit impaired working and episodic memory, but this may represent generalized impairment across memory modalities or performance deficits restricted to particular memory systems in subgroups of patients. Furthermore, it is unclear whether deficits are unique from those associated with other disorders. METHOD Healthy controls (n=1101) and patients with schizophrenia (n=58), bipolar disorder (n=49) and attention-deficit-hyperactivity-disorder (n=46) performed 18 tasks addressing primarily verbal and spatial episodic and working memory. Effect sizes for group contrasts were compared across tasks and the consistency of subjects' distributional positions across memory domains was measured. RESULTS Schizophrenia patients performed poorly relative to the other groups on every test. While low to moderate correlation was found between memory domains (r=.320), supporting modularity of these systems, there was limited agreement between measures regarding each individual's task performance (ICC=.292) and in identifying those individuals falling into the lowest quintile (kappa=0.259). A general ability factor accounted for nearly all of the group differences in performance and agreement across measures in classifying low performers. CONCLUSIONS Pathophysiological processes involved in schizophrenia appear to act primarily on general abilities required in all tasks rather than on specific abilities within different memory domains and modalities. These effects represent a general shift in the overall distribution of general ability (i.e., each case functioning at a lower level than they would have if not for the illness), rather than presence of a generally low-performing subgroup of patients. There is little evidence that memory impairments in schizophrenia are shared with bipolar disorder and ADHD.
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Executive functioning in schizophrenia: Unique and shared variance with measures of fluid intelligence. Brain Cogn 2015; 99:57-67. [DOI: 10.1016/j.bandc.2015.07.009] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 07/26/2015] [Accepted: 07/30/2015] [Indexed: 01/10/2023]
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Cellard C, Rouleau N, Moreau I, Gilbert E, Paccalet T, Roy MA, Jomphe V, Mérette C, Maziade M. Cognitive structure from childhood to adulthood in kindreds densely affected by schizophrenia and bipolar disorder. Psychiatry Res 2015; 229:101-8. [PMID: 26233828 DOI: 10.1016/j.psychres.2015.07.063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2014] [Revised: 07/09/2015] [Accepted: 07/22/2015] [Indexed: 10/23/2022]
Abstract
The developmental aspects of cognitive structures from childhood until adulthood and across different levels of risk for psychopathology have been little studied. The aim of the current study was to explore the cognitive factorial structure in subsamples from highly familial and densely affected kindreds of schizophrenia and bipolar disorder - i.e. affected adult members, non-affected adult members and high-risk youth. The same neuropsychological battery was administered in a sample of 480 participants: schizophrenia and bipolar patients (n=51), young high-risk offspring (n=61), non-affected adult relatives of patients (n=96), and controls (n=272). Exploratory Factorial Analysis was performed in the control sample and yielded a 5-factor solution: verbal comprehension, processing speed/working memory, visual learning and memory, verbal learning and memory, reasoning and problem solving. Confirmatory factor analysis indicated that the hierarchical 5-factor solution was well suited for the young high-risk offspring, the non-affected adult relatives of patient and the patients. A hierarchical model with a "g" factor was a good fit for all subsamples. These results suggest that cognitive impairments may aggregate in highly familial individuals.
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Affiliation(s)
- Caroline Cellard
- Université Laval, Québec, Québec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada.
| | - Nancie Rouleau
- Université Laval, Québec, Québec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
| | - Isabel Moreau
- Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
| | - Elsa Gilbert
- Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
| | - Thomas Paccalet
- Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
| | - Marc-André Roy
- Université Laval, Québec, Québec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
| | - Valérie Jomphe
- Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
| | - Chantal Mérette
- Université Laval, Québec, Québec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
| | - Michel Maziade
- Université Laval, Québec, Québec, Canada; Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Québec, Canada
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Haring L, Mõttus R, Koch K, Trei M, Maron E. Factorial validity, measurement equivalence and cognitive performance of the Cambridge Neuropsychological Test Automated Battery (CANTAB) between patients with first-episode psychosis and healthy volunteers. Psychol Med 2015; 45:1919-1929. [PMID: 25544472 DOI: 10.1017/s0033291714003018] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND The purpose of this study was to use selected Cambridge Neuropsychological Test Automated Battery (CANTAB) tests to examine the dimensional structure of cognitive dysfunction in first episode of psychosis (FEP) patients compared with cognition in healthy subjects. METHOD A total of 109 FEP patients and 96 healthy volunteers were administered eight CANTAB tests of cognitive function. Principal components analysis (PCA) was used to estimate dimensionality within the test results. The dimensions identified by the PCA were assumed to reflect underlying cognitive traits. The plausibility of latent factor models was estimated using confirmatory factor analysis (CFA). Multi-group CFA (MGCFA) was used to test for measurement invariance of factors between groups. The nature and severity of cognitive deficits amongst patients as opposed to controls were evaluated using a general linear model. RESULTS Amongst subjects PCA identified two underlying cognitive traits: (i) a broad cognitive domain; (ii) attention/memory and executive function domains. Corresponding CFA models were built that fitted data well for both FEP patients and healthy volunteers. As in MGCFA latent variables appeared differently defined in patient and control groups, differences had to be ascribed using subtest scores rather than their aggregates. At subtest score level the patients performed significantly worse than healthy subjects in all comparisons (p < 0.001). CONCLUSIONS Results of this study demonstrate that the structure of underlying cognitive abilities as measured by a selection of CANTAB tests is not the same for healthy individuals and FEP patients, with patients displaying widespread cognitive impairment.
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Affiliation(s)
- L Haring
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
| | - R Mõttus
- Department of Psychology,University of Edinburgh,Edinburgh,UK
| | - K Koch
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
| | - M Trei
- Department of Psychology,University of Tartu,Tartu,Estonia
| | - E Maron
- Psychiatry Clinic of Tartu University Hospital,Tartu,Estonia
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McCleery A, Green MF, Hellemann GS, Baade LE, Gold JM, Keefe RS, Kern RS, Mesholam-Gately RI, Seidman LJ, Subotnik KL, Ventura J, Nuechterlein KH. Latent structure of cognition in schizophrenia: a confirmatory factor analysis of the MATRICS Consensus Cognitive Battery (MCCB). Psychol Med 2015; 45:2657-2666. [PMID: 25916421 PMCID: PMC4523424 DOI: 10.1017/s0033291715000641] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND The number of separable cognitive dimensions in schizophrenia has been debated. Guided by the extant factor analytic literature, the NIMH Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative selected seven cognitive domains relevant to treatment studies in schizophrenia: speed of processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. These domains are assessed in the MATRICS Consensus Cognitive Battery (MCCB). The aim of this study was to conduct a confirmatory factor analysis (CFA) of the beta battery of the MCCB to compare the fit of the MATRICS consensus seven-domain model to other models in the current literature on cognition in schizophrenia. METHOD Using data from 281 schizophrenia outpatients, we compared the seven correlated factors model with alternative models. Specifically, we compared the 7-factor model to (a) a single-factor model, (b) a three correlated factors model including speed of processing, working memory, and general cognition, and (c) a hierarchical model in which seven first-order factors loaded onto a second-order general cognitive factor. RESULTS Multiple fit indices indicated the seven correlated factors model was the best fit for the data and provided significant improvement in model fit beyond the comparison models. CONCLUSIONS These results support the assessment of these seven cognitive dimensions in clinical trials of interventions to improve cognition in schizophrenia. Because these cognitive factors are separable to some degree, it is plausible that specific interventions may have differential effects on the domains.
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Affiliation(s)
- Amanda McCleery
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
- Department of Veterans Affairs VISN 22 Mental Illness Research, Education, and Clinical Center, Los Angeles, CA
| | - Gerhard S. Hellemann
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Lyle E. Baade
- University of Kansas School of Medicine at Wichita, Wichita, KS
| | - James M. Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland Baltimore, School of Medicine, Baltimore, MD
| | - Richard S.E. Keefe
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC
| | - Robert S. Kern
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
- Department of Veterans Affairs VISN 22 Mental Illness Research, Education, and Clinical Center, Los Angeles, CA
| | - Raquelle I. Mesholam-Gately
- Massachusetts Mental Health Center, Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Department of Psychiatry, Harvard Medical School, Boston, MA
| | - Larry J. Seidman
- Massachusetts Mental Health Center, Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Department of Psychiatry, Harvard Medical School, Boston, MA
- Massachusetts General Hospital, Boston, MA
| | - Kenneth L. Subotnik
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Joseph Ventura
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA
- UCLA Department of Psychology, Los Angeles, CA
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Factor structure and heritability of endophenotypes in schizophrenia: findings from the Consortium on the Genetics of Schizophrenia (COGS-1). Schizophr Res 2015; 163:73-9. [PMID: 25682549 PMCID: PMC5944296 DOI: 10.1016/j.schres.2015.01.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 01/14/2015] [Accepted: 01/17/2015] [Indexed: 11/23/2022]
Abstract
BACKGROUND Although many endophenotypes for schizophrenia have been studied individually, few studies have examined the extent to which common neurocognitive and neurophysiological measures reflect shared versus unique endophenotypic factors. It may be possible to distill individual endophenotypes into composite measures that reflect dissociable, genetically informative elements. METHODS The first phase of the Consortium on the Genetics of Schizophrenia (COGS-1) is a multisite family study that collected neurocognitive and neurophysiological data between 2003 and 2008. For these analyses, participants included schizophrenia probands (n=83), their nonpsychotic siblings (n=151), and community comparison subjects (n=209) with complete data on a battery of 12 neurocognitive tests (assessing domains of working memory, declarative memory, vigilance, spatial ability, abstract reasoning, facial emotion processing, and motor speed) and 3 neurophysiological tasks reflecting inhibitory processing (P50 gating, prepulse inhibition and antisaccade tasks). Factor analyses were conducted on the measures for each subject group and across the entire sample. Heritability analyses of factors were performed using SOLAR. RESULTS Analyses yielded 5 distinct factors: 1) Episodic Memory, 2) Working Memory, 3) Perceptual Vigilance, 4) Visual Abstraction, and 5) Inhibitory Processing. Neurophysiological measures had low associations with these factors. The factor structure of endophenotypes was largely comparable across probands, siblings and controls. Significant heritability estimates for the factors ranged from 22% (Episodic Memory) to 39% (Visual Abstraction). CONCLUSIONS Neurocognitive measures reflect a meaningful amount of shared variance whereas the neurophysiological measures reflect largely unique contributions as endophenotypes for schizophrenia. Composite endophenotype measures may inform our neurobiological and genetic understanding of schizophrenia.
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Ethridge LE, Soilleux M, Nakonezny PA, Reilly JL, Hill SK, Keefe RSE, Gershon ES, Pearlson GD, Tamminga CA, Keshavan MS, Sweeney JA. Behavioral response inhibition in psychotic disorders: diagnostic specificity, familiality and relation to generalized cognitive deficit. Schizophr Res 2014; 159:491-8. [PMID: 25261042 PMCID: PMC4253557 DOI: 10.1016/j.schres.2014.08.025] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 08/11/2014] [Accepted: 08/14/2014] [Indexed: 01/05/2023]
Abstract
Difficulty inhibiting context-inappropriate behavior is a common deficit in psychotic disorders. The diagnostic specificity of this impairment, its familiality, and its degree of independence from the generalized cognitive deficit associated with psychotic disorders remain to be clarified. Schizophrenia, schizoaffective and bipolar patients with history of psychosis (n=523), their available first-degree biological relatives (n=656), and healthy participants (n=223) from the multi-site B-SNIP study completed a manual Stop Signal task. A nonlinear mixed model was used to fit logistic curves to success rates on Stop trials as a function of parametrically varied Stop Signal Delay. While schizophrenia patients had greater generalized cognitive deficit than bipolar patients, their deficits were similar on the Stop Signal task. Further, only bipolar patients showed impaired inhibitory control relative to healthy individuals after controlling for generalized cognitive deficit. Deficits accounted for by the generalized deficit were seen in relatives of schizophrenia and schizoaffective patients, but not in relatives of bipolar patients. In clinically stable patients with psychotic bipolar disorder, impaired inhibitory behavioral control was a specific cognitive impairment, distinct from the generalized neuropsychological impairment associated with psychotic disorders. Thus, in bipolar disorder with psychosis, a deficit in inhibitory control may contribute to risk for impulsive behavior. Because the deficit was not familial in bipolar families and showed a lack of independence from the generalized cognitive deficit in schizophrenia spectrum disorders, it appears to be a trait related to illness processes rather than one tracking familial risk factors.
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Affiliation(s)
| | - Melanie Soilleux
- Department of Psychiatry, UT Southwestern Medical Center, Dallas Texas
| | - Paul A. Nakonezny
- Department of Psychiatry, UT Southwestern Medical Center, Dallas Texas,Department of Clinical Sciences, Division of Biostatistics, UT Southwestern Medical Center, Dallas, Texas
| | - James L. Reilly
- Departments of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - S. Kristian Hill
- Department of Psychology, Rosalind Franklin University, North Chicago, Illinois
| | - Richard S. E. Keefe
- Departments of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, North Carolina
| | | | - Godfrey D. Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Connecticut, and Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven Connecticut
| | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas Texas
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconness Medical Center, Harvard University, Boston Massachusetts
| | - John A. Sweeney
- Department of Psychiatry, UT Southwestern Medical Center, Dallas Texas,Department of Pediatrics, UT Southwestern Medical Center, Dallas Texas
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Expression of DISC1-interactome members correlates with cognitive phenotypes related to schizophrenia. PLoS One 2014; 9:e99892. [PMID: 24940743 PMCID: PMC4062455 DOI: 10.1371/journal.pone.0099892] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Accepted: 05/19/2014] [Indexed: 11/19/2022] Open
Abstract
Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.
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Dickinson D, Straub RE, Trampush JW, Gao Y, Feng N, Xie B, Shin JH, Lim HK, Ursini G, Bigos KL, Kolachana B, Hashimoto R, Takeda M, Baum GL, Rujescu D, Callicott JH, Hyde TM, Berman KF, Kleinman JE, Weinberger DR. Differential effects of common variants in SCN2A on general cognitive ability, brain physiology, and messenger RNA expression in schizophrenia cases and control individuals. JAMA Psychiatry 2014; 71:647-56. [PMID: 24718902 PMCID: PMC4160812 DOI: 10.1001/jamapsychiatry.2014.157] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
IMPORTANCE One approach to understanding the genetic complexity of schizophrenia is to study associated behavioral and biological phenotypes that may be more directly linked to genetic variation. OBJECTIVE To identify single-nucleotide polymorphisms associated with general cognitive ability (g) in people with schizophrenia and control individuals. DESIGN, SETTING, AND PARTICIPANTS Genomewide association study, followed by analyses in unaffected siblings and independent schizophrenia samples, functional magnetic resonance imaging studies of brain physiology in vivo, and RNA sequencing in postmortem brain samples. The discovery cohort and unaffected siblings were participants in the National Institute of Mental Health Clinical Brain Disorders Branch schizophrenia genetics studies. Additional schizophrenia cohorts were from psychiatric treatment settings in the United States, Japan, and Germany. The discovery cohort comprised 339 with schizophrenia and 363 community control participants. Follow-up analyses studied 147 unaffected siblings of the schizophrenia cases and independent schizophrenia samples including a total of an additional 668 participants. Imaging analyses included 87 schizophrenia cases and 397 control individuals. Brain tissue samples were available for 64 cases and 61 control individuals. MAIN OUTCOMES AND MEASURES We studied genomewide association with g, by group, in the discovery cohort. We used selected genotypes to test specific associations in unaffected siblings and independent schizophrenia samples. Imaging analyses focused on activation in the prefrontal cortex during working memory. Brain tissue studies yielded messenger RNA expression levels for RefSeq transcripts. RESULTS The schizophrenia discovery cohort showed genomewide-significant association of g with polymorphisms in sodium channel gene SCN2A, accounting for 10.4% of g variance (rs10174400, P = 9.27 × 10(-10)). Control individuals showed a trend for g/genotype association with reversed allelic directionality. The genotype-by-group interaction was also genomewide significant (P = 1.75 × 10(-9)). Siblings showed a genotype association with g parallel to the schizophrenia group and the same interaction pattern. Parallel, but weaker, associations with cognition were found in independent schizophrenia samples. Imaging analyses showed a similar pattern of genotype associations by group and genotype-by-group interaction. Sequencing of RNA in brain revealed reduced expression in 2 of 3 SCN2A alternative transcripts in the patient group, with genotype-by-group interaction, that again paralleled the cognition effects. CONCLUSIONS AND RELEVANCE The findings implicate SCN2A and sodium channel biology in cognitive impairment in schizophrenia cases and unaffected relatives and may facilitate development of cognition-enhancing treatments.
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Affiliation(s)
- Dwight Dickinson
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Richard E. Straub
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Joey W. Trampush
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Yuan Gao
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Ningping Feng
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Bin Xie
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Hun Ki Lim
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Gianluca Ursini
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
- Psychiatric Neuroscience Group, Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, Bari, Italy
| | - Kristin L. Bigos
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Bhaskar Kolachana
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Ryota Hashimoto
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Masatoshi Takeda
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Graham L. Baum
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Dan Rujescu
- Department of Psychiatry, Ludwig-Maximilians University, Munich, Germany
- Department of Psychiatry, Martin-Luther University Halle-Wittenberg, Halle, Germany
| | - Joseph H. Callicott
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Thomas M. Hyde
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Karen F. Berman
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Joel E. Kleinman
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Daniel R. Weinberger
- Clinical Brain Disorders Branch, Intramural Research Program, National Institute of Mental Health, NIH, Bethesda, MD, USA
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
- Departments of Psychiatry, Neurology, Neuroscience and the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Gilbert E, Mérette C, Jomphe V, Émond C, Rouleau N, Bouchard RH, Roy MA, Paccalet T, Maziade M. Cluster analysis of cognitive deficits may mark heterogeneity in schizophrenia in terms of outcome and response to treatment. Eur Arch Psychiatry Clin Neurosci 2014; 264:333-43. [PMID: 24173295 PMCID: PMC5025284 DOI: 10.1007/s00406-013-0463-7] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2013] [Accepted: 10/16/2013] [Indexed: 12/31/2022]
Abstract
Cognitive impairments are central to schizophrenia, but their clinical utility for tagging heterogeneity in lifetime outcome and response to treatment is not conclusive. By exploiting four cognitive domains consistently showing large deficits in studies, we tested whether cluster analysis would define separate subsets of patients and then whether the disease heterogeneity marked by these clusters would be related to lifetime outcome and response to treatment. A total of 112 schizophrenia patients completed a neuropsychological evaluation. The PANSS, GAF-S and GAF-F were rated at the onset and endpoint of the illness trajectory. A blind judgment of the lifetime response to treatment was made. The first cluster presented near-normal cognitive performance. Two other clusters of severely impaired patients were identified: one generally impaired in the four cognitive domains and another selectively impaired in visual episodic memory and processing speed, each relating to a different lifetime evolution of disease and treatment response. Although the two impaired clusters were clinically indistinguishable in symptom severity and functioning at disease onset, patients with selective cognitive impairments demonstrated better improvement at outcome, whereas the generally impaired patients were more likely to be treatment refractory. The findings have implications for the management of patients and for clinical trials since particular combinations of cognitive deficits in patients would influence their treatment response.
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Affiliation(s)
- Elsa Gilbert
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada
| | - Chantal Mérette
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada,Faculté de Médecine, Laval University, Quebec, QC, Canada
| | - Valérie Jomphe
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada
| | - Claudia Émond
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada
| | - Nancie Rouleau
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada,École de psychologie, Université Laval, Quebec, QC, Canada
| | - Roch-Hugo Bouchard
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada
| | - Marc-André Roy
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada,Faculté de Médecine, Laval University, Quebec, QC, Canada
| | - Thomas Paccalet
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada
| | - Michel Maziade
- Centre de recherche, Institut universitaire en santé mentale de Québec, 2601, chemin de la Canardière (F-4500), Quebec, QC G1J 2G3, Canada,Faculté de Médecine, Laval University, Quebec, QC, Canada
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Todarello G, Feng N, Kolachana BS, Li C, Vakkalanka R, Bertolino A, Weinberger DR, Straub RE. Incomplete penetrance of NRXN1 deletions in families with schizophrenia. Schizophr Res 2014; 155:1-7. [PMID: 24680031 DOI: 10.1016/j.schres.2014.02.023] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2013] [Revised: 02/27/2014] [Accepted: 02/28/2014] [Indexed: 12/11/2022]
Abstract
Neurexin 1 (NRXN1) is a presynaptic neuronal adhesion molecule that interacts with postsynaptic neuroligins in both glutamatergic and GABAergic synapses and is important in synaptic formation and function. NRXN1 deletions increase the risk of schizophrenia, so our aims were to explore this in our family sample, to distinguish de novo from inherited mutations, to examine transmission to affected and unaffected siblings and to estimate penetrance. We performed copy number analyses in NRXN1 using data from Illumina BeadArrays from 635 subjects with schizophrenia (276 in genotyped families), 487 of their unaffected parents and 309 unaffected siblings as well as 635 normal controls, all from the CBDB/NIMH Genetic Study of Schizophrenia. Deletions called by software were confirmed by quantitative PCR and comparative genome hybridization. There were deletions in 15 individuals in 11 families, including de novo exonic deletions in one case and one unaffected sibling. We observed no deletions in controls, 7 deletions in cases (1.10%), and an unexpectedly high deletion frequency in parents (n=5, 1.02%) and siblings (n=3, 0.97%). Three families showed inheritance from an unaffected parent, and in two families an unaffected parent did not transmit to the affected offspring. Thus we have added to the evidence that NRXN1 deletions are more frequent in patients with schizophrenia than in healthy individuals. However, the presence of de novo deletions in unaffected relatives and transmission from and to unaffected family members demonstrated that while the deletions may well have been necessary for some carriers to develop schizophrenia, they were not always sufficient.
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Affiliation(s)
- Giovanna Todarello
- Psychiatric Neuroscience Group, Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari, Italy
| | - Ningping Feng
- Clinical Brain Disorders Branch, Genes Cognition and Psychosis Program, Intramural Research Program, NIMH, NIH, Bethesda, MD 20892, United States
| | - Bhaskar S Kolachana
- Clinical Brain Disorders Branch, Genes Cognition and Psychosis Program, Intramural Research Program, NIMH, NIH, Bethesda, MD 20892, United States
| | - Chao Li
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, 855 North Wolfe St, Suite 300, Baltimore, MD 21205, United States
| | - Radhakrishna Vakkalanka
- Clinical Brain Disorders Branch, Genes Cognition and Psychosis Program, Intramural Research Program, NIMH, NIH, Bethesda, MD 20892, United States
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari, Bari, Italy; Pharma Research and Early Development, Neuroscience DTA, Hoffman-La Roche, Ltd., Basel, Switzerland
| | - Daniel R Weinberger
- Clinical Brain Disorders Branch, Genes Cognition and Psychosis Program, Intramural Research Program, NIMH, NIH, Bethesda, MD 20892, United States; Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, 855 North Wolfe St, Suite 300, Baltimore, MD 21205, United States; Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD 21230, United States; Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21230, United States; Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21230, United States; Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21230, United States
| | - Richard E Straub
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, 855 North Wolfe St, Suite 300, Baltimore, MD 21205, United States.
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Morita Y, Callicott JH, Testa LR, Mighdoll MI, Dickinson D, Chen Q, Tao R, Lipska BK, Kolachana B, Law AJ, Ye T, Straub RE, Weinberger DR, Kleinman JE, Hyde TM. Characteristics of the cation cotransporter NKCC1 in human brain: alternate transcripts, expression in development, and potential relationships to brain function and schizophrenia. J Neurosci 2014; 34:4929-40. [PMID: 24695712 PMCID: PMC3972720 DOI: 10.1523/jneurosci.1423-13.2014] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2013] [Revised: 01/10/2014] [Accepted: 02/14/2014] [Indexed: 02/07/2023] Open
Abstract
Early in development, GABA, an inhibitory neurotransmitter in adults, is excitatory. NKCC1 (SLC12A2) encodes one of two cation chloride cotransporters mediating the conversion of GABA from excitatory to inhibitory. Using 3' and 5' RACE and PCR, we verified previously characterized alternative transcripts of NKCC1a (1-27) and NKCC1b (1-27(Δ21)), identified new NKCC1 transcripts, and explored their expression patterns during human prefrontal cortical development. A novel ultra-short transcript (1-2a) was expressed preferentially in the fetus. Expression of NKCC1b and 1-2a were decreased in schizophrenia compared with controls (NKCC1b: 0.8-fold decrease, p = 0.013; 1-2a: 0.8-fold decrease, p = 0.006). Furthermore, the expression of NKCC1b was associated with NKCC1 polymorphism rs3087889. The minor allele at rs3087889, associated with reduced NKCC1b expression (homozygous for major allele: N = 37; homozygous for minor allele: N = 15; 1.5-fold decrease; p < 0.01), was also associated with a modest increase in schizophrenia risk in a case-control sample (controls: N = 435; cases: N = 397, OR = 1.5). This same allele was then found associated with cognitive (n = 369) and fMRI (n = 313) intermediate phenotypes associated with schizophrenia-working memory (Cohen's d = 0.35), global cognition or g (d = 0.18), and prefrontal inefficiency (d = 0.36) as measured by BOLD fMRI during a working memory task. Together, these preclinical and clinical results suggest that variation in NKCC1 may increase risk for schizophrenia via alterations of mRNA expression at the molecular level and impairment of optimal prefrontal function at the macro or systems level.
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Affiliation(s)
- Yukitaka Morita
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Department of Psychiatry, Hiroshima City Hospital, Hiroshima City, Hiroshima Prefecture, 730-8518, Japan
| | - Joseph H. Callicott
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Lauren R. Testa
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Michelle I. Mighdoll
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Dwight Dickinson
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Qiang Chen
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Ran Tao
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Barbara K. Lipska
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Bhaskar Kolachana
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Amanda J. Law
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Neurodevelopmental and Neuropsychiatric Genetics Laboratory, Departments of Psychiatry and Cell and Developmental Biology, University of Colorado School of Medicine, Aurora, Colorado 80045, and
| | - Tianzhang Ye
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Richard E. Straub
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Daniel R. Weinberger
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
- Departments of Psychiatry, Neurology, Neuroscience and the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Joel E. Kleinman
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
| | - Thomas M. Hyde
- Clinical Brain Disorders Branch, Genes, Cognition, and Psychosis Program, Division of Intramural Research Programs, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland 21205
- Departments of Psychiatry, Neurology, Neuroscience and the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
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Yeo RA, Martinez D, Pommy J, Ehrlich S, Schulz SC, Ho BC, Bustillo JR, Calhoun VD. The impact of parent socio-economic status on executive functioning and cortical morphology in individuals with schizophrenia and healthy controls. Psychol Med 2014; 44:1257-1265. [PMID: 23866983 PMCID: PMC4428550 DOI: 10.1017/s0033291713001608] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
BACKGROUND Relatively lower executive functioning is characteristic of individuals with schizophrenia. As low socio-economic status (SES) early in life (i.e. parent SES) has been linked with lower executive skills in healthy children, we hypothesized that parental SES (pSES) would be more strongly related to executive functioning in individuals with schizophrenia than in controls and have a greater impact on prefrontal cortical morphology. METHOD Healthy controls (n = 125) and individuals with schizophrenia (n = 102) completed tests assessing executive functioning and intelligence. The groups were matched on pSES, which was evaluated with the Hollingshead-Redlich scale. A principal components analysis (PCA) was conducted on 10 variables from six executive tests, yielding three specific components (fluency, planning and response inhibition). Voxel-based morphometry (VBM) was used to evaluate effects of pSES on gray matter (GM) concentration. RESULTS Lower pSES was associated with lower scores across the three executive functioning components, and a significant group by pSES interaction was observed such that low pSES, in particular, affected individuals with schizophrenia. These effects remained significant when intellectual ability, education and self-SES (sSES) were added as covariates. VBM revealed that lower pSES was associated with reduced GM volume in several anterior brain regions, especially the superior frontal gyrus, in patients but not in controls. CONCLUSIONS These findings suggest that individuals with schizophrenia may be particularly vulnerable to the adverse impact of low pSES, in terms of both lower executive skills and reduced anterior GM volumes.
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Affiliation(s)
- Ronald A. Yeo
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
- The Mind Research Network, Albuquerque, NM, USA
| | - Desirae Martinez
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
| | - Jessica Pommy
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
| | - Stefan Ehrlich
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - S. Charles Schulz
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Beng-Choon Ho
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City IA
| | - Juan R. Bustillo
- The Mind Research Network, Albuquerque, NM, USA
- Department of Psychiatry, University of New Mexico, Albuquerque, NM, USA
| | - Vince D. Calhoun
- The Mind Research Network, Albuquerque, NM, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
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Quee PJ, Alizadeh BZ, Aleman A, van den Heuvel ER. Cognitive subtypes in non-affected siblings of schizophrenia patients: characteristics and profile congruency with affected family members. Psychol Med 2014; 44:395-405. [PMID: 23659373 DOI: 10.1017/s0033291713000809] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Although cognitive subtypes have been suggested in schizophrenia patients, similar analyses have not been carried out in their non-affected siblings. Subtype classification may provide more insight into genetically driven variation in cognitive function. We investigated cognitive subtypes in siblings. METHOD Cluster analyses were performed in 654 non-affected siblings, on a cognitive battery that included tests of attention, intellectual function and episodic memory. Resulting subtypes in the siblings were analyzed for cognitive, demographic and clinical characteristics and compared with those of their probands. RESULTS Three sibling subtypes of cognitive function were distinguished: 'normal', 'mixed' and 'impaired'. Normal profile siblings (n = 192) were unimpaired on cognitive tests, in contrast to their proband (n = 184). Mixed profile siblings (n = 228) and their probands (n = 222) had a more similar performance pattern. Impaired profile siblings had poorer functional outcomes (n = 234) and their profile was almost identical to that of their proband (n = 223). Probands with cognitively impaired siblings could be distinguished from other schizophrenia patients by their own cognitive performance. They also had poorer clinical characteristics, including achievement of symptomatic remission. CONCLUSIONS Unaffected siblings of patients with schizophrenia are heterogeneous with respect to cognitive function. The poorer the cognitive profile of the sibling, the higher the level of correspondence with the proband. The sibling's cognitive subtype was predictive for disease course in the proband. Distinguishing cognitive subtypes of unaffected siblings may be of relevance for genetic studies.
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Affiliation(s)
- P J Quee
- Department of Psychiatry and Rob Giel Research Center, University of Groningen, University Medical Center Groningen, The Netherlands
| | - B Z Alizadeh
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands
| | - A Aleman
- Department of Neuroscience, University of Groningen, University Medical Center Groningen, The Netherlands
| | - E R van den Heuvel
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands
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Hill SK, Bjorkquist O, Carrathers T, Roseberry JE, Hochberger WC, Bishop JR. Sequential processing deficits in schizophrenia: relationship to neuropsychology and genetics. Schizophr Res 2013; 151:91-6. [PMID: 24119464 PMCID: PMC4479132 DOI: 10.1016/j.schres.2013.09.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2013] [Revised: 09/11/2013] [Accepted: 09/16/2013] [Indexed: 11/16/2022]
Abstract
Utilizing a combination of neuropsychological and cognitive neuroscience approaches may be essential for characterizing cognitive deficits in schizophrenia and eventually assessing cognitive outcomes. This study was designed to compare the stability of select exemplars for these approaches and their correlations in schizophrenia patients with stable treatment and clinical profiles. Reliability estimates for serial order processing were comparable to neuropsychological measures and indicate that experimental serial order processing measures may be less susceptible to practice effects than traditional neuropsychological measures. Correlations were moderate and consistent with a global cognitive factor. Exploratory analyses indicated a potentially critical role of the Met allele of the Catechol-O-methyltransferase (COMT) Val158Met polymorphism in externally paced sequential recall. Experimental measures of serial order processing may reflect frontostriatal dysfunction and be a useful supplement to large neuropsychological batteries.
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Affiliation(s)
- S. Kristian Hill
- Rosalind Franklin University of Medicine and Science, North Chicago, IL,Corresponding author at: Rosalind Franklin University of Medicine and Science, Department of Psychology, 3333 Green Bay Rd., North Chicago, IL 60064, Phone: (847) 578-8748,
| | - Olivia Bjorkquist
- Department of Psychology, University of Illinois at Chicago, Chicago, IL
| | - Tarra Carrathers
- Rosalind Franklin University of Medicine and Science, North Chicago, IL
| | | | | | - Jeffrey R. Bishop
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, IL
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Palaniyappan L, Simmonite M, White TP, Liddle EB, Liddle PF. Neural primacy of the salience processing system in schizophrenia. Neuron 2013; 79:814-28. [PMID: 23972602 PMCID: PMC3752973 DOI: 10.1016/j.neuron.2013.06.027] [Citation(s) in RCA: 235] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/20/2013] [Indexed: 01/03/2023]
Abstract
For effective information processing, two large-scale distributed neural networks appear to be critical: a multimodal executive system anchored on the dorsolateral prefrontal cortex (DLPFC) and a salience system anchored on the anterior insula. Aberrant interaction among distributed networks is a feature of psychiatric disorders such as schizophrenia. We used whole-brain Granger causal modeling using resting fMRI and observed a significant failure of both the feedforward and reciprocal influence between the insula and the DLPFC in schizophrenia. Further, a significant failure of directed influence from bilateral visual cortices to the insula was also seen in patients. These findings provide compelling evidence for a breakdown of the salience-execution loop in the clinical expression of psychosis. In addition, this offers a parsimonious explanation for the often-observed “frontal inefficiency,” the failure to recruit prefrontal system when salient or novel information becomes available in patients with schizophrenia. A salience-executive loop emerges on fMRI whole-brain Granger causal analysis At rest, DLPFC has inhibitory Granger influence on the salience network In schizophrenia, the salience-executive interaction is diminished Visual cortex fails to influence the salience network in schizophrenia
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Affiliation(s)
- Lena Palaniyappan
- Centre for Translational Neuroimaging in Mental Health, Division of Psychiatry, University of Nottingham, Nottingham NG7 2TU, UK.
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