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Sefik E, Duan K, Li Y, Sholar B, Evans L, Pincus J, Ammar Z, Murphy MM, Klaiman C, Saulnier CA, Pulver SL, Goldman-Yassen AE, Guo Y, Walker EF, Li L, Mulle JG, Shultz S. Structural deviations of the posterior fossa and the cerebellum and their cognitive links in a neurodevelopmental deletion syndrome. Mol Psychiatry 2024:10.1038/s41380-024-02584-8. [PMID: 38744992 DOI: 10.1038/s41380-024-02584-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 04/16/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
High-impact genetic variants associated with neurodevelopmental disorders provide biologically-defined entry points for mechanistic investigation. The 3q29 deletion (3q29Del) is one such variant, conferring a 40-100-fold increased risk for schizophrenia, as well as high risk for autism and intellectual disability. However, the mechanisms leading to neurodevelopmental disability remain largely unknown. Here, we report the first in vivo quantitative neuroimaging study in individuals with 3q29Del (N = 24) and neurotypical controls (N = 1608) using structural MRI. Given prior radiology reports of posterior fossa abnormalities in 3q29Del, we focused our investigation on the cerebellum and its tissue-types and lobules. Additionally, we compared the prevalence of cystic/cyst-like malformations of the posterior fossa between 3q29Del and controls and examined the association between neuroanatomical findings and quantitative traits to probe gene-brain-behavior relationships. 3q29Del participants had smaller cerebellar cortex volumes than controls, before and after correction for intracranial volume (ICV). An anterior-posterior gradient emerged in finer grained lobule-based and voxel-wise analyses. 3q29Del participants also had larger cerebellar white matter volumes than controls following ICV-correction and displayed elevated rates of posterior fossa arachnoid cysts and mega cisterna magna findings independent of cerebellar volume. Cerebellar white matter and subregional gray matter volumes were associated with visual-perception and visual-motor integration skills as well as IQ, while cystic/cyst-like malformations yielded no behavioral link. In summary, we find that abnormal development of cerebellar structures may represent neuroimaging-based biomarkers of cognitive and sensorimotor function in 3q29Del, adding to the growing evidence identifying cerebellar pathology as an intersection point between syndromic and idiopathic forms of neurodevelopmental disabilities.
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Affiliation(s)
- Esra Sefik
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Kuaikuai Duan
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Yiheng Li
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Brittney Sholar
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Lindsey Evans
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Jordan Pincus
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Zeena Ammar
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Melissa M Murphy
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Cheryl Klaiman
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Celine A Saulnier
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Neurodevelopmental Assessment & Consulting Services, Atlanta, GA, USA
| | - Stormi L Pulver
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Adam E Goldman-Yassen
- Department of Radiology, Children's Healthcare of Atlanta, Atlanta, GA, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Ying Guo
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Longchuan Li
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA
| | - Jennifer G Mulle
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA.
| | - Sarah Shultz
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
- Marcus Autism Center, Children's Healthcare of Atlanta and Emory University School of Medicine, Atlanta, GA, USA.
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2
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Jonas KG, Cannon TD, Docherty AR, Dwyer D, Gur RC, Gur RE, Nelson B, Reininghaus U, Kotov R. Psychosis superspectrum I: Nosology, etiology, and lifespan development. Mol Psychiatry 2024; 29:1005-1019. [PMID: 38200290 DOI: 10.1038/s41380-023-02388-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 12/05/2023] [Accepted: 12/15/2023] [Indexed: 01/12/2024]
Abstract
This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment. The structure of the spectra and their components are shown to parallel the genetic structure of psychosis and related traits. Psychoticism and detachment have distinct patterns of association with urbanicity, migrant and ethnic minority status, childhood adversity, and cannabis use. The superspectrum also provides a useful model for describing the emergence and course of psychosis, as components of the superspectrum are relatively stable over time. Changes in psychoticism predict the onset of psychosis-related psychopathology, whereas changes in detachment and cognition define later course. Implications of the superspectrum for genetic, socio-environmental, and longitudinal research are discussed. A companion review focuses on neurobiology, treatment response, and clinical utility of the superspectrum, and future research directions.
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Affiliation(s)
- Katherine G Jonas
- Department of Psychiatry & Behavioral Health, Stony Brook University, Stony Brook, NY, USA.
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Anna R Docherty
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Dominic Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Ruben C Gur
- Brain Behavior Laboratory, Department of Psychiatry and the Penn-CHOP Lifespan Brain Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Raquel E Gur
- Brain Behavior Laboratory, Department of Psychiatry and the Penn-CHOP Lifespan Brain Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Barnaby Nelson
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Ulrich Reininghaus
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- ESRC Centre for Society and Mental Health and Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Roman Kotov
- Department of Psychiatry & Behavioral Health, Stony Brook University, Stony Brook, NY, USA
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3
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Zhang J, Qiu H, Zhao Q, Liao C, Guoli Y, Luo Q, Zhao G, Zhang N, Wang S, Zhang Z, Lei M, Liu F, Peng Y. Genetic overlap between schizophrenia and cognitive performance. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:31. [PMID: 38443399 PMCID: PMC10914834 DOI: 10.1038/s41537-024-00453-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 02/16/2024] [Indexed: 03/07/2024]
Abstract
Schizophrenia (SCZ), a highly heritable mental disorder, is characterized by cognitive impairment, yet the extent of the shared genetic basis between schizophrenia and cognitive performance (CP) remains poorly understood. Therefore, we aimed to explore the polygenic overlap between SCZ and CP. Specifically, the bivariate causal mixture model (MiXeR) was employed to estimate the extent of genetic overlap between SCZ (n = 130,644) and CP (n = 257,841), and conjunctional false discovery rate (conjFDR) approach was used to identify shared genetic loci. Subsequently, functional annotation and enrichment analysis were carried out on the identified genomic loci. The MiXeR analyses revealed that 9.6 K genetic variants are associated with SCZ and 10.9 K genetic variants for CP, of which 9.5 K variants are shared between these two traits (Dice coefficient = 92.8%). By employing conjFDR, 236 loci were identified jointly associated with SCZ and CP, of which 139 were novel for the two traits. Within these shared loci, 60 exhibited consistent effect directions, while 176 had opposite effect directions. Functional annotation analysis indicated that the shared genetic loci were mainly located in intronic and intergenic regions, and were found to be involved in relevant biological processes such as nervous system development, multicellular organism development, and generation of neurons. Together, our findings provide insights into the shared genetic architecture between SCZ and CP, suggesting common pathways and mechanisms contributing to both traits.
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Affiliation(s)
- Jianfei Zhang
- College of Computer and Control Engineering, Qiqihar University, Qiqihar, Heilongjiang, China
| | - Hao Qiu
- College of Computer and Control Engineering, Qiqihar University, Qiqihar, Heilongjiang, China
| | - Qiyu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chongjian Liao
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Yuxuan Guoli
- The Second Hospital of Tianjin Medial University, Tianjin, China
| | - Qi Luo
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Guoshu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Nannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhihui Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Minghuan Lei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
| | - Yanmin Peng
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.
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4
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Jameei H, Rakesh D, Zalesky A, Cairns MJ, Reay WR, Wray NR, Di Biase MA. Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review. Schizophr Bull 2024; 50:32-46. [PMID: 37354489 PMCID: PMC10754175 DOI: 10.1093/schbul/sbad087] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/26/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is highly heritable, with a polygenic effect of many genes conferring risk. Evidence on whether cumulative risk also predicts alterations in brain morphology and function is inconsistent. This systematic review examined evidence for schizophrenia polygenic risk score (sczPRS) associations with commonly used magnetic resonance imaging (MRI) measures. We expected consistent evidence to emerge for significant sczPRS associations with variation in structure and function, specifically in frontal, temporal, and insula cortices that are commonly implicated in schizophrenia pathophysiology. STUDY DESIGN In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE, Embase, and PsycINFO for peer-reviewed studies published between January 2013 and March 2022. Studies were screened against predetermined criteria and National Institutes of Health (NIH) quality assessment tools. STUDY RESULTS In total, 57 studies of T1-weighted structural, diffusion, and functional MRI were included (age range = 9-80 years, Nrange = 64-76 644). We observed moderate, albeit preliminary, evidence for higher sczPRS predicting global reductions in cortical thickness and widespread variation in functional connectivity, and to a lesser extent, region-specific reductions in frontal and temporal volume and thickness. Conversely, sczPRS does not predict whole-brain surface area or gray/white matter volume. Limited evidence emerged for sczPRS associations with diffusion tensor measures of white matter microstructure in a large community sample and smaller cohorts of children and young adults. These findings were broadly consistent across community and clinical populations. CONCLUSIONS Our review supports the hypothesis that schizophrenia is a disorder of disrupted within and between-region brain connectivity, and points to specific whole-brain and regional MRI metrics that may provide useful intermediate phenotypes.
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Affiliation(s)
- Hadis Jameei
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Divyangana Rakesh
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, VIC, Australia
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Newcastle, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - William R Reay
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Newcastle, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Maria A Di Biase
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Department of Anatomy and Physiology, School of Biomedical Sciences, The University of Melbourne, VIC, Australia
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
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5
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Wootton O, Shadrin AA, Bjella T, Smeland OB, van der Meer D, Frei O, O’Connell KS, Ueland T, Andreassen OA, Stein DJ, Dalvie S. Genomic Insights into the Shared and Distinct Genetic Architecture of Cognitive Function and Schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.13.23298348. [PMID: 38014326 PMCID: PMC10680895 DOI: 10.1101/2023.11.13.23298348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Cognitive impairment is a major determinant of functional outcomes in schizophrenia, and efforts to understand the biological basis of cognitive dysfunction in the disorder are ongoing. Previous studies have suggested genetic overlap between global cognitive ability and schizophrenia, but further work is needed to delineate the shared genetic architecture. Here, we apply genomic structural equation modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank (UKB). We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). We identified three broad factors (visuo-spatial, verbal analytic and decision/reaction time) that underly the genetic correlations between the UKB cognitive tests. Global genetic correlations showed a significant but moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found evidence of substantial polygenic overlap between each cognitive factor and schizophrenia but show that most loci shared between the latent cognitive factors and schizophrenia have unique patterns of association with the cognitive factors. Biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we find that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptom dimensions. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.
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Affiliation(s)
- Olivia Wootton
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Alexey A. Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Thomas Bjella
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B. Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Blindern, Oslo, Norway
| | - Kevin S O’Connell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torill Ueland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dan J. Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- SAMRC Unit on Risk & Resilience in Mental Disorders, South Africa
| | - Shareefa Dalvie
- Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa
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6
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Sideli L, Aas M, Quattrone D, La Barbera D, La Cascia C, Ferraro L, Alameda L, Velthorst E, Trotta G, Tripoli G, Schimmenti A, Fontana A, Gayer-Anderson C, Stilo S, Seminerio F, Sartorio C, Marrazzo G, Lasalvia A, Tosato S, Tarricone I, Berardi D, D'Andrea G, Arango C, Arrojo M, Bernardo M, Bobes J, Sanjuán J, Santos JL, Menezes PR, Del-Ben CM, Jongsma HE, Jones PB, Kirkbride JB, Llorca PM, Tortelli A, Pignon B, de Haan L, Selten JP, Van Os J, Rutten BP, Bentall R, Di Forti M, Murray RM, Morgan C, Fisher HL. The relationship between genetic liability, childhood maltreatment, and IQ: findings from the EU-GEI multicentric case-control study. Soc Psychiatry Psychiatr Epidemiol 2023; 58:1573-1580. [PMID: 37335320 PMCID: PMC10460355 DOI: 10.1007/s00127-023-02513-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 06/04/2023] [Indexed: 06/21/2023]
Abstract
This study investigated if the association between childhood maltreatment and cognition among psychosis patients and community controls was partially accounted for by genetic liability for psychosis. Patients with first-episode psychosis (N = 755) and unaffected controls (N = 1219) from the EU-GEI study were assessed for childhood maltreatment, intelligence quotient (IQ), family history of psychosis (FH), and polygenic risk score for schizophrenia (SZ-PRS). Controlling for FH and SZ-PRS did not attenuate the association between childhood maltreatment and IQ in cases or controls. Findings suggest that these expressions of genetic liability cannot account for the lower levels of cognition found among adults maltreated in childhood.
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Affiliation(s)
- Lucia Sideli
- Department of Human Science, LUMSA University, Piazza delle Vaschette, 101, 00193, Rome, Italy.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England.
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy.
| | - Monica Aas
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
- NORMENT Centre for Psychosis Research, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Behavioural Sciences, OsloMet, Oslo Metropolitan University, Oslo, Norway
| | - Diego Quattrone
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
| | - Daniele La Barbera
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Caterina La Cascia
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Laura Ferraro
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Luis Alameda
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Centro Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Seville, Spain
- Instituto de Biomedicina de Sevilla (IBIS), Hospital Universitario Virgen del Rocio, Departamento de Psiquiatria, Universidad de Sevilla, Seville, Spain
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Eva Velthorst
- Department of Research, Mental Health Service Organization 'GGZ Noord-Holland-Noord', Hoorn, The Netherlands
| | - Giulia Trotta
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
| | - Giada Tripoli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy
| | - Adriano Schimmenti
- Faculty of Human and Social Sciences, UKE - Kore University of Enna, Enna, Italy
| | - Andrea Fontana
- Department of Human Science, LUMSA University, Piazza delle Vaschette, 101, 00193, Rome, Italy
| | - Charlotte Gayer-Anderson
- Department of Health Services and Population Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Simona Stilo
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Department of Mental Health and Addiction Services, ASP Crotone, Crotone, Italy
| | - Fabio Seminerio
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Crocettarachele Sartorio
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Giovanna Marrazzo
- Department of Biomedicine, Neuroscience, and Advanced Diagnostic, University of Palermo, Palermo, Italy
| | - Antonio Lasalvia
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
| | - Sarah Tosato
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
| | - Ilaria Tarricone
- Department of Medical and Surgical Sciences, Alma Mater Studiorum - Bologna University, Bologna, Italy
| | - Domenico Berardi
- Department of Biomedical and NeuroMotor Sciences, Psychiatry Unit, Alma Mater Studiorum - Bologna University, Bologna, Italy
| | - Giuseppe D'Andrea
- Department of Biomedical and NeuroMotor Sciences, Psychiatry Unit, Alma Mater Studiorum - Bologna University, Bologna, Italy
| | - Celso Arango
- Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, ISGM, CIBERSAM, Madrid, Spain
| | - Manuel Arrojo
- Department of Psychiatry, Psychiatric Genetic Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago de Compostela, Santiago, Spain
| | - Miguel Bernardo
- Barcelona Clinic Schizophrenia Unit, Hospital Clinic, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Institut d'Investigacions Biomèdiques, August Pi I Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Julio Bobes
- Department of Medicine, Psychiatry Area, School of Medicine, Universidad de Oviedo, ISPA, INEUROPA, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Oviedo, Spain
| | - Julio Sanjuán
- Department of Psychiatry, School of Medicine, Universidad de Valencia, Centro de Investigación Biomédica en Red de Salud Mental, Valencia, Spain
| | - Jose Luis Santos
- Department of Psychiatry, Hospital "Virgen de La Luz", Cuenca, Spain
| | | | | | - Hannah E Jongsma
- PsyLife Group, Division of Psychiatry, University College London, London, England
- Department of Psychiatry, University of Cambridge, Cambridge, England
| | - Peter B Jones
- CAMEO Early Intervention Service, Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, England
- EA 7280 Npsydo, Université Clermont Auvergne, Clermont-Ferrand, France
| | - James B Kirkbride
- PsyLife Group, Division of Psychiatry, University College London, London, England
| | | | - Andrea Tortelli
- Establissement Public de Santé, Maison Blanche, Paris, France
| | - Baptiste Pignon
- AP-HP, Groupe Hospitalier "Mondor", Pôle de Psychiatrie, Créteil, France
- Institut National de la Santé et de la Recherche Médicale, U955, Créteil, France
- Fondation FondaMental, Créteil, France
| | - Lieuwe de Haan
- Early Psychosis Section, Department of Psychiatry, Amsterdam UMC, Amsterdam, The Netherlands
| | - Jean-Paul Selten
- Institute for Mental Health, GGZ Rivierduinen, Leiden, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jim Van Os
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department Psychiatry, Utrecht University Medical Centre, Utrecht, The Netherlands
| | - Bart P Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Richard Bentall
- Department of Psychology, University of Sheffield, Cathedral Court, 1 Vicar Lane, Sheffield, S1 2LT, UK
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
| | - Craig Morgan
- Department of Health Services and Population Research, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, England
- ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Helen L Fisher
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
- ESRC Centre for Society and Mental Health, King's College London, London, UK
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7
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Tiego J, Thompson K, Arnatkeviciute A, Hawi Z, Finlay A, Sabaroedin K, Johnson B, Bellgrove MA, Fornito A. Dissecting Schizotypy and Its Association With Cognition and Polygenic Risk for Schizophrenia in a Nonclinical Sample. Schizophr Bull 2023; 49:1217-1228. [PMID: 36869759 PMCID: PMC10483465 DOI: 10.1093/schbul/sbac016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Schizotypy is a multidimensional construct that captures a continuum of risk for developing schizophrenia-spectrum psychopathology. Existing 3-factor models of schizotypy, consisting of positive, negative, and disorganized dimensions have yielded mixed evidence of genetic continuity with schizophrenia using polygenic risk scores. Here, we propose an approach that involves splitting positive and negative schizotypy into more specific subdimensions that are phenotypically continuous with distinct positive symptoms and negative symptoms recognized in clinical schizophrenia. We used item response theory to derive high-precision estimates of psychometric schizotypy using 251 self-report items obtained from a non-clinical sample of 727 (424 females) adults. These subdimensions were organized hierarchically using structural equation modeling into 3 empirically independent higher-order dimensions enabling associations with polygenic risk for schizophrenia to be examined at different levels of phenotypic generality and specificity. Results revealed that polygenic risk for schizophrenia was associated with variance specific to delusional experiences (γ = 0.093, P = .001) and reduced social interest and engagement (γ = 0.076, P = .020), and these effects were not mediated via the higher-order general, positive, or negative schizotypy factors. We further fractionated general intellectual functioning into fluid and crystallized intelligence in 446 (246 females) participants that underwent onsite cognitive assessment. Polygenic risk scores explained 3.6% of the variance in crystallized intelligence. Our precision phenotyping approach could be used to enhance the etiologic signal in future genetic association studies and improve the detection and prevention of schizophrenia-spectrum psychopathology.
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Affiliation(s)
- Jeggan Tiego
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
- Monash Biomedical Imaging, Monash University, 770 Blackburn Rd, Clayton, VIC 3800, Australia
| | - Kate Thompson
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
- Monash Biomedical Imaging, Monash University, 770 Blackburn Rd, Clayton, VIC 3800, Australia
| | - Aurina Arnatkeviciute
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Ziarih Hawi
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Amy Finlay
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Kristina Sabaroedin
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
- Monash Biomedical Imaging, Monash University, 770 Blackburn Rd, Clayton, VIC 3800, Australia
| | - Beth Johnson
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Mark A Bellgrove
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC 3800, Australia
- School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia
- Monash Biomedical Imaging, Monash University, 770 Blackburn Rd, Clayton, VIC 3800, Australia
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8
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Owen MJ, Legge SE, Rees E, Walters JTR, O'Donovan MC. Genomic findings in schizophrenia and their implications. Mol Psychiatry 2023; 28:3638-3647. [PMID: 37853064 PMCID: PMC10730422 DOI: 10.1038/s41380-023-02293-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 10/02/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023]
Abstract
There has been substantial progress in understanding the genetics of schizophrenia over the past 15 years. This has revealed a highly polygenic condition with the majority of the currently explained heritability coming from common alleles of small effect but with additional contributions from rare copy number and coding variants. Many specific genes and loci have been implicated that provide a firm basis upon which mechanistic research can proceed. These point to disturbances in neuronal, and particularly synaptic, functions that are not confined to a small number of brain regions and circuits. Genetic findings have also revealed the nature of schizophrenia's close relationship to other conditions, particularly bipolar disorder and childhood neurodevelopmental disorders, and provided an explanation for how common risk alleles persist in the population in the face of reduced fecundity. Current genomic approaches only potentially explain around 40% of heritability, but only a small proportion of this is attributable to robustly identified loci. The extreme polygenicity poses challenges for understanding biological mechanisms. The high degree of pleiotropy points to the need for more transdiagnostic research and the shortcomings of current diagnostic criteria as means of delineating biologically distinct strata. It also poses challenges for inferring causality in observational and experimental studies in both humans and model systems. Finally, the Eurocentric bias of genomic studies needs to be rectified to maximise benefits and ensure these are felt across diverse communities. Further advances are likely to come through the application of new and emerging technologies, such as whole-genome and long-read sequencing, to large and diverse samples. Substantive progress in biological understanding will require parallel advances in functional genomics and proteomics applied to the brain across developmental stages. For these efforts to succeed in identifying disease mechanisms and defining novel strata they will need to be combined with sufficiently granular phenotypic data.
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Affiliation(s)
- Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
| | - Sophie E Legge
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Elliott Rees
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
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9
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Fusar-Poli L, Rodolico A, Martinez M, Fichera C, Lin BD, Basadonne I, Concerto C, Aguglia E, Guloksuz S, Signorelli MS. The association between polygenic risk scores for mental disorders and social cognition: A scoping review. J Psychiatr Res 2023; 164:389-401. [PMID: 37418886 DOI: 10.1016/j.jpsychires.2023.06.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 06/10/2023] [Accepted: 06/21/2023] [Indexed: 07/09/2023]
Abstract
People with mental disorders, such as psychosis or autism spectrum disorder (ASD), often present impairments in social cognition (SC), which may cause significant difficulties in real-world functioning. SC deficits are seen also in unaffected relatives, indicating a genetic substratum. The present review evaluated the evidence on the association between SC and the polygenic risk score (PRS), a single metric of the molecular genetic risk to develop a specific disorder. In July 2022, we conducted systematic searches in Scopus and PubMed following the PRISMA-ScR guidelines. We selected original articles written in English reporting results on the association between PRSs for any mental disorder and domains of SC either in people with mental disorders or controls. The search yielded 244 papers, of which 13 were selected for inclusion. Studies tested mainly PRSs for schizophrenia, ASD, and attention-deficit hyperactivity disorder. Emotion recognition was the most investigated domain of SC. Overall, evidence revealed that currently available PRSs for mental disorders do not explain variation in SC performances. To enhance the understanding of mechanisms underlying SC in mental disorders, future research should focus on the development of transdiagnostic PRSs, study their interaction with environmental risk factors, and standardize outcome measurement.
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Affiliation(s)
- Laura Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Italy; Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Italy.
| | - Alessandro Rodolico
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Italy
| | - Miriam Martinez
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Italy
| | - Clarissa Fichera
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Italy
| | - Bochao D Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Ilaria Basadonne
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
| | - Carmen Concerto
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Italy
| | - Eugenio Aguglia
- Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Italy
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
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10
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Rammos A, Kirov G, Hubbard L, Walters JTR, Holmans P, Owen MJ, O'Donovan MC, Rees E. Family-based analysis of the contribution of rare and common genetic variants to school performance in schizophrenia. Mol Psychiatry 2023; 28:2081-2087. [PMID: 36914811 PMCID: PMC10575776 DOI: 10.1038/s41380-023-02013-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/15/2023] [Accepted: 02/22/2023] [Indexed: 03/16/2023]
Abstract
Impaired cognition in schizophrenia is associated with worse functional outcomes. While genetic factors are known to contribute to variation in cognition in schizophrenia, few rare coding variants with strong effects have been identified, and the relative effects from de novo, inherited and non-transmitted alleles are unknown. We used array and exome sequencing data from 656 proband-parent trios to examine the contribution of common and rare variants to school performance, and by implication cognitive function, in schizophrenia. Parental transmission of common alleles contributing to higher educational attainment (p value = 0.00015; OR = 2.63) and intelligence (p value = 0.00009; OR = 2.80), but not to schizophrenia, were associated with higher proband school performance. No significant effects were seen for non-transmitted parental common alleles. Probands with lower school performance were enriched for damaging de novo coding variants in genes associated with developmental disorders (DD) (p value = 0.00026; OR = 11.6). Damaging, ultra-rare coding variants in DD genes that were transmitted or non-transmitted from parents, had no effects on school performance. Among probands with lower school performance, those with damaging de novo coding variants in DD genes had a higher rate of comorbid mild intellectual disability (p value = 0.0002; OR = 15.6). Overall, we provide evidence for rare and common genetic contributions to school performance in schizophrenia. The strong effects for damaging de novo coding variants in DD genes provide further evidence that cognitive impairment in schizophrenia has a shared aetiology with developmental disorders. Furthermore, we report no evidence in this sample that non-transmitted parental common alleles for cognitive traits contributed to school performance in schizophrenia via indirect effects on the environment.
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Affiliation(s)
- Alexandros Rammos
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
| | - George Kirov
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Leon Hubbard
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Peter Holmans
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Elliott Rees
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
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11
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Fusar-Poli L, Prachason T, Erzin G, Pries LK, Brondino N, Politi P, Delespaul P, Kenis G, Luykx JJ, Lin BD, Richards AL, Akdede B, Binbay T, Altınyazar V, Yalınçetin B, Gümüş-Akay G, Cihan B, Soygür H, Ulaş H, Cankurtaran EŞ, Kaymak SU, Mihaljevic MM, Andric-Petrovic S, Mirjanic T, Bernardo M, Mezquida G, Amoretti S, Bobes J, Saiz PA, García-Portilla MP, Sanjuan J, Escarti MJ, Santos JL, Jiménez-López E, Arrojo M, Carracedo A, López G, González-Peñas J, Parellada M, Maric NP, Atbaşoğlu C, Üçok A, Alptekin K, Saka MC, Arango C, O'Donovan M, van Os J, Rutten BP, Guloksuz S. Examining the association between exposome score for schizophrenia and cognition in schizophrenia, siblings, and healthy controls: Results from the EUGEI study. Psychiatry Res 2023; 323:115184. [PMID: 37015164 DOI: 10.1016/j.psychres.2023.115184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 03/23/2023] [Accepted: 03/26/2023] [Indexed: 04/06/2023]
Abstract
BACKGROUND People with schizophrenia spectrum disorders (SSD) frequently present cognitive impairments. Here, we investigated whether the exposome score for schizophrenia (ES-SCZ) - a cumulative environmental exposure score - was associated with impairments of neurocognition, social cognition, and perception in patients with SSD, their unaffected siblings, and healthy controls. METHODS This cross-sectional sample consisted of 1200 patients, 1371 siblings, and 1564 healthy controls. Neurocognition, social cognition, and perception were assesed using a short version of the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III), the Degraded Facial Affect Recognition Task (DFAR), and the Benton Facial Recognition Test (BFR), respectively. Regression models were used to analyze the association between ES-SCZ and cognitive domains in each group. RESULTS There were no statistically significant associations between ES-SCZ and cognitive domains in SSD. ES-SCZ was negatively associated with T-score of cognition in siblings (B=-0.40, 95% CI -0.76 to -0.03) and healthy controls (B=-0.63, 95% CI -1.06 to -0.21). Additionally, ES-SCZ was positively associated with DFAR-total in siblings (B=0.83, 95% CI 0.26 to 1.40). Sensitivity analyses excluding cannabis use history from ES-SCZ largely confirmed the main findings. CONCLUSIONS Longitudinal cohorts may elucidate how environmental exposures influence the onset and course of cognitive impairments in trans-syndromic psychosis spectrum.
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Affiliation(s)
- Laura Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Thanavadee Prachason
- Department of Psychiatry, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Gamze Erzin
- Department of Psychiatry, Health Science University, Dışkapı Yıldırım Beyazıt Training and Research Hospital, Ankara, Turkey; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Lotta-Katrin Pries
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Natascia Brondino
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Pierluigi Politi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Philippe Delespaul
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands; Mondriaan Mental Health Centre, Maastricht/Heerlen, The Netherlands
| | - Gunter Kenis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Centre, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands; Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; GGNet Mental Health, Apeldoorn, The Netherlands
| | - Bochao D Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands; Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Alexander L Richards
- Cardiff University Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Berna Akdede
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Tolga Binbay
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Vesile Altınyazar
- Department of Psychiatry, Faculty of Medicine, Adnan Menderes University, Aydin, Turkey
| | - Berna Yalınçetin
- Department of Neuroscience, Graduate School of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Güvem Gümüş-Akay
- Department of Physiology, School of Medicine, Ankara University, Ankara, Turkey; Brain Research Center, Ankara University, Ankara, Turkey; Neuroscience and Neurotechnology Center of Excellence (NÖROM), Ankara, Turkey
| | - Burçin Cihan
- Department of Psychology, Middle East Technical University, Ankara, Turkey
| | - Haldun Soygür
- Turkish Federation of Schizophrenia Associations, Ankara, Turkey
| | - Halis Ulaş
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | | | | | - Marina M Mihaljevic
- University of Belgrade, Faculty of Medicine, Belgrade, Serbia; Clinic for Psychiatry, University Clinical Center of Serbia, Belgrade, Serbia
| | - Sanja Andric-Petrovic
- University of Belgrade, Faculty of Medicine, Belgrade, Serbia; Institute of Mental Health, Belgrade, Serbia
| | - Tijana Mirjanic
- Special Hospital for Psychiatric Disorders Kovin, Kovin, Serbia
| | - Miguel Bernardo
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
| | - Gisela Mezquida
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
| | - Silvia Amoretti
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain
| | - Julio Bobes
- Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain; Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo, Spain; Mental Health Services of Principado de Asturias, Oviedo, Spain
| | - Pilar A Saiz
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain; Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo, Spain; Mental Health Services of Principado de Asturias, Oviedo, Spain
| | - Maria Paz García-Portilla
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain; Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo, Spain; Mental Health Services of Principado de Asturias, Oviedo, Spain
| | - Julio Sanjuan
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Psychiatry, Hospital Clínico Universitario de Valencia, School of Medicine, Universidad de Valencia, Valencia, Spain
| | - Maria Jose Escarti
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Psychiatry, Hospital Clínico Universitario de Valencia, School of Medicine, Universidad de Valencia, Valencia, Spain
| | - José Luis Santos
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Psychiatry, Hospital Virgen de la Luz, Cuenca, Spain
| | - Estela Jiménez-López
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Health and Social Research Center, Universidad de Castilla-La Mancha, Cuenca, Spain
| | - Manuel Arrojo
- Department of Psychiatry, Instituto de Investigación Sanitaria, Complejo Hospitalario Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Angel Carracedo
- Grupo de Medicina Genómica, Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Universidad de Santiago de Compostela, Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica (SERGAS), IDIS, Santiago de Compostela, Spain
| | - Gonzalo López
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Javier González-Peñas
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Mara Parellada
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nadja P Maric
- University of Belgrade, Faculty of Medicine, Belgrade, Serbia; Institute of Mental Health, Belgrade, Serbia
| | - Cem Atbaşoğlu
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | - Alp Üçok
- Department of Psychiatry, Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Köksal Alptekin
- Department of Psychiatry, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey; Department of Psychiatry, Faculty of Medicine, Adnan Menderes University, Aydin, Turkey
| | - Meram Can Saka
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | - Celso Arango
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Michael O'Donovan
- Cardiff University Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Jim van Os
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands; Department of Psychiatry, UMC Utrecht Brain Centre, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Bart Pf Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
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12
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McCutcheon RA, Keefe RSE, McGuire PK. Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment. Mol Psychiatry 2023; 28:1902-1918. [PMID: 36690793 PMCID: PMC10575791 DOI: 10.1038/s41380-023-01949-9] [Citation(s) in RCA: 50] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 01/03/2023] [Accepted: 01/06/2023] [Indexed: 01/25/2023]
Abstract
Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.
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Affiliation(s)
- Robert A McCutcheon
- Department of Psychiatry, University of Oxford, Oxford, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
- Oxford health NHS Foundation Trust, Oxford health NHS Foundation Trust, Oxford, UK.
| | - Richard S E Keefe
- Departments of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Philip K McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford health NHS Foundation Trust, Oxford health NHS Foundation Trust, Oxford, UK
- NIHR Oxford Health Biomedical Research Centre, Oxford, UK
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13
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Mallard TT, Grotzinger AD, Smoller JW. Examining the shared etiology of psychopathology with genome-wide association studies. Physiol Rev 2023; 103:1645-1665. [PMID: 36634217 PMCID: PMC9988537 DOI: 10.1152/physrev.00016.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/19/2022] [Accepted: 01/03/2023] [Indexed: 01/13/2023] Open
Abstract
Genome-wide association studies (GWASs) have ushered in a new era of reproducible discovery in psychiatric genetics. The field has now identified hundreds of common genetic variants that are associated with mental disorders, and many of them influence more than one disorder. By advancing the understanding of causal biology underlying psychopathology, GWAS results are poised to inform the development of novel therapeutics, stratification of at-risk patients, and perhaps even the revision of top-down classification systems in psychiatry. Here, we provide a concise review of GWAS findings with an emphasis on findings that have elucidated the shared genetic etiology of psychopathology, summarizing insights at three levels of analysis: 1) genome-wide architecture; 2) networks, pathways, and gene sets; and 3) individual variants/genes. Three themes emerge from these efforts. First, all psychiatric phenotypes are heritable, highly polygenic, and influenced by many pleiotropic variants with incomplete penetrance. Second, GWAS results highlight the broad etiological roles of neuronal biology, system-wide effects over localized effects, and early neurodevelopment as a critical period. Third, many loci that are robustly associated with multiple forms of psychopathology harbor genes that are involved in synaptic structure and function. Finally, we conclude our review by discussing the implications that GWAS results hold for the field of psychiatry, as well as expected challenges and future directions in the next stage of psychiatric genetics.
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Affiliation(s)
- Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States
| | - Andrew D Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, United States
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States
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Cao H, Wei X, Zhang W, Xiao Y, Zeng J, Sweeney JA, Gong Q, Lui S. Cerebellar Functional Dysconnectivity in Drug-Naïve Patients With First-Episode Schizophrenia. Schizophr Bull 2023; 49:417-427. [PMID: 36200880 PMCID: PMC10016395 DOI: 10.1093/schbul/sbac121] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Cerebellar functional dysconnectivity has long been implicated in schizophrenia. However, the detailed dysconnectivity pattern and its underlying biological mechanisms have not been well-charted. This study aimed to conduct an in-depth characterization of cerebellar dysconnectivity maps in early schizophrenia. STUDY DESIGN Resting-state fMRI data were processed from 196 drug-naïve patients with first-episode schizophrenia and 167 demographically matched healthy controls. The cerebellum was parcellated into nine functional systems based on a state-of-the-art atlas, and seed-based connectivity for each cerebellar system was examined. The observed connectivity alterations were further associated with schizophrenia risk gene expressions using data from the Allen Human Brain Atlas. STUDY RESULTS Overall, we observed significantly increased cerebellar connectivity with the sensorimotor cortex, default-mode regions, ventral part of visual cortex, insula, and striatum. In contrast, decreased connectivity was shown chiefly within the cerebellum, and between the cerebellum and the lateral prefrontal cortex, temporal lobe, and dorsal visual areas. Such dysconnectivity pattern was statistically similar across seeds, with no significant group by seed interactions identified. Moreover, connectivity strengths of hypoconnected but not hyperconnected regions were significantly correlated with schizophrenia risk gene expressions, suggesting potential genetic underpinnings for the observed hypoconnectivity. CONCLUSIONS These findings suggest a common bidirectional dysconnectivity pattern across different cerebellar subsystems, and imply that such bidirectional alterations may relate to different biological mechanisms.
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Affiliation(s)
- Hengyi Cao
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Xia Wei
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Xiao
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jiaxin Zeng
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Qiyong Gong
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Su Lui
- Department of Radiology and National Clinical Research Center for Geriatrics, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
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Pedersen ML, Alnæs D, van der Meer D, Fernandez-Cabello S, Berthet P, Dahl A, Kjelkenes R, Schwarz E, Thompson WK, Barch DM, Andreassen OA, Westlye LT. Computational Modeling of the n-Back Task in the ABCD Study: Associations of Drift Diffusion Model Parameters to Polygenic Scores of Mental Disorders and Cardiometabolic Diseases. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:290-299. [PMID: 35427796 DOI: 10.1016/j.bpsc.2022.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 03/04/2022] [Accepted: 03/31/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Cognitive dysfunction is common in mental disorders and represents a potential risk factor in childhood. The nature and extent of associations between childhood cognitive function and polygenic risk for mental disorders is unclear. We applied computational modeling to gain insight into mechanistic processes underlying decision making and working memory in childhood and their associations with polygenic risk scores (PRSs) for mental disorders and comorbid cardiometabolic diseases. METHODS We used the drift diffusion model to infer latent computational processes underlying decision making and working memory during the n-back task in 3707 children ages 9 to 10 years from the Adolescent Brain Cognitive Development (ABCD) Study. Single nucleotide polymorphism-based heritability was estimated for cognitive phenotypes, including computational parameters, aggregated n-back task performance, and neurocognitive assessments. PRSs were calculated for Alzheimer's disease, bipolar disorder, coronary artery disease (CAD), major depressive disorder, obsessive-compulsive disorder, schizophrenia, and type 2 diabetes. RESULTS Heritability estimates of cognitive phenotypes ranged from 12% to 38%. Bayesian mixed models revealed that slower accumulation of evidence was associated with higher PRSs for CAD and schizophrenia. Longer nondecision time was associated with higher PRSs for Alzheimer's disease and lower PRSs for CAD. Narrower decision threshold was associated with higher PRSs for CAD. Load-dependent effects on nondecision time and decision threshold were associated with PRSs for Alzheimer's disease and CAD, respectively. Aggregated neurocognitive test scores were not associated with PRSs for any of the mental or cardiometabolic phenotypes. CONCLUSIONS We identified distinct associations between computational cognitive processes and genetic risk for mental illness and cardiometabolic disease, which could represent childhood cognitive risk factors.
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Affiliation(s)
- Mads L Pedersen
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Bjørknes College, Institute of Psychology, Oslo, Norway
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Sara Fernandez-Cabello
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pierre Berthet
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Rikka Kjelkenes
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Wesley K Thompson
- Division of Biostatistics and Department of Radiology, Population Neuroscience and Genetics Laboratory, University of California San Diego, La Jolla, California
| | - Deanna M Barch
- Departments of Psychological & Brain Sciences, Psychiatry, and Radiology, Washington University, St. Louis, Missouri
| | - Ole A Andreassen
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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A family-based study of genetic and epigenetic effects across multiple neurocognitive, motor, social-cognitive and social-behavioral functions. Behav Brain Funct 2022; 18:14. [PMID: 36457050 PMCID: PMC9714039 DOI: 10.1186/s12993-022-00198-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 09/09/2022] [Indexed: 12/03/2022] Open
Abstract
Many psychiatric and neurodevelopmental disorders are known to be heritable, but studies trying to elucidate the genetic architecture of such traits often lag behind studies of somatic traits and diseases. The reasons as to why relatively few genome-wide significant associations have been reported for such traits have to do with the sample sizes needed for the detection of small effects, the difficulty in defining and characterizing the phenotypes, partially due to overlaps in affected underlying domains (which is especially true for cognitive phenotypes), and the complex genetic architectures of the phenotypes, which are not wholly captured in traditional case-control GWAS designs. We aimed to tackle the last two issues by performing GWASs of eight quantitative neurocognitive, motor, social-cognitive and social-behavioral traits, which may be considered endophenotypes for a variety of psychiatric and neurodevelopmental conditions, and for which we employed models capturing both general genetic association and parent-of-origin effects, in a family-based sample comprising 402 children and their parents (mostly family trios). We identified 48 genome-wide significant associations across several traits, of which 3 also survived our strict study-wide quality criteria. We additionally performed a functional annotation of implicated genes, as most of the 48 associations were with variants within protein-coding genes. In total, our study highlighted associations with five genes (TGM3, CACNB4, ANKS1B, CSMD1 and SYNE1) associated with measures of working memory, processing speed and social behavior. Our results thus identify novel associations, including previously unreported parent-of-origin associations with relevant genes, and our top results illustrate new potential gene → endophenotype → disorder pathways.
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Fiksinski AM, Heung T, Corral M, Breetvelt EJ, Costain G, Marshall CR, Kahn RS, Vorstman JA, Bassett AS. Within-family influences on dimensional neurobehavioral traits in a high-risk genetic model. Psychol Med 2022; 52:3184-3192. [PMID: 33443009 PMCID: PMC9693655 DOI: 10.1017/s0033291720005279] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 12/08/2020] [Accepted: 12/17/2020] [Indexed: 01/05/2023]
Abstract
BACKGROUND Genotype-first and within-family studies can elucidate factors that contribute to psychiatric illness. Combining these approaches, we investigated the patterns of influence of parental scores, a high-impact variant, and schizophrenia on dimensional neurobehavioral phenotypes implicated in major psychiatric disorders. METHODS We quantitatively assessed cognitive (FSIQ, VIQ, PIQ), social, and motor functioning in 82 adult individuals with a de novo 22q11.2 deletion (22 with schizophrenia), and 148 of their unaffected parents. We calculated within-family correlations and effect sizes of the 22q11.2 deletion and schizophrenia, and used linear regressions to assess contributions to neurobehavioral measures. RESULTS Proband-parent intra-class correlations (ICC) were significant for cognitive measures (e.g. FSIQ ICC = 0.549, p < 0.0001), but not for social or motor measures. Compared to biparental scores, the 22q11.2 deletion conferred significant impairments for all phenotypes assessed (effect sizes -1.39 to -2.07 s.d.), strongest for PIQ. There were further decrements in those with schizophrenia. Regression models explained up to 37.7% of the variance in IQ and indicated that for proband IQ, parental IQ had larger effects than schizophrenia. CONCLUSIONS This study, for the first time, disentangles the impact of a high-impact variant from the modifying effects of parental scores and schizophrenia on relevant neurobehavioral phenotypes. The robust proband-parent correlations for cognitive measures, independent of the impact of the 22q11.2 deletion and of schizophrenia, suggest that, for certain phenotypes, shared genetic variation plays a significant role in expression. Molecular genetic and predictor studies are needed to elucidate shared factors and their contribution to psychiatric illness in this and other high-risk groups.
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Affiliation(s)
- Ania M. Fiksinski
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- The Dalglish Family 22q Clinic for 22q11.2 Deletion Syndrome, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
| | - Tracy Heung
- Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- The Dalglish Family 22q Clinic for 22q11.2 Deletion Syndrome, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
| | - Maria Corral
- The Dalglish Family 22q Clinic for 22q11.2 Deletion Syndrome, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
| | - Elemi J. Breetvelt
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Gregory Costain
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Christian R. Marshall
- Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Rene S. Kahn
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jacob A.S. Vorstman
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Anne S. Bassett
- Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- The Dalglish Family 22q Clinic for 22q11.2 Deletion Syndrome, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Toronto General Hospital Research Institute and Campbell Family Mental Health Research Institute, Toronto, Ontario, Canada
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Mitchell BL, Hansell NK, McAloney K, Martin NG, Wright MJ, Renteria ME, Grasby KL. Polygenic influences associated with adolescent cognitive skills. INTELLIGENCE 2022. [DOI: 10.1016/j.intell.2022.101680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Greenwood TA. Genetic Influences on Cognitive Dysfunction in Schizophrenia. Curr Top Behav Neurosci 2022; 63:291-314. [PMID: 36029459 DOI: 10.1007/7854_2022_388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Schizophrenia is a severe and debilitating psychotic disorder that is highly heritable and relatively common in the population. The clinical heterogeneity associated with schizophrenia is substantial, with patients exhibiting a broad range of deficits and symptom severity. Large-scale genomic studies employing a case-control design have begun to provide some biological insight. However, this strategy combines individuals with clinically diverse symptoms and ignores the genetic risk that is carried by many clinically unaffected individuals. Consequently, the majority of the genetic architecture underlying schizophrenia remains unexplained, and the pathways by which the implicated variants contribute to the clinically observable signs and symptoms are still largely unknown. Parsing the complex, clinical phenotype of schizophrenia into biologically relevant components may have utility in research aimed at understanding the genetic basis of liability. Cognitive dysfunction is a hallmark symptom of schizophrenia that is associated with impaired quality of life and poor functional outcome. Here, we examine the value of quantitative measures of cognitive dysfunction to objectively target the underlying neurobiological pathways and identify genetic variants and gene networks contributing to schizophrenia risk. For a complex disorder, quantitative measures are also more efficient than diagnosis, allowing for the identification of associated genetic variants with fewer subjects. Such a strategy supplements traditional analyses of schizophrenia diagnosis, providing the necessary biological insight to help translate genetic findings into actionable treatment targets. Understanding the genetic basis of cognitive dysfunction in schizophrenia may thus facilitate the development of novel pharmacological and procognitive interventions to improve real-world functioning.
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Affiliation(s)
- Tiffany A Greenwood
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
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20
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Karcher NR, Merchant J, Pine J, Kilciksiz CM. Cognitive Dysfunction as a Risk Factor for Psychosis. Curr Top Behav Neurosci 2022; 63:173-203. [PMID: 35989398 DOI: 10.1007/7854_2022_387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The current chapter summarizes recent evidence for cognition as a risk factor for the development of psychosis, including the range of cognitive impairments that exist across the spectrum of psychosis risk symptoms. The chapter examines several possible theories linking cognitive deficits with the development of psychotic symptoms, including evidence that cognitive deficits may be an intermediate risk factor linking genetic and/or neural metrics to psychosis spectrum symptoms. Although there is not strong evidence for unique cognitive markers associated specifically with psychosis compared to other forms of psychopathology, psychotic disorders are generally associated with the greatest severity of cognitive deficits. Cognitive deficits precede the development of psychotic symptoms and may be detectable as early as childhood. Across the psychosis spectrum, both the presence and severity of psychotic symptoms are associated with mild to moderate impairments across cognitive domains, perhaps most consistently for language, cognitive control, and working memory domains. Research generally indicates the size of these cognitive impairments worsens as psychosis symptom severity increases. The chapter points out areas of unclarity and unanswered questions in each of these areas, including regarding the mechanisms contributing to the association between cognition and psychosis, the timing of deficits, and whether any cognitive systems can be identified that function as specific predictors of psychosis risk symptoms.
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Affiliation(s)
- Nicole R Karcher
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
| | - Jaisal Merchant
- Department of Brain and Psychological Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Jacob Pine
- Department of Brain and Psychological Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Can Misel Kilciksiz
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
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Genetic variations in evolutionary accelerated regions disrupt cognition in schizophrenia. Psychiatry Res 2022; 314:114586. [PMID: 35623238 PMCID: PMC10150587 DOI: 10.1016/j.psychres.2022.114586] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 04/03/2022] [Accepted: 04/30/2022] [Indexed: 02/03/2023]
Abstract
Cognition is believed to be a product of human evolution, while schizophrenia is ascribed as the by-product with cognitive impairment as it's genetically mediated endophenotype. Genomic loci associated with these traits are enriched with recent evolutionary markers such as Human accelerated regions (HARs). HARs are markedly different in humans since their divergence with chimpanzees and mostly regulate gene expression by binding to transcription factors and/or modulating chromatin interactions. We hypothesize that variants within HARs may alter such functions and thus contribute to disease pathogenesis. 49 systematically prioritized variants from 2737 genome-wide HARs were genotyped in a north-Indian schizophrenia cohort (331 cases, 235 controls). Six variants were significantly associated with cognitive impairment in schizophrenia, thirteen with general cognition in healthy individuals. These variants were mapped to 122 genes; predicted to alter 79 transcription factors binding sites and overlapped with promoters, enhancers and/or repressors. These genes and TFs are implicated in neurocognitive phenotypes, autism, schizophrenia and bipolar disorders; a few are targets of common or repurposable antipsychotics suggesting their draggability; and enriched for immune response and brain developmental pathways. Immune response has been more strongly targeted by natural selection during human evolution and has a prominent role in neurodevelopment. Thus, its disruption may have deleterious consequences for neuronal and cognitive functions. Importantly, among the 15 associated SNPs, 12 showed association in several independent GWASs of different neurocognitive functions. Further analysis of HARs may be valuable to understand their role in cognition biology and identify improved therapeutics for schizophrenia.
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Kuo SS, Musket CW, Rupert PE, Almasy L, Gur RC, Prasad KM, Roalf DR, Gur RE, Nimgaonkar VL, Pogue-Geile MF. Age-dependent patterns of schizophrenia genetic risk affect cognition. Schizophr Res 2022; 246:39-48. [PMID: 35709646 DOI: 10.1016/j.schres.2022.05.012] [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: 10/28/2021] [Revised: 03/15/2022] [Accepted: 05/15/2022] [Indexed: 11/15/2022]
Abstract
Cognition shares substantial genetic overlap with schizophrenia, yet it remains unclear whether such genetic effects become significant during developmental periods of elevated risk for schizophrenia, such as the peak age of onset. We introduce an investigative framework integrating epidemiological, developmental, and genetic approaches to determine whether genetic effects shared between schizophrenia and cognition are significant across periods of differing risk for schizophrenia onset, and whether these effects are shared with depression. 771 European-American participants, including 636 (ages 15-84 years) from families with at least two first-degree relatives with schizophrenia and 135 unrelated controls, were divided into three age-risk groups based on ages relative to epidemiological age of onset patterns for schizophrenia: Pre-Peak (before peak age-of-onset: 15 to 22 years), Post-Peak (after peak age-of-onset: 23-42 years), and Plateau (during plateau of age-of-onset: over 42 years). For general cognition and 11 specific cognitive traits, we estimated genetic correlations with schizophrenia and with depression within each age-risk group. Genetic effects shared between deficits in general cognition and schizophrenia were nonsignificant before peak age of onset, yet were high and significant after peak age of onset and during the plateau of onset. These age-dependent genetic effects were largely consistent across specific cognitive traits and not transdiagnostically shared with depression. Schizophrenia genetic effects appear to influence cognitive traits in an age-dependent manner, supporting late developmental and perhaps neurodegenerative models that hypothesize increased expression of schizophrenia risk genes during and after the peak age of risk. Our findings underscore the utility of cognitive traits for tracking schizophrenia genetic effects across the lifespan.
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Affiliation(s)
- Susan S Kuo
- Department of Psychology, University of Pittsburgh, United States of America; Stanley Center for Psychiatric Genetics, Broad Institute of MIT and Harvard, United States of America; Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, United States of America
| | - Christie W Musket
- Department of Psychology, University of Pittsburgh, United States of America
| | - Petra E Rupert
- Department of Psychology, University of Pittsburgh, United States of America
| | - Laura Almasy
- Department of Genetics, University of Pennsylvania, United States of America
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, United States of America
| | - Konasale M Prasad
- Department of Psychiatry, University of Pittsburgh, United States of America; Department of Bioengineering, University of Pittsburgh, United States of America; Veteran Affairs Pittsburgh Healthcare System, United States of America
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, United States of America
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, United States of America
| | - Vishwajit L Nimgaonkar
- Department of Psychiatry, University of Pittsburgh, United States of America; Department of Human Genetics, University of Pittsburgh, United States of America
| | - Michael F Pogue-Geile
- Department of Psychology, University of Pittsburgh, United States of America; Department of Psychiatry, University of Pittsburgh, United States of America.
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Sun J, Wang W, Zhang R, Duan H, Tian X, Xu C, Li X, Zhang D. Multivariate genome-wide association study of depression, cognition, and memory phenotypes and validation analysis identify 12 cross-ethnic variants. Transl Psychiatry 2022; 12:304. [PMID: 35907915 PMCID: PMC9338946 DOI: 10.1038/s41398-022-02074-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 07/15/2022] [Accepted: 07/19/2022] [Indexed: 11/10/2022] Open
Abstract
To date, little is known about the pleiotropic genetic variants among depression, cognition, and memory. The current research aimed to identify the potential pleiotropic single nucleotide polymorphisms (SNPs), genes, and pathways of the three phenotypes by conducting a multivariate genome-wide association study and an additional pleiotropy analysis among Chinese individuals and further validate the top variants in the UK Biobank (UKB). In the discovery phase, the participants were 139 pairs of dizygotic twins from the Qingdao Twins Registry. The genome-wide efficient mixed-model analysis identified 164 SNPs reaching suggestive significance (P < 1 × 10-5). Among them, rs3967317 (P = 1.21 × 10-8) exceeded the genome-wide significance level (P < 5 × 10-8) and was also demonstrated to be associated with depression and memory in pleiotropy analysis, followed by rs9863698, rs3967316, and rs9261381 (P = 7.80 × 10-8-5.68 × 10-7), which were associated with all three phenotypes. After imputation, a total of 457 SNPs reached suggestive significance. The top SNP chr6:24597173 was located in the KIAA0319 gene, which had biased expression in brain tissues. Genes and pathways related to metabolism, immunity, and neuronal systems demonstrated nominal significance (P < 0.05) in gene-based and pathway enrichment analyses. In the validation phase, 12 of the abovementioned SNPs reached the nominal significance level (P < 0.05) in the UKB. Among them, three SNPs were located in the KIAA0319 gene, and four SNPs were identified as significant expression quantitative trait loci in brain tissues. These findings may provide evidence for pleiotropic variants among depression, cognition, and memory and clues for further exploring the shared genetic pathogenesis of depression with Alzheimer's disease.
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Affiliation(s)
- Jing Sun
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
| | - Ronghui Zhang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Shibei District, Qingdao, Shandong Province, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Shibei District, Qingdao, Shandong Province, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Shibei District, Qingdao, Shandong Province, China
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao, Shandong Province, China.
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Yang Y, Su Y, Wei G, Kang Z, Lu Z, Liao Y, Lu T, Yan H, Yue W, Qin Y, Zhang Y. Association of NKAPL rs1635 With Cognitive Function in Early-Onset Schizophrenia. Front Genet 2022; 13:941171. [PMID: 35801084 PMCID: PMC9253766 DOI: 10.3389/fgene.2022.941171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 06/01/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND: Schizophrenia is a severe mental disorder with high heritability, and cognitive dysfunction is one of the core features. Growing evidence suggests the genetic risk of schizophrenia may contribute to cognitive impairments. The variant rs1635 (nucleotide sequence: c.455C>A; amino acid sequence: T152N) located on the (NFKB activating protein like) NKAPL gene confers risk for schizophrenia and might play a role in the neurodevelopmental process, which is particularly relevant to cognitive function. However, the relationship between rs1635 and cognitive function remains unclear. METHODS: A total of 130 patients with early-onset schizophrenia (EOS) and 300 patients with adult-onset schizophrenia (AOS) of Han Chinese were recruited and underwent neurocognitive tests by using the MATRICS Consensus Cognitive Battery (MCCB). The NKAPL rs1635 was genotyped by using DNA sequencing. The peripheral blood NKAPL mRNA expression level was examined in 152T or 152N carriers (n = 20) in EOS patients, by using the qRT-PCR. The phosphorylation level of NAKPL T152N polymorphism was detected by cell experiments. In utero electroporation of mouse embryos was examined to explore the effect of Nkapl on neuronal migration. RESULTS: Compared with rs1635 AA and AC carriers, CC (the CC genotype encodes the protein NKAPL-152T) carriers of EOS patients performed better in cognitive domain of speed of processing (t = 2.644, p = 0.009), trail making test (t = 2.221, p = 0.028) and category fluency (t = 2.578, p = 0.011). However, patients with AOS exhibited no significant differences in seven domains among the three genotype groups. There were no significant differences in cognitive performance between EOS and AOS. In EOS patients, NKAPL mRNA level in NKAPL-152N carriers is significantly lower than that of NKAPL-152T carriers. The phosphorylation level of NKAPL-152N is significantly decreased compared to NKAPL-152T. In utero electroporation showed that Nkapl deletion impairs the embryonic radial migration process. CONCLUSION: The present study found that NKAPL rs1635 was associated with cognitive impairments and peripheral blood mRNA expression level in EOS patients. The NKAPL full-length protein is required for embryonic cortical neuronal migration. The phosphorylation level of NKAPL-152N is significantly decreased. The NKAPL T152N may affect the NAKPL mRNA expression level and embryonic cortical neuronal migration by regulating the NAKPL protein phosphorylation. These data suggest that NKAPL rs1635 affects cognitive function by regulating early brain development in early-onset schizophrenia.
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Affiliation(s)
- Yang Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yi Su
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Guiming Wei
- Department of Neurology, Shandong Daizhuang Hospital, Jining, China
| | - Zhewei Kang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Zhe Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yundan Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Tianlan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hao Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Ying Qin
- The Second People’s Hospital of Guizhou Province, Guiyang, China
- *Correspondence: Ying Qin, ; Yuyanan Zhang,
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- *Correspondence: Ying Qin, ; Yuyanan Zhang,
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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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Prasad KM, Gertler J, Tollefson S, Wood JA, Roalf D, Gur RC, Gur RE, Almasy L, Pogue-Geile MF, Nimgaonkar VL. Heritable anisotropy associated with cognitive impairments among patients with schizophrenia and their non-psychotic relatives in multiplex families. Psychol Med 2022; 52:989-1000. [PMID: 32878667 PMCID: PMC8218223 DOI: 10.1017/s0033291720002883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND To test the functional implications of impaired white matter (WM) connectivity among patients with schizophrenia and their relatives, we examined the heritability of fractional anisotropy (FA) measured on diffusion tensor imaging data acquired in Pittsburgh and Philadelphia, and its association with cognitive performance in a unique sample of 175 multigenerational non-psychotic relatives of 23 multiplex schizophrenia families and 240 unrelated controls (total = 438). METHODS We examined polygenic inheritance (h2r) of FA in 24 WM tracts bilaterally, and also pleiotropy to test whether heritability of FA in multiple WM tracts is secondary to genetic correlation among tracts using the Sequential Oligogenic Linkage Analysis Routines. Partial correlation tests examined the correlation of FA with performance on eight cognitive domains on the Penn Computerized Neurocognitive Battery, controlling for age, sex, site and mother's education, followed by multiple comparison corrections. RESULTS Significant total additive genetic heritability of FA was observed in all three-categories of WM tracts (association, commissural and projection fibers), in total 33/48 tracts. There were significant genetic correlations in 40% of tracts. Diagnostic group main effects were observed only in tracts with significantly heritable FA. Correlation of FA with neurocognitive impairments was observed mainly in heritable tracts. CONCLUSIONS Our data show significant heritability of all three-types of tracts among relatives of schizophrenia. Significant heritability of FA of multiple tracts was not entirely due to genetic correlations among the tracts. Diagnostic group main effect and correlation with neurocognitive performance were mainly restricted to tracts with heritable FA suggesting shared genetic effects on these traits.
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Affiliation(s)
- KM Prasad
- Departments of Psychiatry and Bioengineering, University of Pittsburgh, VA Pittsburgh Healthcare System, Pittsburgh, PA
| | - J Gertler
- Departments of Psychiatry and Bioengineering, University of Pittsburgh, VA Pittsburgh Healthcare System, Pittsburgh, PA
| | - S Tollefson
- Departments of Psychiatry and Bioengineering, University of Pittsburgh, VA Pittsburgh Healthcare System, Pittsburgh, PA
| | - JA Wood
- Departments of Psychiatry and Bioengineering, University of Pittsburgh, VA Pittsburgh Healthcare System, Pittsburgh, PA
| | - D Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - RC Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - RE Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - L Almasy
- Department of Genetics, University of Pennsylvania, Philadelphia, PA
| | - MF Pogue-Geile
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA
| | - VL Nimgaonkar
- Departments of Psychiatry and Bioengineering, University of Pittsburgh, VA Pittsburgh Healthcare System, Pittsburgh, PA
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, PA
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Mapping normative trajectories of cognitive function and its relation to psychopathology symptoms and genetic risk in youth. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 3:255-263. [PMID: 37124356 PMCID: PMC10140446 DOI: 10.1016/j.bpsgos.2022.01.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 12/08/2021] [Accepted: 01/16/2022] [Indexed: 12/19/2022] Open
Abstract
Background Adolescence hosts a sharp increase in the incidence of mental disorders. The prodromal phases are often characterized by cognitive deficits that predate disease onset by several years. Characterization of cognitive performance in relation to normative trajectories may have value for early risk assessment and monitoring. Methods Youth aged 8 to 21 years (N = 6481) from the Philadelphia Neurodevelopmental Cohort were included. Performance scores from a computerized neurocognitive battery were decomposed using principal component analysis, yielding a general cognitive score. Items reflecting various aspects of psychopathology from self-report questionnaires and collateral caregiver information were decomposed using independent component analysis, providing individual domain scores. Using normative modeling and Bayesian statistics, we estimated normative trajectories of cognitive function and tested for associations between cognitive deviance and psychopathological domain scores. In addition, we tested for associations with polygenic scores for mental and behavioral disorders often involving cognition, including schizophrenia, bipolar disorder, attention-deficit/hyperactivity disorder, and Alzheimer's disease. Results More negative normative cognitive deviations were associated with higher general psychopathology burden and domains reflecting positive and prodromal psychosis, attention problems, norm-violating behavior, and anxiety. In addition, better performance was associated with higher joint burden of depression, suicidal ideation, and negative psychosis symptoms. The analyses revealed no evidence for associations with polygenic scores. Conclusions Our results show that cognitive performance is associated with general and specific domains of psychopathology in youth. These findings support the close links between cognition and psychopathology in youth and highlight the potential of normative modeling for early risk assessment.
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A scoping review and comparison of approaches for measuring genetic heterogeneity in psychiatric disorders. Psychiatr Genet 2022; 32:1-8. [PMID: 34694248 DOI: 10.1097/ypg.0000000000000304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
An improved understanding of genetic etiological heterogeneity in a psychiatric condition may help us (a) isolate a neurophysiological 'final common pathway' by identifying its upstream genetic origins and (b) facilitate characterization of the condition's phenotypic variation. This review aims to identify existing genetic heterogeneity measurements in the psychiatric literature and provides a conceptual review of their mechanisms, limitations, and assumptions. The Scopus database was searched for studies that quantified genetic heterogeneity or correlation of psychiatric phenotypes with human genetic data. Ninety studies were included. Eighty-seven reports quantified genetic correlation, five applied genomic structural equation modelling, three evaluated departure from the Hardy-Weinberg equilibrium at one or more loci, and two applied a novel approach known as MiXeR. We found no study that rigorously measured genetic etiological heterogeneity across a large number of markers. Developing such approaches may help better characterize the biological diversity of psychopathology.
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Association of polygenic risk for schizophrenia with fast sleep spindle density depends on pro-cognitive variants. Eur Arch Psychiatry Clin Neurosci 2022; 272:1193-1203. [PMID: 35723738 PMCID: PMC9508216 DOI: 10.1007/s00406-022-01435-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 05/15/2022] [Indexed: 11/14/2022]
Abstract
Cognitive impairment is a common feature in schizophrenia and the strongest prognostic factor for long-term outcome. Identifying a trait associated with the genetic background for cognitive outcome in schizophrenia may aid in a deeper understanding of clinical disease subtypes. Fast sleep spindles may represent such a biomarker as they are strongly genetically determined, associated with cognitive functioning and impaired in schizophrenia and unaffected relatives. We measured fast sleep spindle density in 150 healthy adults and investigated its association with a genome-wide polygenic score for schizophrenia (SCZ-PGS). The association between SCZ-PGS and fast spindle density was further characterized by stratifying it to the genetic background of intelligence. SCZ-PGS was positively associated with fast spindle density. This association mainly depended on pro-cognitive genetic variants. Our results strengthen the evidence for a genetic background of spindle abnormalities in schizophrenia. Spindle density might represent an easily accessible marker for a favourable cognitive outcome which should be further investigated in clinical samples.
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Jones HJ, Hammerton G, McCloud T, Hines LA, Wright C, Gage SH, Holmans P, Jones PB, Smith GD, Linden DEJ, O'Donovan MC, Owen MJ, Walters JT, Munafò MR, Heron J, Zammit S. Examining pathways between genetic liability for schizophrenia and patterns of tobacco and cannabis use in adolescence. Psychol Med 2022; 52:132-139. [PMID: 32515721 PMCID: PMC7614952 DOI: 10.1017/s0033291720001798] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND It is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies. METHODS Associations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes. RESULTS The schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses. CONCLUSIONS Our study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.
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Affiliation(s)
- Hannah J. Jones
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
- NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Gemma Hammerton
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
| | - Tayla McCloud
- Division of Psychiatry, University College London, London, UK
| | - Lindsey A. Hines
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
| | - Caroline Wright
- Population Health Sciences, Bristol Medical School, University of Bristol, UK
| | - Suzanne H. Gage
- Department of Psychological Sciences, University of Liverpool, Liverpool, UK
| | - Peter Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
| | - David E. J. Linden
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Michael C. O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Michael J. Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - James T. Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Marcus R. Munafò
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, School of Psychological Science, University of Bristol, UK
| | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
| | - Stanley Zammit
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
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Sex-specific effects of polygenic risk for schizophrenia on lifespan cognitive functioning in healthy individuals. Transl Psychiatry 2021; 11:520. [PMID: 34635642 PMCID: PMC8505489 DOI: 10.1038/s41398-021-01649-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/16/2021] [Accepted: 09/27/2021] [Indexed: 12/13/2022] Open
Abstract
Polygenic risk for schizophrenia has been associated with lower cognitive ability and age-related cognitive change in healthy individuals. Despite well-established neuropsychological sex differences in schizophrenia patients, genetic studies on sex differences in schizophrenia in relation to cognitive phenotypes are scarce. Here, we investigated whether the effect of a polygenic risk score (PRS) for schizophrenia on childhood, midlife, and late-life cognitive function in healthy individuals is modified by sex, and if PRS is linked to accelerated cognitive decline. Using a longitudinal data set from healthy individuals aged 25-100 years (N = 1459) spanning a 25-year period, we found that PRS was associated with lower cognitive ability (episodic memory, semantic memory, visuospatial ability), but not with accelerated cognitive decline. A significant interaction effect between sex and PRS was seen on cognitive task performance, and sex-stratified analyses showed that the effect of PRS was male-specific. In a sub-sample, we observed a male-specific effect of the PRS on school performance at age 12 (N = 496). Our findings of sex-specific effects of schizophrenia genetics on cognitive functioning across the lifespan indicate that the effects of underlying disease genetics on cognitive functioning is dependent on biological processes that differ between the sexes.
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Eum S, Hill SK, Alliey-Rodriguez N, Stevenson JM, Rubin LH, Lee AM, Mills LJ, Reilly JL, Lencer R, Keedy SK, Ivleva E, Keefe RSE, Pearlson GD, Clementz BA, Tamminga CA, Keshavan MS, Gershon ES, Sweeney JA, Bishop JR. Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders. Neuropsychopharmacology 2021; 46:1802-1810. [PMID: 34145405 PMCID: PMC8358015 DOI: 10.1038/s41386-021-01057-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 05/17/2021] [Accepted: 06/03/2021] [Indexed: 12/13/2022]
Abstract
Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.
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Affiliation(s)
- Seenae Eum
- grid.412555.20000 0001 0511 4494Department of Pharmacogenomics, Shenandoah University, Fairfax, VA USA
| | - S. Kristian Hill
- grid.262641.50000 0004 0388 7807Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL USA
| | - Ney Alliey-Rodriguez
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - James M. Stevenson
- grid.21107.350000 0001 2171 9311Division of Clinical Pharmacology, Department of Medicine, Johns Hopkins University, Baltimore, MD USA
| | - Leah H. Rubin
- grid.21107.350000 0001 2171 9311Departments of Neurology, Psychiatry, and Epidemiology, Johns Hopkins University, Baltimore, MD USA
| | - Adam M. Lee
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA
| | - Lauren J. Mills
- grid.17635.360000000419368657Masonic Cancer Center and Department of Pediatrics, University of Minnesota, Minneapolis, MN USA
| | - James L. Reilly
- grid.16753.360000 0001 2299 3507Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL USA
| | - Rebekka Lencer
- grid.5949.10000 0001 2172 9288Institute of Translational Psychiatry and Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Muenster, Muenster, Germany ,grid.4562.50000 0001 0057 2672Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Sarah K. Keedy
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - Elena Ivleva
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Richard S. E. Keefe
- grid.26009.3d0000 0004 1936 7961Department of Psychiatry, Duke University School of Medicine, Durham, NC USA
| | - Godfrey D. Pearlson
- grid.277313.30000 0001 0626 2712Departments of Psychiatry and Neuroscience, Yale School of Medicine, Olin Center, Institute of Living, Hartford Healthcare, Hartford, CT USA
| | - Brett A. Clementz
- grid.213876.90000 0004 1936 738XDepartment of Psychology, University of Georgia, Athens, GA USA
| | - Carol A. Tamminga
- grid.267313.20000 0000 9482 7121Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX USA
| | - Matcheri S. Keshavan
- grid.239395.70000 0000 9011 8547Beth Israel Deaconess Medical Center, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, Harvard Medical School, Boston, MA USA
| | - Elliot S. Gershon
- grid.170205.10000 0004 1936 7822Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL USA
| | - John A. Sweeney
- grid.413561.40000 0000 9881 9161Department of Psychiatry, University of Cincinnati Medical Center, Cincinnati, OH USA
| | - Jeffrey R. Bishop
- grid.17635.360000000419368657Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN USA ,grid.17635.360000000419368657Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN USA
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Valerio KE, Jonas KG, Perlman G, Bromet EJ, Kotov R. A comparison of cognitive performance in the Suffolk County cohort and their unaffected siblings. Psychiatry Res 2021; 303:114111. [PMID: 34284308 PMCID: PMC8409437 DOI: 10.1016/j.psychres.2021.114111] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 06/29/2021] [Accepted: 07/10/2021] [Indexed: 10/20/2022]
Abstract
People diagnosed with schizophrenia and other psychoses demonstrate impaired neuropsychological performance. Their unaffected siblings exhibit mild impairments relative to unrelated controls, suggesting genetic and shared environmental risk for psychosis account for some portion of cognitive impairments observed in cases. However, most sibling studies were conducted early in illness course. Studying cases and unaffected siblings later in life is valuable because diagnostic misclassification is common early in illness, possibly leading to spurious conclusions. This study compared neuropsychological performance of individuals with psychotic disorders (schizophrenia and other psychoses), their unaffected siblings, and controls. Assessments were conducted 20 years after case enrollment in the Suffolk County Mental Health Project, when siblings and controls were added to the protocol. Results showed individuals with schizophrenia and other psychoses performed worse than their matched siblings across domains. Relative to controls, siblings of participants with schizophrenia showed mild deficits in executive function and processing speed, while no significant differences were observed between siblings of those with other psychoses and controls. These findings suggest pre- and post-onset factors impact cognitive deficits in psychosis, but pre-onset factors are more salient in schizophrenia. Additionally, schizophrenia and other psychoses exist on a neurodevelopmental continuum, with schizophrenia being a more severe manifestation.
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Kowalec K, Lu Y, Sariaslan A, Song J, Ploner A, Dalman C, Hultman CM, Larsson H, Lichtenstein P, Sullivan PF. Increased schizophrenia family history burden and reduced premorbid IQ in treatment-resistant schizophrenia: a Swedish National Register and Genomic Study. Mol Psychiatry 2021; 26:4487-4495. [PMID: 31712719 PMCID: PMC9731609 DOI: 10.1038/s41380-019-0575-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 09/23/2019] [Accepted: 10/23/2019] [Indexed: 01/29/2023]
Abstract
A high proportion of those with schizophrenia experience treatment non-response, placing them at higher risk for mortality and suicide attempts, compared to treatment responders. The clinical, social, and economic burden of treatment-resistant schizophrenia (TRS) are substantial. Previous genomic and epidemiological studies of TRS were often limited by sample size or lack of comprehensive genomic data. We aimed to systematically understand the clinical, demographic, and genomic correlates of TRS using epidemiological and genetic epidemiological modelling in a Swedish national population sample (n = 24,706) and then in a subgroup with common variant genetic risk scores, rare copy-number variant burden, and rare exonic burden (n = 4936). Population-based analyses identified increasing schizophrenia family history to be significantly associated with TRS (highest quartile of familial burden vs. lowest: adjusted odds ratio (aOR): 1.31, P = 4.8 × 10-8). In males, a decrease of premorbid IQ of one standard deviation was significantly associated with greater risk of TRS (minimal aOR: 0.94, P = 0.002). In a subset of cases with extensive genomic data, we found no significant association between the genetic risk scores of four psychiatric disorders and two cognitive traits with TRS (schizophrenia genetic risk score: aOR = 1.07, P = 0.067). The association between copy number variant and rare variant burden measures and TRS did not reach the pre-defined statistical significance threshold (all P ≥ 0.005). In conclusion, direct measures of genomic risk were not associated with TRS; however, premorbid IQ in males and schizophrenia family history were significantly correlated with TRS and points to new insights into the architecture of TRS.
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Affiliation(s)
- Kaarina Kowalec
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, College of Pharmacy, University of Manitoba, Winnipeg, MB, Canada
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Amir Sariaslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jie Song
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Alexander Ploner
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Christina Dalman
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Christina M. Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Icahn School of Medicine, Department of Psychiatry, Mt. Sinai Hospital, New York, NY, USA
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, School of Medical Sciences, Örebo University, Örebo, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrick F. Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Martinelli A, Rice ML, Talcott JB, Diaz R, Smith S, Raza MH, Snowling MJ, Hulme C, Stein J, Hayiou-Thomas ME, Hawi Z, Kent L, Pitt SJ, Newbury DF, Paracchini S. A rare missense variant in the ATP2C2 gene is associated with language impairment and related measures. Hum Mol Genet 2021; 30:1160-1171. [PMID: 33864365 PMCID: PMC8188402 DOI: 10.1093/hmg/ddab111] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Revised: 04/09/2021] [Accepted: 04/12/2021] [Indexed: 01/02/2023] Open
Abstract
At least 5% of children present unexpected difficulties in expressing and understanding spoken language. This condition is highly heritable and often co-occurs with other neurodevelopmental disorders such as dyslexia and ADHD. Through an exome sequencing analysis, we identified a rare missense variant (chr16:84405221, GRCh38.p12) in the ATP2C2 gene. ATP2C2 was implicated in language disorders by linkage and association studies, and exactly the same variant was reported previously in a different exome sequencing study for language impairment (LI). We followed up this finding by genotyping the mutation in cohorts selected for LI and comorbid disorders. We found that the variant had a higher frequency in LI cases (1.8%, N = 360) compared with cohorts selected for dyslexia (0.8%, N = 520) and ADHD (0.7%, N = 150), which presented frequencies comparable to reference databases (0.9%, N = 24 046 gnomAD controls). Additionally, we observed that carriers of the rare variant identified from a general population cohort (N = 42, ALSPAC cohort) presented, as a group, lower scores on a range of reading and language-related measures compared to controls (N = 1825; minimum P = 0.002 for non-word reading). ATP2C2 encodes for an ATPase (SPCA2) that transports calcium and manganese ions into the Golgi lumen. Our functional characterization suggested that the rare variant influences the ATPase activity of SPCA2. Thus, our results further support the role of ATP2C2 locus in language-related phenotypes and pinpoint the possible effects of a specific rare variant at molecular level.
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Affiliation(s)
| | - Mabel L Rice
- Child Language Doctoral Program, University of Kansas, Lawrence, KS, USA
| | - Joel B Talcott
- Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, UK
| | - Rebeca Diaz
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Shelley Smith
- Department of Neurological Sciences, University of Nebraska Medical Center, Lincoln, NE, USA
| | | | - Margaret J Snowling
- Department of Experimental Psychology and St John's College, University of Oxford, Oxford, UK
| | - Charles Hulme
- Department of Education, University of Oxford, Oxford, UK
| | - John Stein
- Department of Physiology, University of Oxford, Oxford, UK
| | | | - Ziarih Hawi
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Lindsey Kent
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Samantha J Pitt
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Dianne F Newbury
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, UK
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Functional connectome-wide associations of schizophrenia polygenic risk. Mol Psychiatry 2021; 26:2553-2561. [PMID: 32127647 PMCID: PMC9557214 DOI: 10.1038/s41380-020-0699-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Revised: 02/15/2020] [Accepted: 02/20/2020] [Indexed: 01/29/2023]
Abstract
Schizophrenia is a highly heritable mental disorder characterized by functional dysconnectivity across the brain. However, the relationships between polygenic risk factors and connectome-wide neural mechanisms are unclear. Here, combining genetic and multiparadigm fMRI data of 623 healthy Caucasian adults drawn from the Human Connectome Project, we found that higher schizophrenia polygenic risk scores were significantly correlated with lower functional connectivity in a large-scale brain network primarily encompassing the visual system, default-mode system, and frontoparietal system. Such correlation was robustly observed across multiple fMRI paradigms, suggesting a brain-state-independent neural phenotype underlying individual genetic liability to schizophrenia. Moreover, using an independent clinical dataset acquired from the Consortium for Neuropsychiatric Phenomics, we further demonstrated that the connectivity of the identified network was reduced in patients with schizophrenia and significantly correlated with general cognitive ability. These findings provide the first evidence for connectome-wide associations of schizophrenia polygenic risk at the systems level and suggest that disrupted integration of sensori-cognitive information may be a hallmark of genetic effects on the brain that contributes to the pathogenesis of schizophrenia.
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Polygenic scores for schizophrenia and general cognitive ability: associations with six cognitive domains, premorbid intelligence, and cognitive composite score in individuals with a psychotic disorder and in healthy controls. Transl Psychiatry 2020; 10:416. [PMID: 33257657 PMCID: PMC7705731 DOI: 10.1038/s41398-020-01094-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 10/04/2020] [Accepted: 10/26/2020] [Indexed: 01/24/2023] Open
Abstract
Cognitive impairments are considered core features in schizophrenia and other psychotic disorders. Cognitive impairments are, to a lesser degree, also documented in healthy first-degree relatives. Although recent studies have shown (negative) genetic correlations between schizophrenia and general cognitive ability, the association between polygenic risk for schizophrenia and individual cognitive phenotypes remains unclear. We here investigated the association between a polygenic score for schizophrenia (SCZPGS) and six well-defined cognitive domains, in addition to a composite measure of cognitive ability and a measure of premorbid intellectual ability in 731 participants with a psychotic disorder and 851 healthy controls. We also investigated the association between a PGS for general cognitive ability (COGPGS) and the same cognitive domains in the same sample. We found no significant associations between the SCZPGS and any cognitive phenotypes, in either patients with a psychotic disorder or healthy controls. For COGPGS we observed stronger associations with cognitive phenotypes in healthy controls than in participants with psychotic disorders. In healthy controls, the association between COGPGS (at the p value threshold of ≥0.01) and working memory remained significant after Bonferroni correction (β = 0.12, p = 8.6 × 10-5). Altogether, the lack of associations between SCZPGS and COGPGS with cognitive performance in participants with psychotic disorders suggests that either environmental factors or unassessed genetic factors play a role in the development of cognitive impairments in psychotic disorders. Working memory should be further studied as an important cognitive phenotype.
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van Os J, Pries LK, Delespaul P, Kenis G, Luykx JJ, Lin BD, Richards AL, Akdede B, Binbay T, Altınyazar V, Yalınçetin B, Gümüş-Akay G, Cihan B, Soygür H, Ulaş H, Cankurtaran EŞ, Kaymak SU, Mihaljevic MM, Petrovic SA, Mirjanic T, Bernardo M, Cabrera B, Bobes J, Saiz PA, García-Portilla MP, Sanjuan J, Aguilar EJ, Santos JL, Jiménez-López E, Arrojo M, Carracedo A, López G, González-Peñas J, Parellada M, Maric NP, Atbaşoğlu C, Ucok A, Alptekin K, Saka MC, Arango C, O'Donovan M, Rutten BPF, Guloksuz S. Replicated evidence that endophenotypic expression of schizophrenia polygenic risk is greater in healthy siblings of patients compared to controls, suggesting gene-environment interaction. The EUGEI study. Psychol Med 2020; 50:1884-1897. [PMID: 31414981 DOI: 10.1017/s003329171900196x] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND First-degree relatives of patients with psychotic disorder have higher levels of polygenic risk (PRS) for schizophrenia and higher levels of intermediate phenotypes. METHODS We conducted, using two different samples for discovery (n = 336 controls and 649 siblings of patients with psychotic disorder) and replication (n = 1208 controls and 1106 siblings), an analysis of association between PRS on the one hand and psychopathological and cognitive intermediate phenotypes of schizophrenia on the other in a sample at average genetic risk (healthy controls) and a sample at higher than average risk (healthy siblings of patients). Two subthreshold psychosis phenotypes, as well as a standardised measure of cognitive ability, based on a short version of the WAIS-III short form, were used. In addition, a measure of jumping to conclusion bias (replication sample only) was tested for association with PRS. RESULTS In both discovery and replication sample, evidence for an association between PRS and subthreshold psychosis phenotypes was observed in the relatives of patients, whereas in the controls no association was observed. Jumping to conclusion bias was similarly only associated with PRS in the sibling group. Cognitive ability was weakly negatively and non-significantly associated with PRS in both the sibling and the control group. CONCLUSIONS The degree of endophenotypic expression of schizophrenia polygenic risk depends on having a sibling with psychotic disorder, suggestive of underlying gene-environment interaction. Cognitive biases may better index genetic risk of disorder than traditional measures of neurocognition, which instead may reflect the population distribution of cognitive ability impacting the prognosis of psychotic disorder.
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Affiliation(s)
- Jim van Os
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Psychosis Studies, Institute of Psychiatry, King's College London, King's Health Partners, London, UK
| | - Lotta-Katrin Pries
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Philippe Delespaul
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Gunter Kenis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Jurjen J Luykx
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Bochao D Lin
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Alexander L Richards
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Berna Akdede
- Department of Psychiatry, Dokuz Eylul University School of Medicine, Izmir, Turkey
| | - Tolga Binbay
- Department of Psychiatry, Dokuz Eylul University School of Medicine, Izmir, Turkey
| | - Vesile Altınyazar
- Department of Psychiatry, Faculty of Medicine, Adnan Menderes University, Aydin, Turkey
| | - Berna Yalınçetin
- Department of Neuroscience, Health Sciences Institute, Dokuz Eylul University, Izmir, Turkey
| | | | - Burçin Cihan
- Department of Psychology, Middle East Technical University, Çankaya, Ankara, Turkey
| | - Haldun Soygür
- Department of Psychiatry, School of Medicine, Dokuz Eylül University (discharged by decree 701 on July 8, 2018 because of signing "Peace Petition")
| | - Halis Ulaş
- Department of Psychiatry, School of Medicine, Dokuz Eylül University (discharged by decree 701 on July 8, 2018 because of signing "Peace Petition")
| | | | | | - Marina M Mihaljevic
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
- Clinic for Psychiatry CCS, Belgrade, Serbia
| | | | - Tijana Mirjanic
- Special Hospital for Psychiatric Disorders Kovin, Kovin, Serbia
| | - Miguel Bernardo
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
| | - Bibiana Cabrera
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
| | - Julio Bobes
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias, ISPA, Oviedo, Spain
- Mental Health Services of Principado de Asturias, SESPA, Oviedo, Spain
| | - Pilar A Saiz
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias, ISPA, Oviedo, Spain
- Mental Health Services of Principado de Asturias, SESPA, Oviedo, Spain
| | - María Paz García-Portilla
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Psychiatry, School of Medicine, University of Oviedo, Oviedo, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias, ISPA, Oviedo, Spain
- Mental Health Services of Principado de Asturias, SESPA, Oviedo, Spain
| | - Julio Sanjuan
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Hospital Clínico Universitario de Valencia, School of Medicine, Universidad de Valencia, INCLIVA, Valencia, Spain
| | - Eduardo J Aguilar
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Hospital Clínico Universitario de Valencia, School of Medicine, Universidad de Valencia, INCLIVA, Valencia, Spain
| | - José Luis Santos
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Psychiatry, Hospital Virgen de la Luz, Cuenca, Spain
| | - Estela Jiménez-López
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Universidad de Castilla-La Mancha, Health and Social Research Center, Cuenca, Spain
| | - Manuel Arrojo
- Department of Psychiatry, Instituto de Investigación Sanitaria (IDIS), Complejo Hospitalario Universitario de Santiago de Compostela, SERGAS, Santiago de Compostela, Spain
| | - Angel Carracedo
- Fundación Publica Galega de Medicina Xenómica, Hospital Clínico Universitario de Santiago de Compostela, Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - Gonzalo López
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Javier González-Peñas
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Mara Parellada
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nadja P Maric
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
- Clinic for Psychiatry CCS, Belgrade, Serbia
| | - Cem Atbaşoğlu
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | - Alp Ucok
- Department of Psychiatry, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey
| | - Köksal Alptekin
- Department of Psychiatry, Dokuz Eylul University School of Medicine, Izmir, Turkey
| | - Meram Can Saka
- Department of Psychiatry, School of Medicine, Ankara University, Ankara, Turkey
| | - Celso Arango
- Biomedical Research Networking Centre in Mental Health (CIBERSAM), Madrid, Spain
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Michael O'Donovan
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
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Koch E, Rosenthal B, Lundquist A, Chen CH, Kauppi K. Interactome overlap between schizophrenia and cognition. Schizophr Res 2020; 222:167-174. [PMID: 32546371 DOI: 10.1016/j.schres.2020.06.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 05/20/2020] [Accepted: 06/01/2020] [Indexed: 12/12/2022]
Abstract
Cognitive impairments constitute a core feature of schizophrenia, and a genetic overlap between schizophrenia and cognitive functioning in healthy individuals has been identified. However, due to the high polygenicity and complex genetic architecture of both traits, overlapping biological pathways have not yet been identified between schizophrenia and normal cognitive ability. Network medicine offers a framework to study underlying biological pathways through protein-protein interactions among risk genes. Here, established network-based methods were used to characterize the biological relatedness of schizophrenia and cognition by examining the genetic link between schizophrenia risk genes and genes associated with cognitive performance in healthy individuals, through the protein interactome. First, network separation showed a profound interactome overlap between schizophrenia risk genes and genes associated with cognitive performance (SAB = -0.22, z-score = -6.80, p = 5.38e-12). To characterize this overlap, network propagation was thereafter used to identify schizophrenia risk genes that are close to cognition-associated genes in the interactome network space (n = 140, of which 54 were part of the direct genetic overlap). Schizophrenia risk genes close to cognition were enriched for pathways including long-term potentiation and Alzheimer's disease, and included genes with a role in neurotransmitter systems important for cognitive functioning, such as glutamate and dopamine. These results pinpoint a subset of schizophrenia risk genes that are of particular interest for further examination in schizophrenia patient groups, of which some are druggable genes with potential as candidate targets for cognitive enhancing drugs.
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Affiliation(s)
- Elise Koch
- Umeå University, Department of Integrative Medical Biology, Sweden
| | - Brin Rosenthal
- University of California San Diego, Center for Computational Biology and Bioinformatics, United States of America
| | - Anders Lundquist
- Umeå University, Department of Statistics, School of Business, Economics and Statistics, Sweden
| | - Chi-Hua Chen
- University of California San Diego, Department of Radiology and Center for Multimodal Imaging and Genetics, United States of America
| | - Karolina Kauppi
- Umeå University, Department of Integrative Medical Biology, Sweden; Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Sweden.
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Shared polygenic risk for ADHD, executive dysfunction and other psychiatric disorders. Transl Psychiatry 2020; 10:182. [PMID: 32518222 PMCID: PMC7283259 DOI: 10.1038/s41398-020-00872-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 05/15/2020] [Accepted: 05/26/2020] [Indexed: 12/14/2022] Open
Abstract
Many psychiatric disorders are associated with impaired executive functioning (EF). The associated EF component varies by psychiatric disorders, and this variation might be due to genetic liability. We explored the genetic association between five psychiatric disorders and EF in clinically-recruited attention deficit hyperactivity disorder (ADHD) children using polygenic risk score (PRS) methodology. Genome-wide association study (GWAS) summary data for ADHD, major depressive disorder (MDD), schizophrenia (SZ), bipolar disorder (BIP) and autism were used to calculate the PRSs. EF was evaluated by the Stroop test for inhibitory control, the trail-making test for cognitive flexibility, and the digital span test for working memory in a Chinese ADHD cohort (n = 1147). Exploratory factor analysis of the three measures identified one principal component for EF (EF-PC). Linear regression models were used to analyze the association between each PRS and the EF measures. The role of EF measures in mediating the effects of the PRSs on ADHD symptoms was also analyzed. The result showed the PRSs for MDD, ADHD and BIP were all significantly associated with the EF-PC. For each EF component, the association results were different for the PRSs of the five psychiatric disorders: the PRSs for ADHD and MDD were associated with inhibitory control (adjusted P = 0.0183 and 0.0313, respectively), the PRS for BIP was associated with working memory (adjusted P = 0.0416), and the PRS for SZ was associated with cognitive flexibility (adjusted P = 0.0335). All three EF measures were significantly correlated with ADHD symptoms. In mediation analyses, the ADHD and MDD PRSs, which were associated with inhibitory control, had significant indirect effects on ADHD symptoms through the mediation of inhibitory control. These findings indicate that the polygenic risks for several psychiatric disorders influence specific executive dysfunction in children with ADHD. The results helped to clarify the relationship between risk genes of each mental disorder and the intermediate cognitive domain, which may further help elucidate the risk genes and motivate efforts to develop EF measures as a diagnostic marker and future treatment target.
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Polygenic analysis suggests the involvement of calcium signaling in executive function in schizophrenia patients. Eur Arch Psychiatry Clin Neurosci 2020; 270:425-431. [PMID: 30523404 DOI: 10.1007/s00406-018-0961-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 11/30/2018] [Indexed: 12/14/2022]
Abstract
Cognitive deficits are increasingly recognized as a core dimension rather than a consequence of schizophrenia (SCZ). The previous evidence supports the hypothesis of shared genetic factors between SCZ and cognitive ability. The objective of this study was to test whether and to what extent the variation of disease-relevant neurocognitive function in a sample of SCZ patients from the previous clinical interventional studies can be explained by SCZ polygenic risk scores (PRSs) or by hypothesis-driven and biomedical PRSs. The previous studies have described associations of the SNAP25 gene with cognition in SCZ. Likewise, the enrichment of several calcium signaling-related gene sets has been reported by genome-wide association studies (GWAS) in SCZ. Hypothesis-driven PRSs were calculated on the basis of the SNAP-25 interactome and also for genes regulated by phorbol myristate acetate (PMA), an activator of the signal transduction of protein kinase C (PKC) enzymes. In a cohort of 127 SCZ patients who had completed a comprehensive neurocognitive test battery as part of the previous antipsychotic intervention studies, we investigated the association between neurocognitive dimensions and PRSs. The PRS for SCZ and SNAP-25-associated genes could not explain the variance of neurocognition in this cohort. At a p value threshold of 0.05, the PRS for PMA was able to explain 2% of the variance in executive function (p = 0.05, uncorrected). The correlation between the PRS for PMA-regulated genes and cognition can give hints for further patient-derived cellular assays. In conclusion, incorporating biological information into PRSs and other en masse genetic analyses may help to close the gap between genetic vulnerability and the biological processes underlying neuropsychiatric diseases such as SCZ.
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Lyngstad SH, Bettella F, Aminoff SR, Athanasiu L, Andreassen OA, Faerden A, Melle I. Associations between schizophrenia polygenic risk and apathy in schizophrenia spectrum disorders and healthy controls. Acta Psychiatr Scand 2020; 141:452-464. [PMID: 32091622 DOI: 10.1111/acps.13167] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/16/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE Apathy is a central predictor of a poor functional outcome in schizophrenia. Schizophrenia polygenic risk scores (PRSs) are used to detect genetic associations to key clinical phenotypes in schizophrenia. We explored the associations between schizophrenia PRS and apathy levels in schizophrenia spectrum disorders (n = 281) and matched healthy controls (n = 298), and further how schizophrenia PRS contributed in predicting apathy when added to premorbid and clinical factors in the patient sample. METHOD Schizophrenia PRSs were computed for each participant. Apathy was assessed with the Apathy Evaluation Scale. Bivariate correlation analyses were used to investigate associations between schizophrenia PRS and apathy, and between apathy and premorbid and clinical factors. Multiple hierarchical regression analyses were employed to evaluate the contributions of clinical variables and schizophrenia PRS to apathy levels. RESULTS We found no significant associations between schizophrenia PRS and apathy in patients and healthy controls. Several premorbid and clinical characteristics significantly predicted apathy in patients, but schizophrenia PRS did not. CONCLUSION Since the PRSs are based on common genetic variants, our results do not preclude associations to other types of genetic factors. The results could also indicate that environmentally based biological or psychological factors contribute to apathy levels in schizophrenia.
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Affiliation(s)
- S H Lyngstad
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - F Bettella
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - S R Aminoff
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Early Intervention in Psychosis Advisory Unit for South East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - L Athanasiu
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - O A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - A Faerden
- Division of Mental Health and Addiction, Department of Acute Psychiatry, Oslo University Hospital, Oslo, Norway
| | - I Melle
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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Genetic liability to schizophrenia is negatively associated with educational attainment in UK Biobank. Mol Psychiatry 2020; 25:703-705. [PMID: 30610204 DOI: 10.1038/s41380-018-0328-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 06/22/2018] [Accepted: 07/09/2018] [Indexed: 11/08/2022]
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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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Mallet J, Le Strat Y, Dubertret C, Gorwood P. Polygenic Risk Scores Shed Light on the Relationship between Schizophrenia and Cognitive Functioning: Review and Meta-Analysis. J Clin Med 2020; 9:E341. [PMID: 31991840 PMCID: PMC7074036 DOI: 10.3390/jcm9020341] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 01/14/2020] [Accepted: 01/23/2020] [Indexed: 12/26/2022] Open
Abstract
Schizophrenia is a multifactorial disease associated with widespread cognitive impairment. Although cognitive deficits are one of the factors most strongly associated with functional impairment in schizophrenia (SZ), current treatment strategies hardly tackle these impairments. To develop more efficient treatment strategies in patients, a better understanding of their pathogenesis is needed. Recent progress in genetics, driven by large genome-wide association studies (GWAS) and the use of polygenic risk scores (PRS), has provided new insights about the genetic architecture of complex human traits, including cognition and SZ. Here, we review the recent findings examining the genetic links between SZ and cognitive functions in population-based samples as well as in participants with SZ. The performed meta-analysis showed a negative correlation between the polygenetic risk score of schizophrenia and global cognition (p < 0.001) when the samples rely on general and healthy participants, while no significant correlation was detected when the three studies devoted to schizophrenia patients were meta-analysed (p > 0.05). Our review and meta-analysis therefore argues against universal pleiotropy for schizophrenia alleles and cognition, since cognition in SZ patients would be underpinned by the same genetic factors than in the general population, and substantially independent of common variant liability to the disorder.
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Affiliation(s)
- Jasmina Mallet
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Yann Le Strat
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Caroline Dubertret
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Philip Gorwood
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
- GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
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Abstract
PURPOSE OF REVIEW We review recent progress in uncovering the complex genetic architecture of cognition, arising primarily from genome-wide association studies (GWAS). We explore the genetic correlations between cognitive performance and neuropsychiatric disorders, the genetic and environmental factors associated with age-related cognitive decline, and speculate about the future role of genomics in the understanding of cognitive processes. RECENT FINDINGS Improvements in genomic methods, and the increasing availability of large datasets via consortia cooperation, have led to a greater understanding of the role played by common and rare variants in the genomics of cognition, the highly polygenic basis of cognitive function and dysfunction, and the multiple biological processes involved. Recent research has aided in our understanding of the complex biological nature of genomics of cognition. Further development of data banks and techniques to analyze this data hold significant promise for understanding cognitive ability, and for treating cognitively related disability.
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Warland A, Kendall KM, Rees E, Kirov G, Caseras X. Schizophrenia-associated genomic copy number variants and subcortical brain volumes in the UK Biobank. Mol Psychiatry 2020; 25:854-862. [PMID: 30679740 PMCID: PMC7156345 DOI: 10.1038/s41380-019-0355-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 12/11/2018] [Accepted: 12/26/2018] [Indexed: 11/09/2022]
Abstract
Schizophrenia is a highly heritable disorder for which anatomical brain alterations have been repeatedly reported in clinical samples. Unaffected at-risk groups have also been studied in an attempt to identify brain changes that do not reflect reverse causation or treatment effects. However, no robust associations have been observed between neuroanatomical phenotypes and known genetic risk factors for schizophrenia. We tested subcortical brain volume differences between 49 unaffected participants carrying at least one of the 12 copy number variants associated with schizophrenia in UK Biobank and 9063 individuals who did not carry any of the 93 copy number variants reported to be pathogenic. Our results show that CNV carriers have reduced volume in some of the subcortical structures previously shown to be reduced in schizophrenia. Moreover, these associations partially accounted for the association between pathogenic copy number variants and cognitive impairment, which is one of the features of schizophrenia.
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Affiliation(s)
- Anthony Warland
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - Kimberley M. Kendall
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - Elliott Rees
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - George Kirov
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
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Mistry S, Escott-Price V, Florio AD, Smith DJ, Zammit S. Investigating associations between genetic risk for bipolar disorder and cognitive functioning in childhood. J Affect Disord 2019; 259:112-120. [PMID: 31445336 DOI: 10.1016/j.jad.2019.08.040] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 07/01/2019] [Accepted: 08/17/2019] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Identifying phenotypic manifestations of genetic risk for bipolar disorder (BD) in childhood could increase our understanding of aetiological mechanisms. AIMS To examine whether BD genetic risk is associated with childhood (age 8 years) cognitive function. METHODS Using data from the Avon Longitudinal Study of Parents and Children, we examined associations between polygenic risk scores for BD (BD-PRS) derived using Psychiatric Genomics Consortium summary data at p-thresholds (PT) ≤0.01 (primary) and ≤0.5 (secondary) and several cognitive domains (sample sizes 5,613 to 5,936). We also examined whether associations were due to SNPs that have shared risk effects on schizophrenia (SZ). RESULTS At PT≤0.01, the BD-PRS was associated with poorer executive functioning (ß= -0.03, 95%CI -0.06, -0.01; p = 0.013), and, more weakly with poorer processing speed (ß = -0.02, 95%CI -0.05, 0.02; p = 0.075). Evidence of association with both poorer processing speed (p = 0.016) and performance IQ (p = 0.018) was stronger at PT≤0.5. Associations with performance IQ and processing speed were primarily driven by genetic effects that are shared with SZ risk, but there was some evidence of bipolar-specific genetic effects on childhood executive functioning. LIMITATIONS The BD-PRS still explains only a small proportion of the variance for BD which will have reduced power to detect associations. CONCLUSIONS Genetic risk for BD manifests as impaired cognition in childhood, and this is driven by risk SNPs that are also shared with SZ genetic risk. Further elucidation of which cognitive domains are most affected by genetic risk for BD could help understanding of aetiology and improve prediction of BD.
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Affiliation(s)
- Sumit Mistry
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK.
| | - Valentina Escott-Price
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Arianna D Florio
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
| | - Daniel J Smith
- Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, UK
| | - Stanley Zammit
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
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Smeland OB, Frei O, Fan CC, Shadrin A, Dale AM, Andreassen OA. The emerging pattern of shared polygenic architecture of psychiatric disorders, conceptual and methodological challenges. Psychiatr Genet 2019; 29:152-159. [PMID: 31464996 PMCID: PMC10752571 DOI: 10.1097/ypg.0000000000000234] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Genome-wide association studies have transformed psychiatric genetics and provided novel insights into the genetic etiology of psychiatric disorders. Two major discoveries have emerged; the disorders are polygenic, with a large number of common variants each with a small effect and many genetic variants influence more than one phenotype, suggesting shared genetic etiology. These concepts have the potential to revolutionize the current classification system with diagnostic categories and facilitate development of better treatments. However, to reach clinical impact, we need larger samples and better analytical tools, as most polygenic factors remain undetected. We here present statistical approaches designed to improve the yield of existing genome-wide association studies for polygenic phenotypes. We review how these tools have informed the current knowledge on the genetic architecture of psychiatric disorders, focusing on schizophrenia, bipolar disorder and major depression, and overlap with psychological and cognitive traits. We discuss application of statistical tools for stratification and prediction.
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Affiliation(s)
- Olav B. Smeland
- NORMENT Centre, Institute of Clinical Medicine, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Chun-Chieh Fan
- Center for Human Development, University of California, San Diego, USA
| | - Alexey Shadrin
- NORMENT Centre, Institute of Clinical Medicine, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Anders M. Dale
- Department of Radiology, University of California, USA
- Department of Neuroscience, University of California, San Diego, USA
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, California, USA
| | - Ole A. Andreassen
- NORMENT Centre, Institute of Clinical Medicine, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
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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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