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Chen LG, Tubbs JD, Liu Z, Thach TQ, Sham PC. Mendelian randomization: causal inference leveraging genetic data. Psychol Med 2024; 54:1461-1474. [PMID: 38639006 DOI: 10.1017/s0033291724000321] [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: 04/20/2024]
Abstract
Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples - the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.
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Affiliation(s)
- Lane G Chen
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Justin D Tubbs
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Zipeng Liu
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Thuan-Quoc Thach
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Pak C Sham
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
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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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Cattarinussi G, Gugliotta AA, Sambataro F. The Risk for Schizophrenia-Bipolar Spectrum: Does the Apple Fall Close to the Tree? A Narrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6540. [PMID: 37569080 PMCID: PMC10418911 DOI: 10.3390/ijerph20156540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/24/2023] [Accepted: 08/04/2023] [Indexed: 08/13/2023]
Abstract
Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share clinical features and several risk genes. Important information about their genetic underpinnings arises from intermediate phenotypes (IPs), quantifiable biological traits that are more prevalent in unaffected relatives (RELs) of patients compared to the general population and co-segregate with the disorders. Within IPs, neuropsychological functions and neuroimaging measures have the potential to provide useful insight into the pathophysiology of SCZ and BD. In this context, the present narrative review provides a comprehensive overview of the available evidence on deficits in neuropsychological functions and neuroimaging alterations in unaffected relatives of SCZ (SCZ-RELs) and BD (BD-RELs). Overall, deficits in cognitive functions including intelligence, memory, attention, executive functions, and social cognition could be considered IPs for SCZ. Although the picture for cognitive alterations in BD-RELs is less defined, BD-RELs seem to present worse performances compared to controls in executive functioning, including adaptable thinking, planning, self-monitoring, self-control, and working memory. Among neuroimaging markers, SCZ-RELs appear to be characterized by structural and functional alterations in the cortico-striatal-thalamic network, while BD risk seems to be associated with abnormalities in the prefrontal, temporal, thalamic, and limbic regions. In conclusion, SCZ-RELs and BD-RELs present a pattern of cognitive and neuroimaging alterations that lie between patients and healthy individuals. Similar abnormalities in SCZ-RELs and BD-RELs may be the phenotypic expression of the shared genetic mechanisms underlying both disorders, while the specificities in neuropsychological and neuroimaging profiles may be associated with the differential symptom expression in the two disorders.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Alessio A. Gugliotta
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
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4
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Ben-Azu B, del Re EC, VanderZwaag J, Carrier M, Keshavan M, Khakpour M, Tremblay MÈ. Emerging epigenetic dynamics in gut-microglia brain axis: experimental and clinical implications for accelerated brain aging in schizophrenia. Front Cell Neurosci 2023; 17:1139357. [PMID: 37256150 PMCID: PMC10225712 DOI: 10.3389/fncel.2023.1139357] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 04/27/2023] [Indexed: 06/01/2023] Open
Abstract
Brain aging, which involves a progressive loss of neuronal functions, has been reported to be premature in probands affected by schizophrenia (SCZ). Evidence shows that SCZ and accelerated aging are linked to changes in epigenetic clocks. Recent cross-sectional magnetic resonance imaging analyses have uncovered reduced brain reserves and connectivity in patients with SCZ compared to typically aging individuals. These data may indicate early abnormalities of neuronal function following cyto-architectural alterations in SCZ. The current mechanistic knowledge on brain aging, epigenetic changes, and their neuropsychiatric disease association remains incomplete. With this review, we explore and summarize evidence that the dynamics of gut-resident bacteria can modulate molecular brain function and contribute to age-related neurodegenerative disorders. It is known that environmental factors such as mode of birth, dietary habits, stress, pollution, and infections can modulate the microbiota system to regulate intrinsic neuronal activity and brain reserves through the vagus nerve and enteric nervous system. Microbiota-derived molecules can trigger continuous activation of the microglial sensome, groups of receptors and proteins that permit microglia to remodel the brain neurochemistry based on complex environmental activities. This remodeling causes aberrant brain plasticity as early as fetal developmental stages, and after the onset of first-episode psychosis. In the central nervous system, microglia, the resident immune surveillance cells, are involved in neurogenesis, phagocytosis of synapses and neurological dysfunction. Here, we review recent emerging experimental and clinical evidence regarding the gut-brain microglia axis involvement in SCZ pathology and etiology, the hypothesis of brain reserve and accelerated aging induced by dietary habits, stress, pollution, infections, and other factors. We also include in our review the possibilities and consequences of gut dysbiosis activities on microglial function and dysfunction, together with the effects of antipsychotics on the gut microbiome: therapeutic and adverse effects, role of fecal microbiota transplant and psychobiotics on microglial sensomes, brain reserves and SCZ-derived accelerated aging. We end the review with suggestions that may be applicable to the clinical setting. For example, we propose that psychobiotics might contribute to antipsychotic-induced therapeutic benefits or adverse effects, as well as reduce the aging process through the gut-brain microglia axis. Overall, we hope that this review will help increase the understanding of SCZ pathogenesis as related to chronobiology and the gut microbiome, as well as reveal new concepts that will serve as novel treatment targets for SCZ.
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Affiliation(s)
- Benneth Ben-Azu
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Department of Pharmacology, Faculty of Basic Medical Sciences, College of Health Sciences, Delta State University, Abraka, Nigeria
| | - Elisabetta C. del Re
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- VA Boston Healthcare System, Brockton, MA, United States
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Jared VanderZwaag
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Micaël Carrier
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | | | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Axe Neurosciences, Centre de Recherche du CHU de Québec, Université Laval, Québec City, QC, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
- Department of Molecular Medicine, Université Laval, Québec City, QC, Canada
- Centre for Advanced Materials and Related Technology (CAMTEC), Institute on Aging and Lifelong Health (IALH), University of Victoria, Victoria, BC, Canada
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5
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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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6
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Schmitt A, Falkai P, Papiol S. Neurodevelopmental disturbances in schizophrenia: evidence from genetic and environmental factors. J Neural Transm (Vienna) 2023; 130:195-205. [PMID: 36370183 PMCID: PMC9660136 DOI: 10.1007/s00702-022-02567-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 11/03/2022] [Indexed: 11/13/2022]
Abstract
Since more than 3 decades, schizophrenia (SZ) has been regarded as a neurodevelopmental disorder. The neurodevelopmental hypothesis proposes that SZ is associated with genetic and environmental risk factors, which influence connectivity in neuronal circuits during vulnerable developmental periods. We carried out a non-systematic review of genetic/environmental factors that increase SZ risk in light of its neurodevelopmental hypothesis. We also reviewed the potential impact of SZ-related environmental and genetic risk factors on grey and white matter pathology and brain function based on magnetic resonance imaging and post-mortem studies. Finally, we reviewed studies that have used patient-derived neuronal models to gain knowledge of the role of genetic and environmental factors in early developmental stages. Taken together, these studies indicate that a variety of environmental factors may interact with genetic risk factors during the pre- or postnatal period and/or during adolescence to induce symptoms of SZ in early adulthood. These risk factors induce disturbances of macro- and microconnectivity in brain regions involving the prefrontal, temporal and parietal cortices and the hippocampus. On the molecular and cellular level, a disturbed synaptic plasticity, loss of oligodendrocytes and impaired myelination have been shown in brain regions of SZ patients. These cellular/histological phenotypes are related to environmental risk factors such as obstetric complications, maternal infections and childhood trauma and genetic risk factors identified in recent genome-wide association studies. SZ-related genetic risk may contribute to active processes interfering with synaptic plasticity in the adult brain. Advances in stem cell technologies are providing promising mechanistic insights into how SZ risk factors impact the developing brain. Further research is needed to understand the timing of the different complex biological processes taking place as a result of the interplay between genetic and environmental factors.
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Affiliation(s)
- Andrea Schmitt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstr. 7, 80336, Munich, Germany.
- Laboratory of Neuroscience (LIM27), Institute of Psychiatry, University of São Paulo, São Paulo, Brazil.
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstr. 7, 80336, Munich, Germany
- Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, Munich, Germany
| | - Sergi Papiol
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstr. 7, 80336, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
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7
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Liu Z, Qin Y, Wu T, Tubbs JD, Baum L, Mak TSH, Li M, Zhang YD, Sham PC. Reciprocal causation mixture model for robust Mendelian randomization analysis using genome-scale summary data. Nat Commun 2023; 14:1131. [PMID: 36854672 PMCID: PMC9975185 DOI: 10.1038/s41467-023-36490-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 02/03/2023] [Indexed: 03/02/2023] Open
Abstract
Mendelian randomization using GWAS summary statistics has become a popular method to infer causal relationships across complex diseases. However, the widespread pleiotropy observed in GWAS has made the selection of valid instrumental variables problematic, leading to possible violations of Mendelian randomization assumptions and thus potentially invalid inferences concerning causation. Furthermore, current MR methods can examine causation in only one direction, so that two separate analyses are required for bi-directional analysis. In this study, we propose a ststistical framework, MRCI (Mixture model Reciprocal Causation Inference), to estimate reciprocal causation between two phenotypes simultaneously using the genome-scale summary statistics of the two phenotypes and reference linkage disequilibrium information. Simulation studies, including strong correlated pleiotropy, showed that MRCI obtained nearly unbiased estimates of causation in both directions, and correct Type I error rates under the null hypothesis. In applications to real GWAS data, MRCI detected significant bi-directional and uni-directional causal influences between common diseases and putative risk factors.
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Affiliation(s)
- Zipeng Liu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China.,Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Yiming Qin
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China.,Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Tian Wu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Justin D Tubbs
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Larry Baum
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China.,Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Timothy Shin Heng Mak
- Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Miaoxin Li
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. .,Zhongshan School of Medicine, Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China. .,Key Laboratory of Tropical Disease Control (SYSU), Ministry of Education, Guangzhou, China.
| | - Yan Dora Zhang
- Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. .,Department of Statistics & Actuarial Science, Faculty of Science, The University of Hong Kong, Hong Kong SAR, China.
| | - Pak Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. .,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China. .,Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
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Valli I, De la Serna E, Segura AG, Pariente JC, Calvet-Mirabent A, Borras R, Ilzarbe D, Moreno D, Martín-Martínez N, Baeza I, Rosa-Justicia M, Garcia-Rizo C, Díaz-Caneja CM, Crossley NA, Young AH, Vieta E, Mas S, Castro-Fornieles J, Sugranyes G. Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder. J Am Acad Child Adolesc Psychiatry 2023; 62:74-83. [PMID: 35710081 DOI: 10.1016/j.jaac.2022.05.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/21/2022] [Accepted: 06/06/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Cognitive impairment is an important feature of schizophrenia (SZ) and bipolar disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership. METHOD One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores. RESULTS Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area. CONCLUSION Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.
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Affiliation(s)
- Isabel Valli
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London.
| | - Elena De la Serna
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | | | - Jose C Pariente
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Roger Borras
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Daniel Ilzarbe
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Dolores Moreno
- Institute of Neuroscience, Hospital Clínic Barcelona, Spain; Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nuria Martín-Martínez
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Inmaculada Baeza
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Mireia Rosa-Justicia
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente Garcia-Rizo
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
| | - Nicolas A Crossley
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Allan H Young
- Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, United Kingdom
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Sergi Mas
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; University of Barcelona, Spain
| | - Josefina Castro-Fornieles
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
| | - Gisela Sugranyes
- Institut d'Investigacions Biomèdiques Agustí Pi I Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; Institute of Neuroscience, Hospital Clínic Barcelona, Spain; University of Barcelona, Spain
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Zhang M, Yang F, Fan H, Fan F, Wang Z, Xiang H, Huang W, Tan Y, Tan S, Hong LE. Increased connectivity of insula sub-regions correlates with emotional dysregulation in patients with first-episode schizophrenia. Psychiatry Res Neuroimaging 2022; 326:111535. [PMID: 36084435 DOI: 10.1016/j.pscychresns.2022.111535] [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: 09/06/2021] [Revised: 08/05/2022] [Accepted: 08/24/2022] [Indexed: 11/21/2022]
Abstract
Dysfunctional insula is crucial in the development of social cognition deficits, especially emotional dysregulation in patients with schizophrenia. However, function networks of insula sub-regions in schizophrenia are rarely investigated. In this study, functional connectivity between insula sub-regions and whole-brain voxels and its relationship with social cognition ability were investigated in patients with first-episode schizophrenia (FES). This study included 47 patients with FES and 47 healthy controls (HCs). Resting-state functional connectivity (rsFC) was assessed using a seed-based approach, and social cognition was measured by the "managing emotions" branch of the Mayer-Salovey-Caruso Emotional Intelligence Test. Differences in rsFC of insula sub-regions between the two groups were examined. Patients with FES showed increased rsFC between the left anterior insula (AI) and the right inferior frontal gyrus or the right anterior middle cingulate cortex (aMCC) and between the right middle insula and the right aMCC. Moreover, the increased AI-aMCC connectivity correlated negatively with the "managing emotion" scores in patients. This study highlights the altered functional connectivity of insula sub-regions and its correlation with emotional dysregulation in patients with FES. Our findings provide some insights into underlying neuropathological mechanisms associated with emotional regulation deficiency in patients with schizophrenia.
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Affiliation(s)
- Meng Zhang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China
| | - Fude Yang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China.
| | - Hongzhen Fan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China
| | - Fengmei Fan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China
| | - Zhiren Wang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China
| | - Hong Xiang
- Chongqing University Three Gorges Hospital, Chongqing 404000, China
| | - Wenqian Huang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China
| | - Yunlong Tan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China
| | - Shuping Tan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing 100096, China.
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21288, United States of America
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10
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Transmission of intelligence, working memory, and processing speed from parents to their seven-year-old offspring is function specific in families with schizophrenia or bipolar disorder. Schizophr Res 2022; 246:195-201. [PMID: 35802954 DOI: 10.1016/j.schres.2022.06.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 06/15/2022] [Accepted: 06/26/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Prior studies have shown high heritability estimates regarding within-function transmission of neurocognition, both in healthy families and in families with schizophrenia but it remains an open question whether transmission from parents to offspring is function specific and whether the pattern is the same in healthy families and families with schizophrenia or bipolar disorder. We aimed to characterize the transmission of intelligence, processing speed, and verbal working memory functions from both biological parents to their 7-year-old offspring in families with parental schizophrenia, bipolar disorder, and population-based control parents. METHODS The population-based cohort consists of 7-year-old children with one parent diagnosed with schizophrenia (n = 186), bipolar disorder (n = 114), and of parents without schizophrenia or bipolar disorder (n = 192). Children and both parents were assessed using identical, age-relevant neurocognitive tests of intelligence, verbal working memory, and processing speed. RESULTS In multiple regression analyses children's intelligence, verbal working memory, and processing speed scores were significantly associated with the corresponding parental cognitive function score. All associations from parents to offspring across functions were non-significant. No significant parental cognitive function by group interaction was observed. CONCLUSION Transmissions of intelligence, processing speed, and verbal working memory from parents to offspring are function specific. The structure of transmission is comparable between families with schizophrenia, families with bipolar disorder and families without these disorders.
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11
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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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12
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Kahn RS. Retroverting schizophrenia. Schizophr Res 2022; 242:62-63. [PMID: 35123864 DOI: 10.1016/j.schres.2022.01.040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/19/2022] [Accepted: 01/20/2022] [Indexed: 01/02/2023]
Affiliation(s)
- René Sylvain Kahn
- Icahn School of Medicine, One Gustave L. Levy Place, Box 1230, New York, NY 10010, United States.
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13
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Dyakin VV, Dyakina-Fagnano NV, Mcintire LB, Uversky VN. Fundamental Clock of Biological Aging: Convergence of Molecular, Neurodegenerative, Cognitive and Psychiatric Pathways: Non-Equilibrium Thermodynamics Meet Psychology. Int J Mol Sci 2021; 23:ijms23010285. [PMID: 35008708 PMCID: PMC8745688 DOI: 10.3390/ijms23010285] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 11/24/2021] [Accepted: 12/22/2021] [Indexed: 12/23/2022] Open
Abstract
In humans, age-associated degrading changes, widely observed in molecular and cellular processes underly the time-dependent decline in spatial navigation, time perception, cognitive and psychological abilities, and memory. Cross-talk of biological, cognitive, and psychological clocks provides an integrative contribution to healthy and advanced aging. At the molecular level, genome, proteome, and lipidome instability are widely recognized as the primary causal factors in aging. We narrow attention to the roles of protein aging linked to prevalent amino acids chirality, enzymatic and spontaneous (non-enzymatic) post-translational modifications (PTMs SP), and non-equilibrium phase transitions. The homochirality of protein synthesis, resulting in the steady-state non-equilibrium condition of protein structure, makes them prone to multiple types of enzymatic and spontaneous PTMs, including racemization and isomerization. Spontaneous racemization leads to the loss of the balanced prevalent chirality. Advanced biological aging related to irreversible PTMs SP has been associated with the nontrivial interplay between somatic (molecular aging) and mental (psychological aging) health conditions. Through stress response systems (SRS), the environmental and psychological stressors contribute to the age-associated “collapse” of protein homochirality. The role of prevalent protein chirality and entropy of protein folding in biological aging is mainly overlooked. In a more generalized context, the time-dependent shift from enzymatic to the non-enzymatic transformation of biochirality might represent an important and yet underappreciated hallmark of aging. We provide the experimental arguments in support of the racemization theory of aging.
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Affiliation(s)
- Victor V. Dyakin
- The Nathan S. Kline Institute for Psychiatric Research (NKI), 140 Old Orangeburg Road, Bldg, 35, Bld. 35. Rom 201-C, Orangeburg, NY 10962, USA
- Correspondence: ; Tel.: +1-845-548-96-94; Fax: +1-845-398-5510
| | - Nuka V. Dyakina-Fagnano
- Child, Adolescent and Young Adult Psychiatry, 36 Franklin Turnpike, Waldwick, NJ 07463, USA;
| | - Laura B. Mcintire
- Department of Pathology and Cell Biology, Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, NY 10032, USA;
| | - Vladimir N. Uversky
- Department of Molecular Medicine and Byrd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd., MDC07, Tampa, FL 33612, USA;
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14
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Schmitt S, Meller T, Stein F, Brosch K, Ringwald K, Pfarr JK, Bordin C, Peusch N, Steinsträter O, Grotegerd D, Dohm K, Meinert S, Förster K, Redlich R, Opel N, Hahn T, Jansen A, Forstner AJ, Streit F, Witt SH, Rietschel M, Müller-Myhsok B, Nöthen MM, Dannlowski U, Krug A, Kircher T, Nenadić I. Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity. Psychol Med 2021; 52:1-12. [PMID: 33827729 PMCID: PMC9811276 DOI: 10.1017/s0033291721001082] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Revised: 02/25/2021] [Accepted: 03/05/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. METHODS We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. RESULTS The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. CONCLUSIONS Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.
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Affiliation(s)
- Simon Schmitt
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
- Marburg University Hospital – UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
- Marburg University Hospital – UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Kai Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Clemens Bordin
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Nina Peusch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Olaf Steinsträter
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Dominik Grotegerd
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Katharina Dohm
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Susanne Meinert
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Katharina Förster
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Ronny Redlich
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
- Department of Psychology, University of Halle, Halle, Germany
| | - Nils Opel
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Tim Hahn
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
- Faculty of Medicine, Core-Facility BrainImaging, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039, Germany
| | - Andreas J. Forstner
- Centre for Human Genetics, Philipps-Universität Marburg, Baldingerstr., 35033 Marburg, Germany
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Wilhelm-Johnen-Straße, 52428 Jülich, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159 Mannheim, Germany
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159 Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159 Mannheim, Germany
| | - Bertram Müller-Myhsok
- Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Str. 17, 81377 Munich, Germany
- Institute of Translational Medicine, University of Liverpool, Crown Street, Liverpool L69 3BX, UK
- Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Markus M. Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany
| | - Udo Dannlowski
- Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
- Marburg University Hospital – UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany
- Marburg University Hospital – UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
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15
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Cai Y, Xing L, Yang T, Chai R, Wang J, Bao J, Shen W, Ding S, Chen G. The neurodevelopmental role of dopaminergic signaling in neurological disorders. Neurosci Lett 2020; 741:135540. [PMID: 33278505 DOI: 10.1016/j.neulet.2020.135540] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/10/2020] [Accepted: 11/27/2020] [Indexed: 12/11/2022]
Abstract
Dopamine (DA), a critical neurotransmitter of both the central and peripheral nerve system, plays important roles in a series of biological processes. Dysfunction of dopaminergic signalling may lead to a series of developmental disorders, including attention deficit/hyperactivity disorder, autism and schizophrenia. However, the exact roles of dopaminergic signalling in these diseases are far from fully understood. We analyse the roles of dopaminergic signalling in multiple physiological and pathological processes, focusing on brain development and related disorders. By summarizing current research in this area, we provide guidance for future studies. This review seeks to deepen our understanding of dopaminergic signalling in developmental disorders, which may offer clues for developing more effective therapeutic drugs.
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Affiliation(s)
- Yunyun Cai
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, 226001, China
| | - Lingyan Xing
- Key Laboratory of Neuroregeneration of Jiangsu and the Ministry of Education, Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu Province, 226001, China
| | - Tuo Yang
- Department of Hand Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, 130033, China
| | - Rui Chai
- Key Laboratory of Neuroregeneration of Jiangsu and the Ministry of Education, Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu Province, 226001, China
| | - Jiaqi Wang
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, 226001, China
| | - Jingyin Bao
- Basic Medical Research Centre, Medical College of Nantong University, Nantong, Jiangsu Province, 226001, China
| | - Weixing Shen
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, 226001, China.
| | - Sujun Ding
- Department of Ultrasound, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, 226001, China.
| | - Gang Chen
- Department of Tissue and Embryology, Medical School of Nantong University, Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu Province, 226001, China; Department of Anesthesiology, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, 226001, China.
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16
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Evermann U, Gaser C, Besteher B, Langbein K, Nenadić I. Cortical Gyrification, Psychotic-Like Experiences, and Cognitive Performance in Nonclinical Subjects. Schizophr Bull 2020; 46:1524-1534. [PMID: 32691058 PMCID: PMC7707080 DOI: 10.1093/schbul/sbaa068] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND Psychotic-like experiences (PLE) are present in nonclinical populations, yet their association with brain structural variation, especially markers of early neurodevelopment, is poorly understood. We tested the hypothesis that cortical surface gyrification, a putative marker of early brain development, is associated with PLE in healthy subjects. METHODS We analyzed gyrification from 3 Tesla MRI scans (using CAT12 software) and PLE (positive, negative, and depressive symptom dimensions derived from the Community Assessment of Psychic Experiences, CAPE) in 103 healthy participants (49 females, mean age 29.13 ± 9.37 years). A subsample of 63 individuals completed tasks from the Wechsler Adult Intelligence Scale and Controlled Oral Word Association Test. Estimated IQ and a composite neuropsychological score were used to explore mediation pathways via cognition. RESULTS Positive PLE distress was negatively associated with gyrification of the left precuneus. PLE depression dimension showed a negative association with gyrification in the right supramarginal and temporal region. There was no significant mediating effect of cognition on these associations. CONCLUSION Our results support a neurobiological psychosis spectrum, for the first time linking an early developmental imaging marker (rather than volume) to dimensional subclinical psychotic symptoms. While schizophrenia risk, neurodevelopment, and cognitive function might share genetic risk factors, additional mediation analyses did not confirm a mediating effect of cognition on the gyrification-psychopathology correlation.
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Affiliation(s)
- Ulrika Evermann
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Bianca Besteher
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Kerstin Langbein
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Igor Nenadić
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Marburg University Hospital – UKGM, Marburg, Germany
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17
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de Zwarte SMC, Brouwer RM, Agartz I, Alda M, Alonso‐Lana S, Bearden CE, Bertolino A, Bonvino A, Bramon E, Buimer EEL, Cahn W, Canales‐Rodríguez EJ, Cannon DM, Cannon TD, Caseras X, Castro‐Fornieles J, Chen Q, Chung Y, De la Serna E, del Mar Bonnin C, Demro C, Di Giorgio A, Doucet GE, Eker MC, Erk S, Fatjó‐Vilas M, Fears SC, Foley SF, Frangou S, Fullerton JM, Glahn DC, Goghari VM, Goikolea JM, Goldman AL, Gonul AS, Gruber O, Hajek T, Hawkins EL, Heinz A, Hidiroglu Ongun C, Hillegers MHJ, Houenou J, Hulshoff Pol HE, Hultman CM, Ingvar M, Johansson V, Jönsson EG, Kane F, Kempton MJ, Koenis MMG, Kopecek M, Krämer B, Lawrie SM, Lenroot RK, Marcelis M, Mattay VS, McDonald C, Meyer‐Lindenberg A, Michielse S, Mitchell PB, Moreno D, Murray RM, Mwangi B, Nabulsi L, Newport J, Olman CA, van Os J, Overs BJ, Ozerdem A, Pergola G, Picchioni MM, Piguet C, Pomarol‐Clotet E, Radua J, Ramsay IS, Richter A, Roberts G, Salvador R, Saricicek Aydogan A, Sarró S, Schofield PR, Simsek EM, Simsek F, Soares JC, Sponheim SR, Sugranyes G, Toulopoulou T, Tronchin G, Vieta E, Walter H, Weinberger DR, Whalley HC, Wu M, Yalin N, Andreassen OA, Ching CRK, Thomopoulos SI, van Erp TGM, Jahanshad N, Thompson PM, Kahn RS, van Haren NEM. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder. Hum Brain Mapp 2020; 43:414-430. [PMID: 33027543 PMCID: PMC8675411 DOI: 10.1002/hbm.25206] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 08/28/2020] [Accepted: 09/03/2020] [Indexed: 12/25/2022] Open
Abstract
First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.
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Affiliation(s)
- Sonja M. C. de Zwarte
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Rachel M. Brouwer
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,Department of PsychiatryDiakonhjemmet HospitalOsloNorway
| | - Martin Alda
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Silvia Alonso‐Lana
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Carrie E. Bearden
- Semel Institute for Neuroscience and Human Behavior, University of CaliforniaCaliforniaLos AngelesUSA,Department of PsychologyUniversity of CaliforniaCaliforniaLos AngelesUSA
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Aurora Bonvino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Elvira Bramon
- Division of Psychiatry, Neuroscience in Mental Health Research DepartmentUniversity College LondonLondonUK
| | - Elizabeth E. L. Buimer
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Wiepke Cahn
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Erick J. Canales‐Rodríguez
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Dara M. Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Tyrone D. Cannon
- Department of PsychologyYale UniversityNew HavenConnecticutUSA,Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUK
| | - Josefina Castro‐Fornieles
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA
| | - Yoonho Chung
- Department of PsychologyYale UniversityNew HavenConnecticutUSA
| | - Elena De la Serna
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Caterina del Mar Bonnin
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Caroline Demro
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | - Gaelle E. Doucet
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA,Boys Town National Research HospitalOmahaNEUSA
| | - Mehmet Cagdas Eker
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey
| | - Susanne Erk
- Research Division of Mind and Brain, Department of Psychiatry and PsychotherapyCharité Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Mar Fatjó‐Vilas
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Scott C. Fears
- Department of Psychiatry and Biobehavioral ScienceUniversity of CaliforniaLos AngelesCaliforniaUSA,Center for Neurobehavioral GeneticsUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Sonya F. Foley
- Cardiff University Brain Research Imaging Centre, Cardiff UniversityCardiffUK
| | - Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Janice M. Fullerton
- Neuroscience Research AustraliaSydneyAustralia,School of Medical Sciences, University of New South WalesSydneyAustralia
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA,Tommy Fuss Center for Neuropsychiatric Disease ResearchBoston Children's HospitalBostonMassachusettsUSA,Harvard Medical SchoolBostonMassachusettsUSA
| | - Vina M. Goghari
- Department of Psychology and Graduate Department of Psychological Clinical ScienceUniversity of TorontoTorontoOntarioCanada
| | - Jose M. Goikolea
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Aaron L. Goldman
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA
| | - Ali Saffet Gonul
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey,Department of Psychiatry and Behavioral SciencesMercer University School of MedicineMaconGeorgiaUSA
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Tomas Hajek
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Emma L. Hawkins
- Division of PsychiatryRoyal Edinburgh Hospital, University of EdinburghEdinburghUK
| | - Andreas Heinz
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey
| | | | - Manon H. J. Hillegers
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center‐Sophia Children's HospitalRotterdamNetherlands
| | - Josselin Houenou
- APHP, Mondor University HospitalsCréteilFrance,INSERM U955 Team 15 "Translational Psychiatry"CréteilFrance,NeuroSpin neuroimaging platform, Psychiatry Team, UNIACT Lab, CEA SaclayGif‐Sur‐YvetteFrance
| | - Hilleke E. Hulshoff Pol
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands
| | - Christina M. Hultman
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Martin Ingvar
- Section for Neuroscience, Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden,Department of NeuroradiologyKarolinska University HospitalStockholmSweden
| | - Viktoria Johansson
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden
| | - Fergus Kane
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Matthew J. Kempton
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Marinka M. G. Koenis
- Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA,Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA
| | - Miloslav Kopecek
- National Institute of Mental HealthKlecanyCzech Republic,Department of Psychiatry, Third Faculty of MedicineCharles UniversityPragueCzech Republic
| | - Bernd Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Stephen M. Lawrie
- Division of PsychiatryRoyal Edinburgh Hospital, University of EdinburghEdinburghUK
| | - Rhoshel K. Lenroot
- Neuroscience Research AustraliaSydneyAustralia,School of Psychiatry, University of New South WalesSydneyAustralia,Department of Psychiatry and Behavioral SciencesUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Machteld Marcelis
- Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | - Venkata S. Mattay
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreMarylandUSA,Departments of Neurology and RadiologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Andreas Meyer‐Lindenberg
- Department of Psychiatry and PsychotherapyCentral Institute of Mental Health, Medical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Stijn Michielse
- Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | | | - Dolores Moreno
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Child and Adolescent Psychiatry DepartmentHospital General Universitario Gregorio Marañón (IiSGM), School of Medicine, Universidad ComplutenseMadridSpain
| | - Robin M. Murray
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College LondonLondonUK
| | - Benson Mwangi
- Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Leila Nabulsi
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Jason Newport
- Department of PsychiatryDalhousie UniversityHalifaxNova ScotiaCanada
| | - Cheryl A. Olman
- Department of Psychology and Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Jim van Os
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Psychiatry and NeuropsychologySchool for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht UniversityMaastrichtNetherlands
| | | | - Aysegul Ozerdem
- Department of Psychiatry, Faculty of MedicineDokuz Eylül UniversityIzmirTurkey,Department of NeurosciencesHealth Sciences Institute, Dokuz Eylül UniversityIzmirTurkey,Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari 'Aldo Moro'BariItaly
| | - Marco M. Picchioni
- Department of Forensic and Neurodevelopmental ScienceInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Camille Piguet
- INSERM U955 Team 15 "Translational Psychiatry"CréteilFrance,NeuroSpin neuroimaging platform, Psychiatry Team, UNIACT Lab, CEA SaclayGif‐Sur‐YvetteFrance,Department of Psychiatry, Faculty of MedicineUniversity of GenevaGenevaSwitzerland,School of Medicine, Universitat Internacional de CatalunyaBarcelonaSpain
| | - Edith Pomarol‐Clotet
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Joaquim Radua
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care Services, Stockholm RegionStockholmSweden,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Early Psychosis: Interventions and Clinical‐detection (EPIC) lab, Department of Psychosis StudiesInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUK
| | - Ian S. Ramsay
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Anja Richter
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryUniversity of HeidelbergHeidelbergGermany
| | - Gloria Roberts
- School of Psychiatry, University of New South WalesSydneyAustralia
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Aybala Saricicek Aydogan
- Department of NeurosciencesHealth Sciences Institute, Dokuz Eylül UniversityIzmirTurkey,Department of Psychiatry, Faculty of MedicineIzmir Katip Çelebi UniversityIzmirTurkey
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research FoundationBarcelonaSpain,CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain
| | - Peter R. Schofield
- School of Medical Sciences, University of New South WalesSydneyAustralia,Olin Neuropsychiatry Research Center, Institute of Living, Hartford HospitalHartfordConnecticutUSA
| | | | - Fatma Simsek
- SoCAT LAB, Department of PsychiatrySchool of Medicine, Ege UniversityIzmirTurkey,Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK,Cigli State HospitalDepartment of PsychiatryIzmirTurkey
| | - Jair C. Soares
- Department of Psychiatry and Behavioral SciencesThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA,Minneapolis VA Health Care SystemMinneapolisMinnesotaUSA
| | - Gisela Sugranyes
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881Institute of Neuroscience, Hospital Clínic of BarcelonaBarcelonaSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,University of BarcelonaBarcelonaSpain
| | - Timothea Toulopoulou
- Department of PsychologyBilkent UniversityAnkaraTurkey,Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Giulia Tronchin
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland GalwayGalwayIreland
| | - Eduard Vieta
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)MadridSpain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain,Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Henrik Walter
- Research Division of Mind and Brain, Department of Psychiatry and PsychotherapyCharité Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of HealthBerlinGermany
| | - Daniel R. Weinberger
- Bipolar and Depressive Disorders UnitHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Heather C. Whalley
- Department of Psychology, Faculty of ArtsDokuz Eylül UniversityİzmirTurkey
| | - Mon‐Ju Wu
- Department of Psychology and Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Nefize Yalin
- Centre for Affective Disorders, Department of Psychological MedicineInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of OsloOsloNorway,Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA,Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - René S. Kahn
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Neeltje E. M. van Haren
- Department of PsychiatryUniversity Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht UniversityUtrechtNetherlands,Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center‐Sophia Children's HospitalRotterdamNetherlands
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Affiliation(s)
- René S Kahn
- Department of Psychiatry and Behavioral Health System, Icahn School of Medicine at Mount Sinai, N.Y.; and VISN 2 Mental Illness Research, Education, and Clinical Center, James J. Peters VA Medical Center, Bronx, N.Y
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19
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Twin studies of brain structure and cognition in schizophrenia. Neurosci Biobehav Rev 2019; 109:103-113. [PMID: 31843545 DOI: 10.1016/j.neubiorev.2019.12.021] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 12/09/2019] [Accepted: 12/12/2019] [Indexed: 11/20/2022]
Abstract
Twin studies in schizophrenia have been crucial in establishing estimates for the heritability and thus providing evidence for a genetic component in this disorder. Recent years have seen the application of the twin study paradigm to both putative intermediate phenotypes and biomarkers of disease as well as a diversification of its use in schizophrenia research. This review addressed studies of brain structure (T1 morphometry) and cognition in schizophrenia using twin study designs. We review major findings such as the overlap of genetic variance between schizophrenia and cognition as a model for the emergence of psychopathology. The use of novel hybrid models integrating molecular genetic risk markers, as well as the use of twin studies in epigenetics might prove to significantly enhance schizophrenia research in the post-GWAS era.
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20
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Erbeli F, van Bergen E, Hart SA. Unraveling the Relation Between Reading Comprehension and Print Exposure. Child Dev 2019; 91:1548-1562. [PMID: 31732976 DOI: 10.1111/cdev.13339] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
The purpose of this study was to test the directionality of influence between reading comprehension (RC) and print exposure (PE), thereby estimating genetic and environmental effects of this relation. The sample consisted of 910 twins in fourth through ninth grades (Mage = 12.33 years, SD = 1.41) from the Florida Twin Project on Reading, Behavior, and Environment. Using direction-of-causation model in a twin design, results supported a direction of influence running from RC to PE. This relation was underpinned by genetic and environmental factors of RC as well as PE. Implications for reading education are discussed.
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21
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de Zwarte SMC, Brouwer RM, Tsouli A, Cahn W, Hillegers MHJ, Hulshoff Pol HE, Kahn RS, van Haren NEM. Running in the Family? Structural Brain Abnormalities and IQ in Offspring, Siblings, Parents, and Co-twins of Patients with Schizophrenia. Schizophr Bull 2019; 45:1209-1217. [PMID: 30597053 PMCID: PMC6811835 DOI: 10.1093/schbul/sby182] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Structural brain abnormalities and cognitive deficits have been reported in patients with schizophrenia and to a lesser extent in their first-degree relatives (FDRs). Here we investigated whether brain abnormalities in nonpsychotic relatives differ per type of FDR and how these abnormalities are related to intelligent quotient (IQ). Nine hundred eighty individuals from 5 schizophrenia family cohorts (330 FDRs, 432 controls, 218 patients) were included. Effect sizes were calculated to compare brain measures of FDRs and patients with controls, and between each type of FDR. Analyses were repeated with a correction for IQ, having a nonpsychotic diagnosis, and intracranial volume (ICV). FDRs had significantly smaller ICV, surface area, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, thalamus, putamen, amygdala, and accumbens volumes as compared with controls (ds < -0.19, q < 0.05 corrected). Offspring showed the largest effect sizes relative to the other FDRs; however, none of the effects in the different relative types survived correction for multiple comparisons. After IQ correction, all effects disappeared in the FDRs after correction for multiple comparisons. The findings in FDRs were not explained by having a nonpsychotic disorder and were only partly explained by ICV. FDRs show brain abnormalities that are strongly covarying with IQ. On the basis of consistent evidence of genetic overlap between schizophrenia, IQ, and brain measures, we suggest that the brain abnormalities in FDRs are at least partly explained by genes predisposing to both schizophrenia risk and IQ.
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Affiliation(s)
- Sonja M C de Zwarte
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands,To whom correspondence should be addressed; Department of Psychiatry, University Medical Center Utrecht, House A.01.126 A01.126, PO Box 85500, 3508 GA Utrecht, The Netherlands; tel: +31-88-75-67656, e-mail:
| | - Rachel M Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Andromachi Tsouli
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Manon H J Hillegers
- 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
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - René S Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Neeltje E M 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
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22
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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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23
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Li Z, Wang Y, Yan C, Cheung EFC, Docherty AR, Sham PC, Gur RE, Gur RC, Chan RCK. Inheritance of Neural Substrates for Motivation and Pleasure. Psychol Sci 2019; 30:1205-1217. [PMID: 31318629 DOI: 10.1177/0956797619859340] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Despite advances in the understanding of the reward system and the role of dopamine in recent decades, the heritability of the underlying neural mechanisms is not known. In the present study, we examined the hemodynamic activation of the nucleus accumbens (NAcc), a key hub of the reward system, in 86 healthy monozygotic twins and 88 healthy dizygotic twins during a monetary-incentive-delay task. The participants also completed self-report measures of pleasure. Using voxelwise heritability mapping, we found that activation of the bilateral NAcc during the anticipation of monetary gains had significant heritability (h2 = .20-.49). Moreover, significant shared genetic covariance was observed between pleasure and NAcc activation during the anticipation of monetary gain. These findings suggest that both NAcc activation and self-reported pleasure may be heritable and that their phenotypic correlation may be partially explained by shared genetic variation.
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Affiliation(s)
- Zhi Li
- 1 Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences.,2 Department of Psychology, Chinese Academy of Sciences
| | - Yi Wang
- 1 Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences
| | - Chao Yan
- 3 Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University
| | | | - Anna R Docherty
- 5 Department of Psychiatry, University of Utah School of Medicine.,6 Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
| | - Pak C Sham
- 7 Centre for Genomic Sciences, The University of Hong Kong.,8 State Key Laboratory in Brain and Cognitive Sciences, The University of Hong Kong.,9 Department of Psychiatry, The University of Hong Kong
| | - Raquel E Gur
- 10 Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania
| | - Ruben C Gur
- 10 Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania
| | - Raymond C K Chan
- 1 Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences.,2 Department of Psychology, Chinese Academy of Sciences
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24
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Abstract
Causal inference is essential across the biomedical, behavioural and social sciences.By progressing from confounded statistical associations to evidence of causal relationships, causal inference can reveal complex pathways underlying traits and diseases and help to prioritize targets for intervention. Recent progress in genetic epidemiology - including statistical innovation, massive genotyped data sets and novel computational tools for deep data mining - has fostered the intense development of methods exploiting genetic data and relatedness to strengthen causal inference in observational research. In this Review, we describe how such genetically informed methods differ in their rationale, applicability and inherent limitations and outline how they should be integrated in the future to offer a rich causal inference toolbox.
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25
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Meller T, Schmitt S, Stein F, Brosch K, Mosebach J, Yüksel D, Zaremba D, Grotegerd D, Dohm K, Meinert S, Förster K, Redlich R, Opel N, Repple J, Hahn T, Jansen A, Andlauer TFM, Forstner AJ, Heilmann-Heimbach S, Streit F, Witt SH, Rietschel M, Müller-Myhsok B, Nöthen MM, Dannlowski U, Krug A, Kircher T, Nenadić I. Associations of schizophrenia risk genes ZNF804A and CACNA1C with schizotypy and modulation of attention in healthy subjects. Schizophr Res 2019; 208:67-75. [PMID: 31076262 DOI: 10.1016/j.schres.2019.04.018] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2018] [Revised: 03/05/2019] [Accepted: 04/20/2019] [Indexed: 12/30/2022]
Abstract
Schizotypy is a multidimensional risk phenotype distributed in the general population, constituting of subclinical, psychotic-like symptoms. It is associated with psychosis proneness, and several risk genes for psychosis are associated with schizotypy in non-clinical populations. Schizotypy might also modulate cognitive abilities as it is associated with attentional deficits in healthy subjects. In this study, we tested the hypothesis that established genetic risk variants ZNF804A rs1344706 and CACNA1C rs1006737 are associated with psychometric schizotypy and that schizotypy mediates their effect on attention or vice versa. In 615 healthy subjects from the FOR2107 cohort study, we analysed the genetic risk variants ZNF804A rs1344706 and CACNA1C rs1006737, psychometric schizotypy (schizotypal personality questionnaire-brief SPQB), and a neuropsychological measure of sustained and selective attention (d2 test). ZNF804A rs1344706 C (non-risk) alleles were significantly associated with higher SPQ-B Cognitive-Perceptual subscores in women and with attention deficits in both sexes. This schizotypy dimension also mediated the effect of ZNF804A on attention in women, but not in men. CACNA1C rs1006737-A showed a significant sex-modulated negative association with Interpersonal schizotypy only in men, and no effect on attention. Our multivariate model demonstrates differential genetic contributions of two psychosis risk genes to dimensions of schizotypy and, partly, to attention. This supports a model of shared genetic influence between schizotypy and cognitive functions impaired in schizophrenia.
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Affiliation(s)
- Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany.
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Johannes Mosebach
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Dilara Yüksel
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; SRI International, Center for Health Sciences, Bioscience Division, 333 Ravenswood Avenue, 94025 Menlo Park, CA, USA
| | - Dario Zaremba
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Dominik Grotegerd
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Katharina Dohm
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Susanne Meinert
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Katharina Förster
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Ronny Redlich
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Nils Opel
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Jonathan Repple
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Tim Hahn
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany; Core-Facility BrainImaging, Faculty of Medicine, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Till F M Andlauer
- Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany; Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675 Munich, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Sigmund-Freud-Straße 25, 53127 Bonn, Germany; Institute of Human Genetics, Philipps-Universität Marburg, Baldingerstraße, 35033 Marburg, Germany; Department of Biomedicine, University of Basel, Hebelstrasse 20, 4031 Basel, Switzerland; Institute of Medical Genetics and Pathology, University Hospital Basel, Schönbeinstr. 40, 4056 Basel, Switzerland
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Sigmund-Freud-Straße 25, 53127 Bonn, Germany
| | - Fabian Streit
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159 Mannheim, Germany
| | - Stephanie H Witt
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159 Mannheim, Germany
| | - Marcella Rietschel
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159 Mannheim, Germany
| | - Bertram Müller-Myhsok
- Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Str. 17, 81377 Munich, Germany; Institute of Translational Medicine, University of Liverpool, Crown Street, Liverpool L69 3BX, UK
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Sigmund-Freud-Straße 25, 53127 Bonn, Germany
| | - Udo Dannlowski
- Department of Psychiatry and Psychotherapy, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), Hans-Meerwein-Str. 6, 35032 Marburg, Germany
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26
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Cherny SS, Freidin MB, Williams FMK, Livshits G. The analysis of causal relationships between blood lipid levels and BMD. PLoS One 2019; 14:e0212464. [PMID: 30794634 PMCID: PMC6386286 DOI: 10.1371/journal.pone.0212464] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 02/01/2019] [Indexed: 12/11/2022] Open
Abstract
Bone mineral density (BMD) and lipid levels are two of the most extensively studied risk factors for common diseases of aging, such as cardiovascular disease (CVD) and osteoporosis (OP). These two risk factors are also correlated with each other, but little is known about the molecular mechanisms behind this correlation. Recent studies revealed that circulating levels of several metabolites involved in the biosynthesis of androsterone correlate significantly with BMD and have the capacity to affect cholesterol and lipids levels. A main aim of the present study was to investigate the hypothesis that androsterone-related metabolites could provide a link between CVD and OP, as a common cause of lipid levels and BMD. The present study employed data from the NIHR BRC TwinsUK BioResource, comprising 1909 and 1994 monozygotic and dizygotic twin pairs, respectively, to address the causal relationships among BMD and lipids, and their associated metabolites, using reciprocal causation twin modelling, as well as Mendelian randomization (MR) using large publicly-available GWAS datasets on lipids and BMD, in conjunction with TwinsUK metabolite data. While results involving the twin modelling and MR analyses with metabolites were unable to establish a causal link between metabolite levels and either lipids or BMD, MR analyses of BMD and lipids suggest that lipid levels have a causal impact on BMD, which is consistent with findings from clinical trials of lipid-lowering drugs, which have also increased BMD.
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Affiliation(s)
- Stacey S. Cherny
- Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Maxim B. Freidin
- Department of Twin Research and Genetic Epidemiology, School of Life Course Science, King’s College London, London, United Kingdom
| | - Frances M. K. Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Science, King’s College London, London, United Kingdom
| | - Gregory Livshits
- Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Twin Research and Genetic Epidemiology, School of Life Course Science, King’s College London, London, United Kingdom
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27
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Caldiroli A, Buoli M, van Haren NEM, de Nijs J, Altamura AC, Cahn W. The relationship of IQ and emotional processing with insula volume in schizophrenia. Schizophr Res 2018; 202:141-148. [PMID: 29954697 DOI: 10.1016/j.schres.2018.06.048] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 06/19/2018] [Accepted: 06/19/2018] [Indexed: 11/18/2022]
Abstract
OBJECTIVE The insula is involved in general and social cognition, in particular emotion regulation. Aim of this study is to investigate whether insula volume is associated with Intelligence Quotient (IQ) and emotional processing in schizophrenia patients versus healthy controls (HC). METHODS Magnetic resonance imaging (MRI) brain scans, IQ and emotional processing tests (Benton Facial Recognition Test [BFRT], Degraded Facial Affect Recognition Task [DFAR], Emotional Mentalizing Task [EMT]) were administered in 246 subjects (133 schizophrenia patients and 113 controls). First order linear regression analyses were performed with group as independent variable and IQ/emotional processing test scores as dependent variables. Second order stepwise linear regression analyses were performed with IQ/emotional processing test scores as independent variables (as well as intracranial volumes, age, gender and cannabis abuse) and right/left insula volumes as dependent ones. A final mediation analysis (Sobel test) was performed to verify if IQ or emotional processing test scores could explain the eventual differences in insula volumes between the two groups. RESULTS Schizophrenia patients presented lower insula volumes (left: F = 9.72, p < 0.01; right: F = 10.93, p < 0.01) as compared with healthy controls. Smaller insula volumes in schizophrenia patients are mediated by lower IQ scores (Sobel tests: 3.07, p < 0.01 for right insula; 2.72, p < 0.01 for left insula), but not by impairments in emotion processing. CONCLUSIONS IQ, but not emotional processing mediates smaller insula volumes in schizophrenia patients.
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Affiliation(s)
- Alice Caldiroli
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122 Milan, Italy; University Medical Center Utrecht, Department of Psychiatry, Brain Center Rudolf Magnus, the Netherlands
| | - Massimiliano Buoli
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122 Milan, Italy; University Medical Center Utrecht, Department of Psychiatry, Brain Center Rudolf Magnus, the Netherlands.
| | - Neeltje E M van Haren
- University Medical Center Utrecht, Department of Psychiatry, Brain Center Rudolf Magnus, the Netherlands; Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Jessica de Nijs
- University Medical Center Utrecht, Department of Psychiatry, Brain Center Rudolf Magnus, the Netherlands
| | - A Carlo Altamura
- Department of Psychiatry, University of Milan, Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122 Milan, Italy
| | - Wiepke Cahn
- University Medical Center Utrecht, Department of Psychiatry, Brain Center Rudolf Magnus, the Netherlands
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28
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van Bergen E, Snowling MJ, de Zeeuw EL, van Beijsterveldt CEM, Dolan CV, Boomsma DI. Why do children read more? The influence of reading ability on voluntary reading practices. J Child Psychol Psychiatry 2018; 59:1205-1214. [PMID: 29635740 DOI: 10.1111/jcpp.12910] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/12/2018] [Indexed: 11/25/2022]
Abstract
BACKGROUND This study investigates the causal relationships between reading and print exposure and investigates whether the amount children read outside school determines how well they read, or vice versa. Previous findings from behavioural studies suggest that reading predicts print exposure. Here, we use twin-data and apply the behaviour-genetic approach of direction of causality modelling, suggested by Heath et al. (), to investigate the causal relationships between these two traits. METHOD Partial data were available for a large sample of twin children (N = 11,559) and 262 siblings, all enrolled in the Netherlands Twin Register. Children were assessed around 7.5 years of age. Mothers completed questionnaires reporting children's time spent on reading activities and reading ability. Additional information on reading ability was available through teacher ratings and performance on national reading tests. For siblings reading test, results were available. RESULTS The reading ability of the twins was comparable to that of the siblings and national norms, showing that twin findings can be generalized to the population. A measurement model was specified with two latent variables, Reading Ability and Print Exposure, which correlated .41. Heritability analyses showed that Reading Ability was highly heritable, while genetic and environmental influences were equally important for Print Exposure. We exploited the fact that the two constructs differ in genetic architecture and fitted direction of causality models. The results supported a causal relationship running from Reading Ability to Print Exposure. CONCLUSIONS How much and how well children read are moderately correlated. Individual differences in print exposure are less heritable than individual differences in reading ability. Importantly, the present results suggest that it is the children's reading ability that determines how much they choose to read, rather than vice versa.
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Affiliation(s)
- Elsje van Bergen
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Experimental Psychology, University of Oxford, Oxford, UK
| | - Margaret J Snowling
- Experimental Psychology, University of Oxford, Oxford, UK.,St. John's College, Oxford, UK
| | - Eveline L de Zeeuw
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Conor V Dolan
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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29
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Ranlund S, Calafato S, Thygesen JH, Lin K, Cahn W, Crespo‐Facorro B, de Zwarte SM, Díez Á, Di Forti M, Iyegbe C, Jablensky A, Jones R, Hall M, Kahn R, Kalaydjieva L, Kravariti E, McDonald C, McIntosh AM, McQuillin A, Picchioni M, Prata DP, Rujescu D, Schulze K, Shaikh M, Toulopoulou T, van Haren N, van Os J, Vassos E, Walshe M, Lewis C, Murray RM, Powell J, Bramon E. A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains. Am J Med Genet B Neuropsychiatr Genet 2018; 177:21-34. [PMID: 28851104 PMCID: PMC5763362 DOI: 10.1002/ajmg.b.32581] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 07/24/2017] [Indexed: 12/26/2022]
Abstract
This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.
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Affiliation(s)
- Siri Ranlund
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | | | - Kuang Lin
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Wiepke Cahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Benedicto Crespo‐Facorro
- CIBERSAMCentro Investigación Biomédica en Red Salud MentalMadridSpain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of MedicineUniversity of Cantabria–IDIVALSantanderSpain
| | - Sonja M.C. de Zwarte
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Álvaro Díez
- Division of PsychiatryUniversity College LondonLondonUK
- Laboratory of Cognitive and Computational Neuroscience—Centre for Biomedical Technology (CTB)Complutense University and Technical University of MadridMadridSpain
| | - Marta Di Forti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Conrad Iyegbe
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Assen Jablensky
- Centre for Clinical Research in NeuropsychiatryThe University of Western AustraliaPerth, Western AustraliaAustralia
| | - Rebecca Jones
- Division of PsychiatryUniversity College LondonLondonUK
| | - Mei‐Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical SchoolMcLean HospitalBelmontMassachusetts
| | - Rene Kahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Luba Kalaydjieva
- Harry Perkins Institute of Medical Research and Centre for Medical ResearchThe University of Western AustraliaPerthAustralia
| | - Eugenia Kravariti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Colm McDonald
- The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience CentreNational University of Ireland GalwayGalwayIreland
| | - Andrew M. McIntosh
- Division of Psychiatry, University of EdinburghRoyal Edinburgh HospitalEdinburghUK
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
| | | | | | - Marco Picchioni
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Diana P. Prata
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Faculdade de Medicina, Instituto de Medicina MolecularUniversidade de LisboaPortugal
| | - Dan Rujescu
- Department of PsychiatryLudwig‐Maximilians University of MunichMunichGermany
- Department of Psychiatry, Psychotherapy and PsychosomaticsUniversity of Halle WittenbergHalleGermany
| | - Katja Schulze
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Madiha Shaikh
- North East London Foundation TrustLondonUK
- Research Department of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
| | - Timothea Toulopoulou
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychology, Bilkent UniversityMain CampusBilkent, AnkaraTurkey
- Department of PsychologyThe University of Hong Kong, Pokfulam RdHong Kong SARChina
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong KongThe Hong Kong Jockey Club Building for Interdisciplinary ResearchHong Kong SARChina
| | - Neeltje van Haren
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Jim van Os
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychiatry and Psychology, Maastricht University Medical CentreEURONMaastrichtThe Netherlands
| | - Evangelos Vassos
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Muriel Walshe
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Cathryn Lewis
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Robin M. Murray
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - John Powell
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Elvira Bramon
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
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Murray RM, Bhavsar V, Tripoli G, Howes O. 30 Years on: How the Neurodevelopmental Hypothesis of Schizophrenia Morphed Into the Developmental Risk Factor Model of Psychosis. Schizophr Bull 2017; 43:1190-1196. [PMID: 28981842 PMCID: PMC5737804 DOI: 10.1093/schbul/sbx121] [Citation(s) in RCA: 188] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
At its re-birth 30 years ago, the neurodevelopment hypothesis of schizophrenia focussed on aberrant genes and early neural hazards, but then it grew to include ideas concerning aberrant synaptic pruning in adolescence. The hypothesis had its own stormy development and it endured some difficult teenage years when a resurgence of interest in neurodegeneration threatened its survival. In early adult life, it over-reached itself with some reductionists claiming that schizophrenia was simply a neurodevelopmental disease. However, by age 30, the hypothesis has matured sufficiently to incorporated childhood and adult adversity, urban living and migration, as well as heavy cannabis use, as important risk factors. Thus, it morphed into the developmental risk factor model of psychosis and integrated new evidence concerning dysregulated striatal dopamine as the final step on the pathway linking risk factors to psychotic symptoms.
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Affiliation(s)
- Robin M Murray
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK,National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King’s College, London, UK,To whom correspondence should be addressed;
| | - Vishal Bhavsar
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK
| | - Giada Tripoli
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK
| | - Oliver Howes
- Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, UK,Psychiatric Imaging Group, Clinical Science Centre, Imperial College, London, UK
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31
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Toulopoulou T, Picchioni M, Mortensen PB, Petersen L. IQ, the Urban Environment, and Their Impact on Future Schizophrenia Risk in Men. Schizophr Bull 2017; 43:1056-1063. [PMID: 28338769 PMCID: PMC5581890 DOI: 10.1093/schbul/sbw147] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Exposure to an urban environment during early life and low IQ are 2 well-established risk factors for schizophrenia. It is not known, however, how these factors might relate to one another. Data were pooled from the North Jutland regional draft board IQ assessments and the Danish Conscription Registry for men born between 1955 and 1993. Excluding those who were followed up for less than 1 year after the assessment yielded a final cohort of 153170 men of whom 578 later developed a schizophrenia spectrum disorder. We found significant effects of having an urban birth, and also experiencing an increase in urbanicity before the age of 10 years, on adult schizophrenia risk. The effect of urban birth was independent of IQ. However, there was a significant interaction between childhood changes in urbanization in the first 10 years and IQ level on the future adult schizophrenia risk. In short, those subjects who moved to more or less urban areas before their 10th birthday lost the protective effect of IQ. When thinking about adult schizophrenia risk, the critical time window of childhood sensitivity to changes in urbanization seems to be linked to IQ. Given the prediction that by 2050, over 80% of the developed world's population will live in an urban environment, this represents a major future public health issue.
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Affiliation(s)
- Timothea Toulopoulou
- Department of Psychology, Bilkent University, Ankara, Turkey;,Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK;,Department of Psychology, The University of Hong Kong, Hong Kong SAR, China;,The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China;,To whom correspondence should be addressed; Department of Psychology, Bilkent University, Bilkent 06800, Ankara, Turkey; Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London SE5 8AF, UK; tel: +44-(0)20-7848-0100, fax: +44-(0)20-7848-0287, e-mail:
| | - Marco Picchioni
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Preben Bo Mortensen
- National Centre for Register-based Research, Aarhus University, Aarhus V, Denmark
| | - Liselotte Petersen
- National Centre for Register-based Research, Aarhus University, Aarhus V, Denmark
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32
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Castro-de-Araujo LFS, Kanaan RAA. First episode psychosis moderates the effect of gray matter volume on cognition. Psychiatry Res Neuroimaging 2017; 266:108-113. [PMID: 28644997 DOI: 10.1016/j.pscychresns.2017.06.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 06/13/2017] [Accepted: 06/14/2017] [Indexed: 11/30/2022]
Abstract
Patients with first episode psychosis (FEP) present with cognitive deficits and volume differences in certain brain areas. Brain volumetric information further correlates with cognitive testing, and multiple brain areas shows different strengths of correlation with the cognitive functions being tested. Traditionally, these cognitive functions are independently related to volumetric differences, but these functions share variance. Failing to account for this aspect of cognition hinders the proper representation of cognition in neuroimaging studies. We used modeling methods which account for this shared variance to investigate the differences of correlations between cognitive abilities and brain areas. A multiple-groups structured equation model (SEM) approach was used to design and test a model representing the relation between gray matter volumetric data and neuropsychological test scores in a sample of 100 Brazilian FEP patients and 94 controls. Models with a latent variable formed by neurological measures and reflecting cognitive measures performed better on fit tests. FEP moderated the relation between gray matter volumes and cognition by altering the profile of correlations between groups. This moderation had a large effect size. SEM provides a fine grained picture of the interdependence of structural brain changes and cognition.
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Affiliation(s)
- Luis F S Castro-de-Araujo
- CAPES Foundation, Ministry of Education of Brazil, Brasília, DF, Brazil; University of Melbourne, Department of Psychiatry, Austin Health, Heidelberg, Victoria, Australia.
| | - Richard A A Kanaan
- University of Melbourne, Department of Psychiatry, Austin Health, Heidelberg, Victoria, Australia.
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33
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Progressive cortical reorganisation: A framework for investigating structural changes in schizophrenia. Neurosci Biobehav Rev 2017; 79:1-13. [DOI: 10.1016/j.neubiorev.2017.04.028] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Revised: 04/26/2017] [Accepted: 04/26/2017] [Indexed: 12/27/2022]
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34
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Blokland GAM, Mesholam-Gately RI, Toulopoulou T, del Re EC, Lam M, DeLisi LE, Donohoe G, Walters JTR, Seidman LJ, Petryshen TL. Heritability of Neuropsychological Measures in Schizophrenia and Nonpsychiatric Populations: A Systematic Review and Meta-analysis. Schizophr Bull 2017; 43:788-800. [PMID: 27872257 PMCID: PMC5472145 DOI: 10.1093/schbul/sbw146] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Schizophrenia is characterized by neuropsychological deficits across many cognitive domains. Cognitive phenotypes with high heritability and genetic overlap with schizophrenia liability can help elucidate the mechanisms leading from genes to psychopathology. We performed a meta-analysis of 170 published twin and family heritability studies of >800 000 nonpsychiatric and schizophrenia subjects to accurately estimate heritability across many neuropsychological tests and cognitive domains. The proportion of total variance of each phenotype due to additive genetic effects (A), shared environment (C), and unshared environment and error (E), was calculated by averaging A, C, and E estimates across studies and weighting by sample size. Heritability ranged across phenotypes, likely due to differences in genetic and environmental effects, with the highest heritability for General Cognitive Ability (32%-67%), Verbal Ability (43%-72%), Visuospatial Ability (20%-80%), and Attention/Processing Speed (28%-74%), while the lowest heritability was observed for Executive Function (20%-40%). These results confirm that many cognitive phenotypes are under strong genetic influences. Heritability estimates were comparable in nonpsychiatric and schizophrenia samples, suggesting that environmental factors and illness-related moderators (eg, medication) do not substantially decrease heritability in schizophrenia samples, and that genetic studies in schizophrenia samples are informative for elucidating the genetic basis of cognitive deficits. Substantial genetic overlap between cognitive phenotypes and schizophrenia liability (average rg = -.58) in twin studies supports partially shared genetic etiology. It will be important to conduct comparative studies in well-powered samples to determine whether the same or different genes and genetic variants influence cognition in schizophrenia patients and the general population.
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Affiliation(s)
- Gabriëlla A. M. Blokland
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA;,Department of Psychiatry, Harvard Medical School, Boston, MA;,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Raquelle I. Mesholam-Gately
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Commonwealth Research Center, Harvard Medical School, Boston, MA;,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Timothea Toulopoulou
- Psychology Department, Bilkent University, Ankara, Turkey;,Department of Psychology, University of Hong Kong, Pokfulam, Hong Kong;,Department of Psychosis Studies, Institute of Psychiatry, King’s College London, London, UK
| | - Elisabetta C. del Re
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton, MA
| | - Max Lam
- Institute of Mental Health, Woodbridge Hospital, Singapore
| | - Lynn E. DeLisi
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton, MA
| | - Gary Donohoe
- School of Psychology, National University of Ireland, Galway, Ireland;,Neuropsychiatric Genetics Group, Department of Psychiatry and Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - James T. R. Walters
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | | | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA;,Commonwealth Research Center, Harvard Medical School, Boston, MA;,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Tracey L. Petryshen
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA;,Department of Psychiatry, Harvard Medical School, Boston, MA;,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
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35
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Bohlken MM, Brouwer RM, Mandl RCW, Kahn RS, Hulshoff Pol HE. Genetic Variation in Schizophrenia Liability is Shared With Intellectual Ability and Brain Structure. Schizophr Bull 2016; 42:1167-75. [PMID: 27056715 PMCID: PMC4988741 DOI: 10.1093/schbul/sbw034] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Alterations in intellectual ability and brain structure are important genetic markers for schizophrenia liability. How variations in these phenotypes interact with variance in schizophrenia liability due to genetic or environmental factors is an area of active investigation. Studying these genetic markers using a multivariate twin modeling approach can provide novel leads for (genetic) pathways of schizophrenia development. METHODS In a sample of 70 twins discordant for schizophrenia and 130 healthy control twins, structural equation modeling was applied to quantify unique contributions of genetic and environmental factors on human brain structure (cortical thickness, cortical surface and global white matter fractional anisotropy [FA]), intellectual ability and schizophrenia liability. RESULTS In total, up to 28.1% of the genetic variance (22.8% of total variance) in schizophrenia liability was shared with intelligence quotient (IQ), global-FA, cortical thickness, and cortical surface. The strongest contributor was IQ, sharing on average 16.4% of the genetic variance in schizophrenia liability, followed by cortical thickness (6.3%), global-FA (4.7%) and cortical surface (0.5%). Furthermore, we found that up to 57.4% of the variation due to environmental factors (4.6% of total variance) in schizophrenia was shared with IQ (34.2%) and cortical surface (13.4%). CONCLUSIONS Intellectual ability, FA and cortical thickness show significant and independent shared genetic variance with schizophrenia liability. This suggests that measuring brain-imaging phenotypes helps explain genetic variance in schizophrenia liability that is not captured by variation in IQ.
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Affiliation(s)
- Marc M Bohlken
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rachel M Brouwer
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - René C W Mandl
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - René S Kahn
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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36
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Franke B, Stein JL, Ripke S, Anttila V, Hibar DP, van Hulzen KJE, Arias-Vasquez A, Smoller JW, Nichols TE, Neale MC, McIntosh AM, Lee P, McMahon FJ, Meyer-Lindenberg A, Mattheisen M, Andreassen OA, Gruber O, Sachdev PS, Roiz-Santiañez R, Saykin AJ, Ehrlich S, Mather KA, Turner JA, Schwarz E, Thalamuthu A, Shugart YY, Ho YYW, Martin NG, Wright MJ, O'Donovan MC, Thompson PM, Neale BM, Medland SE, Sullivan PF. Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat Neurosci 2016; 19:420-431. [PMID: 26854805 PMCID: PMC4852730 DOI: 10.1038/nn.4228] [Citation(s) in RCA: 148] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Accepted: 12/22/2015] [Indexed: 12/12/2022]
Abstract
Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.
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Affiliation(s)
- Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jason L Stein
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
- Neurogenetics Program, Department of Neurology, UCLA School of Medicine, Los Angeles, USA
| | - Stephan Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, CCM, Berlin, Germany
| | - Verneri Anttila
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Derrek P Hibar
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Kimm J E van Hulzen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Alejandro Arias-Vasquez
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jordan W Smoller
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Thomas E Nichols
- FMRIB Centre, University of Oxford, United Kingdom
- Department of Statistics & WMG, University of Warwick, Coventry, United Kingdom
| | - Michael C Neale
- Departments of Psychiatry & Human Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
| | - Phil Lee
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Francis J McMahon
- Intramural Research Program, National Institutes of Health, US Dept of Health & Human Services, Bethesda, USA
| | - Andreas Meyer-Lindenberg
- Central Institute of Mental Health, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
| | - Manuel Mattheisen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus and Copenhagen, Denmark
- Center for integrated Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - Ole A Andreassen
- NORMENT - KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Oliver Gruber
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen, Germany
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales (UNSW), Sydney, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia
| | - Roberto Roiz-Santiañez
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
- Cibersam (Centro Investigación Biomédica en Red Salud Mental), Madrid, Spain
| | - Andrew J Saykin
- Center for Neuroimaging, Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, USA
- Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
| | - Stefan Ehrlich
- Department of Child and Adolescent Psychiatry, Faculty of Medicine and University Hospital, TU Dresden, Dresden, Germany
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales (UNSW), Sydney, Australia
| | - Jessica A Turner
- Georgia State University, Atlanta, USA
- Mind Research Network, Albuquerque, NM, USA
| | - Emanuel Schwarz
- Central Institute of Mental Health, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales (UNSW), Sydney, Australia
| | - Yin Yao Shugart
- Intramural Research Program, National Institutes of Health, US Dept of Health & Human Services, Bethesda, USA
| | - Yvonne YW Ho
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - Margaret J Wright
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Psychology, University of Queensland, Brisbane, Australia
| | | | | | - Michael C O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
- National Centre for Mental Health, Cardiff University, Cardiff, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
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Factor structure and heritability of endophenotypes in schizophrenia: findings from the Consortium on the Genetics of Schizophrenia (COGS-1). Schizophr Res 2015; 163:73-9. [PMID: 25682549 PMCID: PMC5944296 DOI: 10.1016/j.schres.2015.01.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 01/14/2015] [Accepted: 01/17/2015] [Indexed: 11/23/2022]
Abstract
BACKGROUND Although many endophenotypes for schizophrenia have been studied individually, few studies have examined the extent to which common neurocognitive and neurophysiological measures reflect shared versus unique endophenotypic factors. It may be possible to distill individual endophenotypes into composite measures that reflect dissociable, genetically informative elements. METHODS The first phase of the Consortium on the Genetics of Schizophrenia (COGS-1) is a multisite family study that collected neurocognitive and neurophysiological data between 2003 and 2008. For these analyses, participants included schizophrenia probands (n=83), their nonpsychotic siblings (n=151), and community comparison subjects (n=209) with complete data on a battery of 12 neurocognitive tests (assessing domains of working memory, declarative memory, vigilance, spatial ability, abstract reasoning, facial emotion processing, and motor speed) and 3 neurophysiological tasks reflecting inhibitory processing (P50 gating, prepulse inhibition and antisaccade tasks). Factor analyses were conducted on the measures for each subject group and across the entire sample. Heritability analyses of factors were performed using SOLAR. RESULTS Analyses yielded 5 distinct factors: 1) Episodic Memory, 2) Working Memory, 3) Perceptual Vigilance, 4) Visual Abstraction, and 5) Inhibitory Processing. Neurophysiological measures had low associations with these factors. The factor structure of endophenotypes was largely comparable across probands, siblings and controls. Significant heritability estimates for the factors ranged from 22% (Episodic Memory) to 39% (Visual Abstraction). CONCLUSIONS Neurocognitive measures reflect a meaningful amount of shared variance whereas the neurophysiological measures reflect largely unique contributions as endophenotypes for schizophrenia. Composite endophenotype measures may inform our neurobiological and genetic understanding of schizophrenia.
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