1
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Strom NI, Burton CL, Iyegbe C, Silzer T, Antonyan L, Pool R, Lemire M, Crowley JJ, Hottenga JJ, Ivanov VZ, Larsson H, Lichtenstein P, Magnusson P, Rück C, Schachar R, Wu HM, Cath D, Crosbie J, Mataix-Cols D, Boomsma DI, Mattheisen M, Meier SM, Smit DJA, Arnold PD. Genome-Wide Association Study of Obsessive-Compulsive Symptoms including 33,943 individuals from the general population. Mol Psychiatry 2024:10.1038/s41380-024-02489-6. [PMID: 38548983 DOI: 10.1038/s41380-024-02489-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/18/2024] [Accepted: 02/15/2024] [Indexed: 04/24/2024]
Abstract
While 1-2% of individuals meet the criteria for a clinical diagnosis of obsessive-compulsive disorder (OCD), many more (~13-38%) experience subclinical obsessive-compulsive symptoms (OCS) during their life. To characterize the genetic underpinnings of OCS and its genetic relationship to OCD, we conducted the largest genome-wide association study (GWAS) meta-analysis of parent- or self-reported OCS to date (N = 33,943 with complete phenotypic and genome-wide data), combining the results from seven large-scale population-based cohorts from Sweden, the Netherlands, England, and Canada (including six twin cohorts and one cohort of unrelated individuals). We found no genome-wide significant associations at the single-nucleotide polymorphism (SNP) or gene-level, but a polygenic risk score (PRS) based on the OCD GWAS previously published by the Psychiatric Genetics Consortium (PGC-OCD) was significantly associated with OCS (Pfixed = 3.06 × 10-5). Also, one curated gene set (Mootha Gluconeogenesis) reached Bonferroni-corrected significance (Ngenes = 28, Beta = 0.79, SE = 0.16, Pbon = 0.008). Expression of genes in this set is high at sites of insulin mediated glucose disposal. Dysregulated insulin signaling in the etiology of OCS has been suggested by a previous study describing a genetic overlap of OCS with insulin signaling-related traits in children and adolescents. We report a SNP heritability of 4.1% (P = 0.0044) in the meta-analyzed GWAS, and heritability estimates based on the twin cohorts of 33-43%. Genetic correlation analysis showed that OCS were most strongly associated with OCD (rG = 0.72, p = 0.0007) among all tested psychiatric disorders (N = 11). Of all 97 tested phenotypes, 24 showed a significant genetic correlation with OCS, and 66 traits showed concordant directions of effect with OCS and OCD. OCS have a significant polygenic contribution and share genetic risk with diagnosed OCD, supporting the hypothesis that OCD represents the extreme end of widely distributed OCS in the population.
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Affiliation(s)
- Nora I Strom
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany.
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden.
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
| | - Christie L Burton
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - Conrad Iyegbe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, USA
| | - Talisa Silzer
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - Lilit Antonyan
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Mathieu Lemire
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - James J Crowley
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
- Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jouke-Jan Hottenga
- Netherlands Twin Register, Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Volen Z Ivanov
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical sciences, Örebro University, Örebro, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Christian Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Russell Schachar
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - Hei Man Wu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, USA
| | - Danielle Cath
- Rijksuniversiteit Groningen and Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
- Department of Specialized Training, Drenthe Mental Health Care Institute, Assen, The Netherlands
| | - Jennifer Crosbie
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - David Mataix-Cols
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Dorret I Boomsma
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Netherlands Twin Register, Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, The Netherlands
| | - Manuel Mattheisen
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Community Health & Epidemiology, Dalhousie University, NS, Halifax, Canada
| | - Sandra M Meier
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Community Health & Epidemiology, Dalhousie University, NS, Halifax, Canada
| | - Dirk J A Smit
- Amsterdam UMC location University of Amsterdam, Department of Psychiatry, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Compulsivity Impulsivity and Attention, Amsterdam, The Netherlands
| | - Paul D Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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2
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Bergstedt J, Pasman JA, Ma Z, Harder A, Yao S, Parker N, Treur JL, Smit DJA, Frei O, Shadrin A, Meijsen JJ, Shen Q, Hägg S, Tornvall P, Buil A, Werge T, Hjerling-Leffler J, Als TD, Børglum AD, Lewis CM, McIntosh AM, Valdimarsdóttir UA, Andreassen OA, Sullivan PF, Lu Y, Fang F. Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease. medRxiv 2024:2023.09.01.23294931. [PMID: 37693619 PMCID: PMC10491387 DOI: 10.1101/2023.09.01.23294931] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genomic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying their comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and atherosclerotic CVD (ASCVD) revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial/lifestyle risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and demonstrated that the causal effects were partly explained by metabolic and psychosocial/lifestyle factors. The distinct signature of MDD-ASCVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.
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Affiliation(s)
- Jacob Bergstedt
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Joëlle A Pasman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ziyan Ma
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Arvid Harder
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Nadine Parker
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jorien L Treur
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Dirk J A Smit
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Joeri J Meijsen
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Qing Shen
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai, China
- Institute for Advanced Study, Tongji University, Shanghai, China
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Tornvall
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens Hjerling-Leffler
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Thomas D Als
- Department of Molecular Medicine (MOMA), Molecular Diagnostic Laboratory, Aarhus University Hospital, Aarhus, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
| | - Andrew M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Genomics and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Unnur A Valdimarsdóttir
- Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, NC, USA
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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3
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Bignardi G, Smit DJA, Vessel EA, Trupp MD, Ticini LF, Fisher SE, Polderman TJC. Genetic effects on variability in visual aesthetic evaluations are partially shared across visual domains. Commun Biol 2024; 7:55. [PMID: 38184755 PMCID: PMC10771521 DOI: 10.1038/s42003-023-05710-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 12/14/2023] [Indexed: 01/08/2024] Open
Abstract
The aesthetic values that individuals place on visual images are formed and shaped over a lifetime. However, whether the formation of visual aesthetic value is solely influenced by environmental exposure is still a matter of debate. Here, we considered differences in aesthetic value emerging across three visual domains: abstract images, scenes, and faces. We examined variability in two major dimensions of ordinary aesthetic experiences: taste-typicality and evaluation-bias. We build on two samples from the Australian Twin Registry where 1547 and 1231 monozygotic and dizygotic twins originally rated visual images belonging to the three domains. Genetic influences explained 26% to 41% of the variance in taste-typicality and evaluation-bias. Multivariate analyses showed that genetic effects were partially shared across visual domains. Results indicate that the heritability of major dimensions of aesthetic evaluations is comparable to that of other complex social traits, albeit lower than for other complex cognitive traits. The exception was taste-typicality for abstract images, for which we found only shared and unique environmental influences. Our study reveals that diverse sources of genetic and environmental variation influence the formation of aesthetic value across distinct visual domains and provides improved metrics to assess inter-individual differences in aesthetic value.
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Affiliation(s)
- Giacomo Bignardi
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.
- Max Planck School of Cognition, Stephanstrasse 1a, Leipzig, Germany.
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC, Amsterdam, The Netherlands
| | - Edward A Vessel
- Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany
- Department of Psychology, City College, City University of New York, New York, NY, USA
| | - MacKenzie D Trupp
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Luca F Ticini
- Department of Psychology, Webster Vienna Private University, Vienna, Austria
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Tinca J C Polderman
- Clinical Developmental Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- VKC Psyche, Child and Adolescent Psychiatry and Psychosocial Care, Amsterdam UMC, Amsterdam, The Netherlands
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4
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Bangel KA, Bais M, Eijsker N, Schuurman PR, van den Munckhof P, Figee M, Smit DJA, Denys D. Acute effects of deep brain stimulation on brain function in obsessive-compulsive disorder. Clin Neurophysiol 2023; 148:109-117. [PMID: 36774324 DOI: 10.1016/j.clinph.2022.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 12/08/2022] [Accepted: 12/24/2022] [Indexed: 01/24/2023]
Abstract
OBJECTIVE Deep brain stimulation (DBS) is an effective treatment for refractory obsessive-compulsive disorder (OCD) yet neural markers of optimized stimulation parameters are largely unknown. We aimed to describe (sub-)cortical electrophysiological responses to acute DBS at various voltages in OCD. METHODS We explored how DBS doses between 3-5 V delivered to the ventral anterior limb of the internal capsule of five OCD patients affected electroencephalograms and intracranial local field potentials (LFPs). We focused on theta power/ phase-stability, given their previously established role in DBS for OCD. RESULTS Cortical theta power and theta phase-stability did not increase significantly with DBS voltage. DBS-induced theta power peaks were seen at the previously defined individualized therapeutic voltage. Although LFP power generally increased with DBS voltages, this occurred mostly in frequency peaks that overlapped with stimulation artifacts limiting its interpretability. Though highly idiosyncratic, three subjects showed significant acute DBS effects on electroencephalogram theta power and four subjects showed significant carry-over effects (pre-vs post DBS, unstimulated) on LFP and electroencephalogram theta power. CONCLUSIONS Our findings challenge the presence of a consistent dose-response relationship between stimulation voltage and brain activity. SIGNIFICANCE Theta power may be investigated further as a neurophysiological marker to aid personalized DBS voltage optimization in OCD.
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Affiliation(s)
- Katrin A Bangel
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, the Netherlands; Institute of Neuroscience, The Medical School, Newcastle University, NE2 4HH, UK; Department of Medical Physics and Clinical Engineering, Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK; Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Melisse Bais
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Nadine Eijsker
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - P Richard Schuurman
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Pepijn van den Munckhof
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Martijn Figee
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Dirk J A Smit
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands.
| | - Damiaan Denys
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Amsterdam, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands; The Netherlands Institute for Neuroscience, Amsterdam, the Netherlands
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5
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Fridgeirsson EA, Bais MN, Eijsker N, Thomas RM, Smit DJA, Bergfeld IO, Schuurman PR, van den Munckhof P, de Koning P, Vulink N, Figee M, Mazaheri A, van Wingen GA, Denys D. Patient specific intracranial neural signatures of obsessions and compulsions in the ventral striatum. J Neural Eng 2023; 20. [PMID: 36827705 DOI: 10.1088/1741-2552/acbee1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 02/24/2023] [Indexed: 02/26/2023]
Abstract
Objective. Deep brain stimulation is a treatment option for patients with refractory obsessive-compulsive disorder. A new generation of stimulators hold promise for closed loop stimulation, with adaptive stimulation in response to biologic signals. Here we aimed to discover a suitable biomarker in the ventral striatum in patients with obsessive compulsive disorder using local field potentials.Approach.We induced obsessions and compulsions in 11 patients undergoing deep brain stimulation treatment using a symptom provocation task. Then we trained machine learning models to predict symptoms using the recorded intracranial signal from the deep brain stimulation electrodes.Main results.Average areas under the receiver operating characteristics curve were 62.1% for obsessions and 78.2% for compulsions for patient specific models. For obsessions it reached over 85% in one patient, whereas performance was near chance level when the model was trained across patients. Optimal performances for obsessions and compulsions was obtained at different recording sites.Significance. The results from this study suggest that closed loop stimulation may be a viable option for obsessive-compulsive disorder, but that intracranial biomarkers are patient and not disorder specific.Clinical Trial:Netherlands trial registry NL7486.
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Affiliation(s)
- Egill A Fridgeirsson
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Melisse N Bais
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Nadine Eijsker
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Rajat M Thomas
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Isidoor O Bergfeld
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - P Richard Schuurman
- Department of Neurosurgery, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Pepijn van den Munckhof
- Department of Neurosurgery, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Pelle de Koning
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
| | - Nienke Vulink
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
| | - Martijn Figee
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Ali Mazaheri
- School of Psychology, University of Birmingham, Birmingham, United Kingdom.,Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
| | - Guido A van Wingen
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Amsterdam, The Netherlands.,The Netherlands institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
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6
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Liu S, Smit DJA, Abdellaoui A, van Wingen GA, Verweij KJH. Brain Structure and Function Show Distinct Relations With Genetic Predispositions to Mental Health and Cognition. Biol Psychiatry Cogn Neurosci Neuroimaging 2023; 8:300-310. [PMID: 35961582 DOI: 10.1016/j.bpsc.2022.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/09/2022] [Accepted: 08/01/2022] [Indexed: 10/15/2022]
Abstract
BACKGROUND Mental health and cognitive achievement are partly heritable, highly polygenic, and associated with brain variations in structure and function. However, the underlying neural mechanisms remain unclear. METHODS We investigated the association between genetic predispositions to various mental health and cognitive traits and a large set of structural and functional brain measures from the UK Biobank (N = 36,799). We also applied linkage disequilibrium score regression to estimate the genetic correlations between various traits and brain measures based on genome-wide data. To decompose the complex association patterns, we performed a multivariate partial least squares model of the genetic and imaging modalities. RESULTS The univariate analyses showed that certain traits were related to brain structure (significant genetic correlations with total cortical surface area from rg = -0.101 for smoking initiation to rg = 0.230 for cognitive ability), while other traits were related to brain function (significant genetic correlations with functional connectivity from rg = -0.161 for educational attainment to rg = 0.318 for schizophrenia). The multivariate analysis showed that genetic predispositions to attention-deficit/hyperactivity disorder, smoking initiation, and cognitive traits had stronger associations with brain structure than with brain function, whereas genetic predispositions to most other psychiatric disorders had stronger associations with brain function than with brain structure. CONCLUSIONS These results reveal that genetic predispositions to mental health and cognitive traits have distinct brain profiles.
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Affiliation(s)
- Shu Liu
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - Dirk J A Smit
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Abdel Abdellaoui
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Guido A van Wingen
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - Karin J H Verweij
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
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7
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Chavez-Baldini U, Nieman DH, Keestra A, Lok A, Mocking RJT, de Koning P, Krzhizhanovskaya VV, Bockting CL, van Rooijen G, Smit DJA, Sutterland AL, Verweij KJH, van Wingen G, Wigman JT, Vulink NC, Denys D. The relationship between cognitive functioning and psychopathology in patients with psychiatric disorders: a transdiagnostic network analysis. Psychol Med 2023; 53:476-485. [PMID: 34165065 PMCID: PMC9899564 DOI: 10.1017/s0033291721001781] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 03/05/2021] [Accepted: 04/21/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND Patients with psychiatric disorders often experience cognitive dysfunction, but the precise relationship between cognitive deficits and psychopathology remains unclear. We investigated the relationships between domains of cognitive functioning and psychopathology in a transdiagnostic sample using a data-driven approach. METHODS Cross-sectional network analyses were conducted to investigate the relationships between domains of psychopathology and cognitive functioning and detect clusters in the network. This naturalistic transdiagnostic sample consists of 1016 psychiatric patients who have a variety of psychiatric diagnoses, such as depressive disorders, anxiety disorders, obsessive-compulsive and related disorders, and schizophrenia spectrum and other psychotic disorders. Psychopathology symptoms were assessed using various questionnaires. Core cognitive domains were assessed with a battery of automated tests. RESULTS Network analysis detected three clusters that we labelled: general psychopathology, substance use, and cognition. Depressive and anxiety symptoms, verbal memory, and visual attention were the most central nodes in the network. Most associations between cognitive functioning and symptoms were negative, i.e. increased symptom severity was associated with worse cognitive functioning. Cannabis use, (subclinical) psychotic experiences, and anhedonia had the strongest total negative relationships with cognitive variables. CONCLUSIONS Cognitive functioning and psychopathology are independent but related dimensions, which interact in a transdiagnostic manner. Depression, anxiety, verbal memory, and visual attention are especially relevant in this network and can be considered independent transdiagnostic targets for research and treatment in psychiatry. Moreover, future research on cognitive functioning in psychopathology should take a transdiagnostic approach, focusing on symptom-specific interactions with cognitive domains rather than investigating cognitive functioning within diagnostic categories.
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Affiliation(s)
- UnYoung Chavez-Baldini
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Dorien H. Nieman
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Amos Keestra
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Anja Lok
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Roel J. T. Mocking
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Pelle de Koning
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | | | - Claudi L.H. Bockting
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Geeske van Rooijen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Dirk J. A. Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Arjen L. Sutterland
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Karin J. H. Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Guido van Wingen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Johanna T.W. Wigman
- University Medical Center Groningen, University Center Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, CC72, P.O. Box 30.001, 9700 RB, Groningen, The Netherlands
| | - Nienke C. Vulink
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
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Strom NI, Smit DJA, Silzer T, Iyegbe C, Burton CL, Pool R, Lemire M, Crowley JJ, Hottenga JJ, Ivanov VZ, Larsson H, Lichtenstein P, Magnusson P, Rück C, Schachar RJ, Wu HM, Meier SM, Crosbie J, Arnold PD, Mattheisen M, Boomsma DI, Mataix-Cols D, Cath D. Correction: Meta-analysis of genome-wide association studies of hoarding symptoms in 27,537 individuals. Transl Psychiatry 2022; 12:521. [PMID: 36550104 PMCID: PMC9780311 DOI: 10.1038/s41398-022-02288-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Nora I. Strom
- grid.7468.d0000 0001 2248 7639Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany ,grid.411095.80000 0004 0477 2585Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany ,grid.467087.a0000 0004 0442 1056Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden ,grid.7048.b0000 0001 1956 2722Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Dirk J. A. Smit
- grid.509540.d0000 0004 6880 3010Department of Psychiatry, Amsterdam University Medical Centers, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Talisa Silzer
- grid.42327.300000 0004 0473 9646Department of Psychiatry, Hospital for Sick Children, Toronto, ON Canada
| | - Conrad Iyegbe
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, England ,grid.59734.3c0000 0001 0670 2351Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, USA
| | - Christie L. Burton
- grid.42327.300000 0004 0473 9646Department of Psychiatry, Hospital for Sick Children, Toronto, ON Canada
| | - René Pool
- grid.12380.380000 0004 1754 9227Department of Biological Psychology, Vrije Universiteit, Amsterdam, Netherlands
| | - Mathieu Lemire
- grid.42327.300000 0004 0473 9646Department of Psychiatry, Hospital for Sick Children, Toronto, ON Canada
| | - James J. Crowley
- grid.467087.a0000 0004 0442 1056Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden ,grid.10698.360000000122483208Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Jouke-Jan Hottenga
- grid.12380.380000 0004 1754 9227Netherlands Twin Register, Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Volen Z. Ivanov
- grid.467087.a0000 0004 0442 1056Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Henrik Larsson
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden ,grid.15895.300000 0001 0738 8966School of Medical sciences, Örebro University, Örebro, Sweden
| | - Paul Lichtenstein
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik Magnusson
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Christian Rück
- grid.467087.a0000 0004 0442 1056Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Russell J. Schachar
- grid.42327.300000 0004 0473 9646Department of Psychiatry, Hospital for Sick Children, Toronto, ON Canada
| | - Hei Man Wu
- grid.59734.3c0000 0001 0670 2351Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, USA
| | - Sandra M. Meier
- grid.55602.340000 0004 1936 8200Department of Psychiatry, Dalhousie University, Halifax, NS Canada ,grid.55602.340000 0004 1936 8200Community Health & Epidemiology, Dalhousie University, NS Dalhousie, Canada
| | - Jennifer Crosbie
- grid.42327.300000 0004 0473 9646Department of Psychiatry, Hospital for Sick Children, Toronto, ON Canada
| | - Paul D. Arnold
- grid.22072.350000 0004 1936 7697The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB Canada ,grid.22072.350000 0004 1936 7697Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB Canada
| | - Manuel Mattheisen
- grid.411095.80000 0004 0477 2585Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany ,grid.55602.340000 0004 1936 8200Department of Psychiatry, Dalhousie University, Halifax, NS Canada ,grid.55602.340000 0004 1936 8200Community Health & Epidemiology, Dalhousie University, NS Dalhousie, Canada
| | - Dorret I. Boomsma
- grid.12380.380000 0004 1754 9227Netherlands Twin Register, Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands ,grid.16872.3a0000 0004 0435 165XAmsterdam Public Health Research Institute, Amsterdam, The Netherlands ,Amsterdam Reproduction and Development Research Institute, Amsterdam, The Netherlands
| | - David Mataix-Cols
- grid.467087.a0000 0004 0442 1056Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Danielle Cath
- grid.4494.d0000 0000 9558 4598Rijksuniversiteit Groningen and Department of Psychiatry, University Medical Center Groningen, Groningen, Netherlands ,Department of specialized training, Drenthe Mental Health Care Institute, Assen, The Netherlands
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9
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Strom NI, Smit DJA, Silzer T, Iyegbe C, Burton CL, Pool R, Lemire M, Crowley JJ, Hottenga JJ, Ivanov VZ, Larsson H, Lichtenstein P, Magnusson P, Rück C, Schachar RJ, Wu HM, Meier SM, Crosbie J, Arnold PD, Mattheisen M, Boomsma DI, Mataix-Cols D, Cath D. Meta-analysis of genome-wide association studies of hoarding symptoms in 27,537 individuals. Transl Psychiatry 2022; 12:479. [PMID: 36379924 PMCID: PMC9666541 DOI: 10.1038/s41398-022-02248-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 10/27/2022] [Accepted: 11/02/2022] [Indexed: 11/16/2022] Open
Abstract
Hoarding Disorder (HD) is a mental disorder characterized by persistent difficulties discarding or parting with possessions, often resulting in cluttered living spaces, distress, and impairment. Its etiology is largely unknown, but twin studies suggest that it is moderately heritable. In this study, we pooled phenotypic and genomic data from seven international cohorts (N = 27,537 individuals) and conducted a genome wide association study (GWAS) meta-analysis of parent- or self-reported hoarding symptoms (HS). We followed up the results with gene-based and gene-set analyses, as well as leave-one-out HS polygenic risk score (PRS) analyses. To examine a possible genetic association between hoarding symptoms and other phenotypes we conducted cross-trait PRS analyses. Though we did not report any genome-wide significant SNPs, we report heritability estimates for the twin-cohorts between 26-48%, and a SNP-heritability of 11% for an unrelated sub-cohort. Cross-trait PRS analyses showed that the genetic risk for schizophrenia and autism spectrum disorder were significantly associated with hoarding symptoms. We also found suggestive evidence for an association with educational attainment. There were no significant associations with other phenotypes previously linked to HD, such as obsessive-compulsive disorder, depression, anxiety, or attention-deficit hyperactivity disorder. To conclude, we found that HS are heritable, confirming and extending previous twin studies but we had limited power to detect any genome-wide significant loci. Much larger samples will be needed to further extend these findings and reach a "gene discovery zone". To move the field forward, future research should not only include genetic analyses of quantitative hoarding traits in larger samples, but also in samples of individuals meeting strict diagnostic criteria for HD, and more ethnically diverse samples.
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Affiliation(s)
- Nora I Strom
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany.
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden.
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam University Medical Centers, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Talisa Silzer
- Department of Psychiatry, Hospital for Sick Children, Toronto, ON, Canada
| | - Conrad Iyegbe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, USA
| | - Christie L Burton
- Department of Psychiatry, Hospital for Sick Children, Toronto, ON, Canada
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, Netherlands
| | - Mathieu Lemire
- Department of Psychiatry, Hospital for Sick Children, Toronto, ON, Canada
| | - James J Crowley
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
- Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Jouke-Jan Hottenga
- Netherlands Twin Register, Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Volen Z Ivanov
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical sciences, Örebro University, Örebro, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Christian Rück
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Russell J Schachar
- Department of Psychiatry, Hospital for Sick Children, Toronto, ON, Canada
| | - Hei Man Wu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York, USA
| | - Sandra M Meier
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Community Health & Epidemiology, Dalhousie University, NS, Dalhousie, Canada
| | - Jennifer Crosbie
- Department of Psychiatry, Hospital for Sick Children, Toronto, ON, Canada
| | - Paul D Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Manuel Mattheisen
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Community Health & Epidemiology, Dalhousie University, NS, Dalhousie, Canada
| | - Dorret I Boomsma
- Netherlands Twin Register, Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, The Netherlands
| | - David Mataix-Cols
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Sweden
| | - Danielle Cath
- Rijksuniversiteit Groningen and Department of Psychiatry, University Medical Center Groningen, Groningen, Netherlands
- Department of specialized training, Drenthe Mental Health Care Institute, Assen, The Netherlands
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10
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Fraga-González G, Smit DJA, Van der Molen MJW, Tijms J, Stam CJ, de Geus EJC, Van der Molen MW. Corrigendum: Graph Analysis of EEG Functional Connectivity Networks During a Letter-Speech Sound Binding Task in Adult Dyslexics. Front Psychol 2022; 12:828043. [PMID: 35069402 PMCID: PMC8767144 DOI: 10.3389/fpsyg.2021.828043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 12/03/2021] [Indexed: 12/03/2022] Open
Affiliation(s)
- Gorka Fraga-González
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Rudolf Berlin Center, Amsterdam, Netherlands.,Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland
| | - Dirk J A Smit
- Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, Netherlands
| | - Melle J W Van der Molen
- Institute of Psychology, Leiden University, Leiden, Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
| | - Jurgen Tijms
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Rudolf Berlin Center, Amsterdam, Netherlands.,RID Institute, Amsterdam, Netherlands
| | - Cornelis J Stam
- Department of Clinical Neuropsychology and MEG Center, VU University Medical Center, Amsterdam, Netherlands
| | - Eco J C de Geus
- Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, Netherlands
| | - Maurits W Van der Molen
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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11
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Eijsker N, Schröder A, Liebrand LC, Smit DJA, van Wingen G, Denys D. White matter abnormalities in misophonia. Neuroimage Clin 2022; 32:102787. [PMID: 34461433 PMCID: PMC8405911 DOI: 10.1016/j.nicl.2021.102787] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 08/02/2021] [Accepted: 08/06/2021] [Indexed: 11/18/2022]
Abstract
Misophonia is a condition in which specific ordinary sounds provoke disproportionately strong negative affect and physiological arousal. Evidence for neurobiological abnormalities underlying misophonia is scarce. Since many psychiatric disorders show white matter (WM) abnormalities, we tested for both macro and micro-structural WM differences between misophonia patients and healthy controls. We collected T1-weighted and diffusion-weighted magnetic resonance images from 24 patients and 25 matched controls. We tested for group differences in WM volume using whole-brain voxel-based morphometry and used the significant voxels from this analysis as seeds for probabilistic tractography. After calculation of diffusion tensors, we compared group means for fractional anisotropy, mean diffusivity, and directional diffusivities, and applied tract-based spatial statistics for voxel-wise comparison. Compared to controls, patients had greater left-hemispheric WM volumes in the inferior fronto-occipital fasciculus, anterior thalamic radiation, and body of the corpus callosum connecting bilateral superior frontal gyri. Patients also had lower averaged radial and mean diffusivities and voxel-wise comparison indicated large and widespread clusters of lower mean diffusivity. We found both macro and microstructural WM abnormalities in our misophonia sample, suggesting misophonia symptomatology is associated with WM alterations. These biological alterations may be related to differences in social-emotional processing, particularly recognition of facial affect, and to attention for affective information.
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Affiliation(s)
- Nadine Eijsker
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129, Amsterdam 1001 NK, the Netherlands
| | - Arjan Schröder
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129, Amsterdam 1001 NK, the Netherlands
| | - Luka C Liebrand
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129, Amsterdam 1001 NK, the Netherlands; Amsterdam University Medical Centers, University of Amsterdam, Department of Biomedical Engineering and Physics, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands
| | - Dirk J A Smit
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129, Amsterdam 1001 NK, the Netherlands
| | - Guido van Wingen
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129, Amsterdam 1001 NK, the Netherlands
| | - Damiaan Denys
- Amsterdam University Medical Centers, University of Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129, Amsterdam 1001 NK, the Netherlands.
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12
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Smit DJA, Bakker M, Abdellaoui A, Hoetink AE, Vulink N, Denys D. A genome-wide association study of a rage-related misophonia symptom and the genetic link with audiological traits, psychiatric disorders, and personality. Front Neurosci 2022; 16:971752. [PMID: 36760791 PMCID: PMC9902885 DOI: 10.3389/fnins.2022.971752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 12/21/2022] [Indexed: 01/26/2023] Open
Abstract
Introduction People with misophonia experience strong negative emotional responses to sounds and associated stimuli-mostly human produced-to an extent that it may cause impairment in social functioning. The exact nature of the disorder remains a matter of ongoing research and debate. Here, we investigated the genetic etiology of misophonia to understand contributing genetic factors and shed light on individual differences in characteristics that are related to the disorder. Methods For misophonia, we used an unpublished genome-wide association study (GWAS) from genetic service provider 23andMe, Inc., on a self-report item probing a single common misophonic symptom: the occurrence of rage when others produce eating sounds. First, we used gene-based and functional annotation analyses to explore neurobiological determinants of the rage-related misophonia symptom. Next, we calculated genetic correlations (r G) of this rage-related misophonia symptom GWAS with a wide range of traits and disorders from audiology (tinnitus, hearing performance, and hearing trauma), psychiatry, neurology, and personality traits. Results The rage-related misophonia symptom was significantly correlated with tinnitus, major depression disorder (MDD), post-traumatic stress disorder (PTSD), and generalized anxiety disorder (GAD; 0.12 < r G < 0.22). Stronger genetic correlations (0.21 < r G < 0.42) were observed for two clusters of personality traits: a guilt/neuroticism and an irritability/sensitivity cluster. Our results showed no genetic correlation with attention deficit and hyperactivity disorder, obsessive-compulsive disorder, and psychotic disorders. A negative correlation with autism spectrum disorder (ASD) was found, which may be surprising given the previously reported comorbidities and the sensory sensitivity reported in ASD. Clustering algorithms showed that rage-related misophonia consistently clustered with MDD, generalized anxiety, PTSD, and related personality traits. Discussion We conclude that-based on the genetics of a common misophonia symptom-misophonia most strongly clusters with psychiatric disorders and a personality profile consistent with anxiety and PTSD.
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Affiliation(s)
- Dirk J A Smit
- Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Melissa Bakker
- Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Alexander E Hoetink
- Department of Otorhinolaryngology-Head and Neck Surgery, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, Netherlands
| | - Nienke Vulink
- Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
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13
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Fraga-González G, Smit DJA, Van der Molen MJW, Tijms J, Stam CJ, de Geus EJC, Van der Molen MW. Graph Analysis of EEG Functional Connectivity Networks During a Letter-Speech Sound Binding Task in Adult Dyslexics. Front Psychol 2021; 12:767839. [PMID: 34899515 PMCID: PMC8658451 DOI: 10.3389/fpsyg.2021.767839] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/26/2021] [Indexed: 11/16/2022] Open
Abstract
We performed an EEG graph analysis on data from 31 typical readers (22.27 ± 2.53 y/o) and 24 dyslexics (22.99 ± 2.29 y/o), recorded while they were engaged in an audiovisual task and during resting-state. The task simulates reading acquisition as participants learned new letter-sound mappings via feedback. EEG data was filtered for the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands. We computed the Phase Lag Index (PLI) to provide an estimate of the functional connectivity between all pairs of electrodes per band. Then, networks were constructed using a Minimum Spanning Tree (MST), a unique sub-graph connecting all nodes (electrodes) without loops, aimed at minimizing bias in between groups and conditions comparisons. Both groups showed a comparable accuracy increase during task blocks, indicating that they correctly learned the new associations. The EEG results revealed lower task-specific theta connectivity, and lower theta degree correlation over both rest and task recordings, indicating less network integration in dyslexics compared to typical readers. This pattern suggests a role of theta oscillations in dyslexia and may reflect differences in task engagement between the groups, although robust correlations between MST metrics and performance indices were lacking.
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Affiliation(s)
- Gorka Fraga-González
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Rudolf Berlin Center, Amsterdam, Netherlands.,Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland
| | - Dirk J A Smit
- Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, Netherlands
| | - Melle J W Van der Molen
- Institute of Psychology, Leiden University, Leiden, Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
| | - Jurgen Tijms
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Rudolf Berlin Center, Amsterdam, Netherlands.,RID Institute, Amsterdam, Netherlands
| | - Cornelis J Stam
- Department of Clinical Neuropsychology and MEG Center, VU University Medical Center, Amsterdam, Netherlands
| | - Eco J C de Geus
- Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, Netherlands
| | - Maurits W Van der Molen
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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14
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Smit DJA, Andreassen OA, Boomsma DI, Burwell SJ, Chorlian DB, de Geus EJC, Elvsåshagen T, Gordon RL, Harper J, Hegerl U, Hensch T, Iacono WG, Jawinski P, Jönsson EG, Luykx JJ, Magne CL, Malone SM, Medland SE, Meyers JL, Moberget T, Porjesz B, Sander C, Sisodiya SM, Thompson PM, van Beijsterveldt CEM, van Dellen E, Via M, Wright MJ. Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity. Brain Behav 2021; 11:e02188. [PMID: 34291596 PMCID: PMC8413828 DOI: 10.1002/brb3.2188] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 03/12/2021] [Accepted: 04/30/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND AND PURPOSE The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.
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Affiliation(s)
- Dirk J A Smit
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Scott J Burwell
- Department of Psychology, Minnesota Center for Twin and Family Research, University of Minnesota, Minneapolis, MN, USA.,Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Reyna L Gordon
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jeremy Harper
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Goethe Universität Frankfurt am Main, Frankfurt, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany.,LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,IU International University, Erfurt, Germany
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Philippe Jawinski
- LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Erik G Jönsson
- TOP-Norment, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Outpatient Second Opinion Clinic, GGNet Mental Health, Apeldoorn, The Netherlands
| | - Cyrille L Magne
- Psychology Department, Middle Tennessee State University, Murfreesboro, TN, USA.,Literacy Studies Ph.D. Program, Middle Tennessee State University, Mufreesboro, TN, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA.,Department of Psychiatry, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Torgeir Moberget
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont-St-Peter, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Edwin van Dellen
- Department of Psychiatry, Department of Intensive Care Medicine, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marc Via
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, and Institute of Neurosciences (UBNeuro), Universitat de Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Spain
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
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15
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Babiloni C, Arakaki X, Bonanni L, Bujan A, Carrillo MC, Del Percio C, Edelmayer RM, Egan G, Elahh FM, Evans A, Ferri R, Frisoni GB, Güntekin B, Hainsworth A, Hampel H, Jelic V, Jeong J, Kim DK, Kramberger M, Kumar S, Lizio R, Nobili F, Noce G, Puce A, Ritter P, Smit DJA, Soricelli A, Teipel S, Tucci F, Sachdev P, Valdes-Sosa M, Valdes-Sosa P, Vergallo A, Yener G. EEG measures for clinical research in major vascular cognitive impairment: recommendations by an expert panel. Neurobiol Aging 2021; 103:78-97. [PMID: 33845399 DOI: 10.1016/j.neurobiolaging.2021.03.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 02/17/2021] [Accepted: 03/05/2021] [Indexed: 11/22/2022]
Abstract
Vascular contribution to cognitive impairment (VCI) and dementia is related to etiologies that may affect the neurophysiological mechanisms regulating brain arousal and generating electroencephalographic (EEG) activity. A multidisciplinary expert panel reviewed the clinical literature and reached consensus about the EEG measures consistently found as abnormal in VCI patients with dementia. As compared to cognitively unimpaired individuals, those VCI patients showed (1) smaller amplitude of resting state alpha (8-12 Hz) rhythms dominant in posterior regions; (2) widespread increases in amplitude of delta (< 4 Hz) and theta (4-8 Hz) rhythms; and (3) delayed N200/P300 peak latencies in averaged event-related potentials, especially during the detection of auditory rare target stimuli requiring participants' responses in "oddball" paradigms. The expert panel formulated the following recommendations: (1) the above EEG measures are not specific for VCI and should not be used for its diagnosis; (2) they may be considered as "neural synchronization" biomarkers to enlighten the relationships between features of the VCI-related cerebrovascular lesions and abnormalities in neurophysiological brain mechanisms; and (3) they may be tested in future clinical trials as prognostic biomarkers and endpoints of interventions aimed at normalizing background brain excitability and vigilance in wakefulness.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy; San Raffaele Cassino, Cassino, FR, Italy.
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G D'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Ana Bujan
- Psychological Neuroscience Lab, School of Psychology, University of Minho, Portugal
| | | | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Gary Egan
- Foundation Director of the Monash Biomedical Imaging (MBI) research facilities, Monash University, Clayton, Australia
| | - Fanny M Elahh
- Memory and Aging Center, University of California, San Francisco
| | - Alan Evans
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | | | - Giovanni B Frisoni
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey; REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
| | - Atticus Hainsworth
- University of London St George's Molecular and Clinical Sciences Research Institute, London, UK
| | - Harald Hampel
- Sorbonne University, GRC No. 21, Alzheimer Precision Medicine, Pitié-Salpêtrière Hospital, Paris, France
| | - Vesna Jelic
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Jaeseung Jeong
- Department of Bio and Brain Engineering/Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Doh Kwan Kim
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Suwon, South Korea
| | - Milica Kramberger
- Center for cognitive and movement disorders, Department of neurology, University Medical Center Ljubljana, Slovenia
| | - Sanjeev Kumar
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | | | - Flavio Nobili
- Clinica neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy; Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI)
| | | | - Aina Puce
- Department of Psychological and Brain Sciences at Indiana University in Bloomington, Indiana, USA
| | - Petra Ritter
- Brain Simulation Section, Department of Neurology, Charité Universitätsmedizin and Berlin Institute of Health, Berlin, Germany; Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Dirk J A Smit
- Department of Psychiatry Academisch Medisch Centrum Universiteit van Amsterdam, Amsterdam, the Netherlands
| | - Andrea Soricelli
- IRCCS SDN, Naples, Italy; Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Stefan Teipel
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany; German Center for Neurodegenerative Diseases (DZNE) - Rostock/Greifswald, Rostock, Germany
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Perminder Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales; Neuropsychiatric Institute, The Prince of Wales Hospital, Sydney, Australia
| | | | - Pedro Valdes-Sosa
- Cuban Neuroscience Center, Havana, Cuba; Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Andrea Vergallo
- Sorbonne University, GRC No. 21, Alzheimer Precision Medicine, Pitié-Salpêtrière Hospital, Paris, France
| | - Görsev Yener
- Izmir Biomedicine and Genome Center. Dokuz Eylul University Health Campus, Izmir, Turkey
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16
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Stevelink R, Luykx JJ, Lin BD, Leu C, Lal D, Smith AW, Schijven D, Carpay JA, Rademaker K, Rodrigues Baldez RA, Devinsky O, Braun KPJ, Jansen FE, Smit DJA, Koeleman BPC. Shared genetic basis between genetic generalized epilepsy and background electroencephalographic oscillations. Epilepsia 2021; 62:1518-1527. [PMID: 34002374 PMCID: PMC8672363 DOI: 10.1111/epi.16922] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Indexed: 11/29/2022]
Abstract
Objective Paroxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations. Methods Confounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome‐wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses. Results Our analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations. Significance Our results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy.
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Affiliation(s)
- Remi Stevelink
- Department of Genetics, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,GGNet Mental Health, Apeldoorn, the Netherlands
| | - Bochao D Lin
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Costin Leu
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachussets, USA
| | - Dennis Lal
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachussets, USA
| | - Alexander W Smith
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachussets, USA
| | - Dick Schijven
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Johannes A Carpay
- Department of Neurology, Tergooi Hospital, Hilversum, the Netherlands
| | - Koen Rademaker
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Roiza A Rodrigues Baldez
- Clinical Research Laboratory on Neuroinfectious Diseases, Evandro Chagas Clinical Research Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Orrin Devinsky
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, New York, USA
| | - Kees P J Braun
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Floor E Jansen
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Dirk J A Smit
- Psychiatry Department, Amsterdam Neuroscience, Amsterdam Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Bobby P C Koeleman
- Department of Genetics, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
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17
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Abdellaoui A, Smit DJA, van den Brink W, Denys D, Verweij KJH. Genomic relationships across psychiatric disorders including substance use disorders. Drug Alcohol Depend 2021; 220:108535. [PMID: 33524898 DOI: 10.1016/j.drugalcdep.2021.108535] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 12/08/2020] [Accepted: 12/23/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND A recent study investigated the genetic associations and latent genetic structure among eight psychiatric disorders using findings from genome-wide association studies (GWASs). No data from substance use disorders were included, while these represent an important category of mental disorders and could influence the latent genetic structure. We extended the original paper by recreating the genetic relationship matrix, graph, and latent genetic factor structure, including additional data from substance use disorders. METHODS We used GWAS summary statistics of 11 psychiatric disorders, including alcohol dependence, nicotine dependence, and cannabis use disorder. We estimated genetic correlations between all traits in Linkage Disequilibrium-Score Regression. A graph was created to illustrate the network of genetic correlations. We then used the genetic relationships to model a latent genetic factor structure. RESULTS Alcohol and nicotine dependence showed significant genetic correlations with several other psychiatric disorders, including ADHD, schizophrenia, and major depression. Cannabis use disorder was only significantly associated with ADHD. The addition of substance use disorders resulted in some changes in the latent structure of the factor model when compared to the original model including eight disorders. All substance use disorders contributed mostly to Factor 3, a heterogeneous factor with also loadings from ADHD, major depression, Autism Spectrum Disorders, and Tourette Syndrome. CONCLUSIONS Alcohol and nicotine dependence show widespread genetic correlations with other psychiatric disorders. Including substance use disorders in the factor analysis results in some changes in the underlying genetic factor structure. Given the instability of such models, identified structures should be interpreted with caution.
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Affiliation(s)
- Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Wim van den Brink
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands.
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18
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Hederih J, Nuninga JO, van Eijk K, van Dellen E, Smit DJA, Oranje B, Luykx JJ. Genetic underpinnings of schizophrenia-related electroencephalographical intermediate phenotypes: A systematic review and meta-analysis. Prog Neuropsychopharmacol Biol Psychiatry 2021; 104:110001. [PMID: 32525059 DOI: 10.1016/j.pnpbp.2020.110001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 06/02/2020] [Accepted: 06/03/2020] [Indexed: 02/04/2023]
Abstract
Although substantial research into genetics of psychotic disorders has been conducted, a large proportion of their genetic architecture has remained unresolved. Electroencephalographical intermediate phenotypes (EIP) have the potential to constitute a valuable tool when studying genetic risk loci for schizophrenia, in particular P3b amplitude, P50 suppression, mismatch negativity (MMN) and resting state power spectra of the electroencephalogram (EEG). Here, we systematically reviewed studies investigating the association of single nucleotide polymorphisms (SNPs) with these EIPs and meta-analysed them when appropriate. We retrieved 45 studies (N = 34,971 study participants). Four SNPs investigated in more than one study were genome-wide significant for an association with schizophrenia and three were genome-wide suggestive, based on a lookup in the influential 2014 GWAS (Ripke et al., 2014). However, in our meta-analyses, rs1625579 failed to reach a statistically significant association with p3b amplitude decrease and rs4680 risk allele carrier status was not associated with p3b amplitude decrease or with impaired p50 suppression. In conclusion, evidence for SNP associations with EIPs remains limited to individual studies. Careful selection of EIPs and SNPs, combined with consistent reporting of effect sizes, directions of effect and p-values would aid future meta-analyses.
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Affiliation(s)
- Jure Hederih
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; Medical Sciences Division, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom.
| | - Jasper O Nuninga
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands
| | - Kristel van Eijk
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands
| | - Edwin van Dellen
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Dirk J A Smit
- Department of Psychiatry, Academic Medical Centre, Meibergdreef 5, Amsterdam 1105 AZ, the Netherlands
| | - Bob Oranje
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands
| | - Jurjen J Luykx
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, CX 3584, the Netherlands; GGNet Mental Health, Apeldoorn, the Netherlands
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19
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Pasman JA, Smit DJA, Kingma L, Vink JM, Treur JL, Verweij KJH. Corrigendum to "Causal relationships between substance use and insomnia" [Drug Alcohol Dependence 214 (2020) 108151]. Drug Alcohol Depend 2020; 216:108313. [PMID: 33017751 DOI: 10.1016/j.drugalcdep.2020.108313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Joëlle A Pasman
- Behavioural Science Institute, Radboud University Nijmegen, the Netherlands.
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Lilian Kingma
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University Nijmegen, the Netherlands
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
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20
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Smit DJA, Cath D, Zilhão NR, Ip HF, Denys D, den Braber A, de Geus EJC, Verweij KJH, Hottenga J, Boomsma DI. Genetic meta-analysis of obsessive-compulsive disorder and self-report compulsive symptoms. Am J Med Genet B Neuropsychiatr Genet 2020; 183:208-216. [PMID: 31891238 PMCID: PMC7317414 DOI: 10.1002/ajmg.b.32777] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 12/17/2019] [Accepted: 12/18/2019] [Indexed: 12/02/2022]
Abstract
We investigated whether obsessive-compulsive (OC) symptoms from a population-based sample could be analyzed to detect genetic variants influencing obsessive-compulsive disorder (OCD). We performed a genome-wide association studies (GWAS) on the obsession (rumination and impulsions) and compulsion (checking, washing, and ordering/precision) subscales of an abbreviated version of the Padua Inventory (N = 8,267 with genome-wide genotyping and phenotyping). The compulsion subscale showed a substantial and significant positive genetic correlation with an OCD case-control GWAS (r G = 0.61, p = .017) previously published by the Psychiatric Genomics Consortium (PGC-OCD). The obsession subscale and the total Padua score showed no significant genetic correlations (r G = -0.02 and r G = 0.42, respectively). A meta-analysis of the compulsive symptoms GWAS with the PGC-OCD revealed no genome-wide significant Single-Nucleotide Polymorphisms (SNPs combined N = 17,992, indicating that the power is still low for individual SNP effects). A gene-based association analysis, however, yielded two novel genes (WDR7 and ADCK1). The top 250 genes in the gene-based test also showed a significant increase in enrichment for psychiatric and brain-expressed genes. S-Predixcan testing showed that for genes expressed in hippocampus, amygdala, and caudate nucleus significance increased in the meta-analysis with compulsive symptoms compared to the original PGC-OCD GWAS. Thus, the inclusion of dimensional symptom data in genome-wide association on clinical case-control GWAS of OCD may be useful to find genes for OCD if the data are based on quantitative indices of compulsive behavior. SNP-level power increases were limited, but aggregate, gene-level analyses showed increased enrichment for brain-expressed genes related to psychiatric disorders, and increased association with gene expression in brain tissues with known emotional, reward processing, memory, and fear-formation functions.
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Affiliation(s)
- Dirk J. A. Smit
- Department of PsychiatryAmsterdam UMC Location AMCAmsterdamThe Netherlands
| | - Danielle Cath
- Department of PsychiatryUniversity Medical Center GroningenGroningenThe Netherlands,GGZ‐DrentheAssenThe Netherlands
| | - Nuno R. Zilhão
- Icelandic Heart AssociationReykjavikIceland,Netherlands Twin Register, Department of Biological PsychologyVrije UniversiteitAmsterdamThe Netherlands
| | - Hill F. Ip
- Netherlands Twin Register, Department of Biological PsychologyVrije UniversiteitAmsterdamThe Netherlands
| | - Damiaan Denys
- Department of PsychiatryAmsterdam UMC Location AMCAmsterdamThe Netherlands
| | - Anouk den Braber
- Netherlands Twin Register, Department of Biological PsychologyVrije UniversiteitAmsterdamThe Netherlands,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam NeuroscienceVrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
| | - Eco J. C. de Geus
- Netherlands Twin Register, Department of Biological PsychologyVrije UniversiteitAmsterdamThe Netherlands
| | | | - Jouke‐Jan Hottenga
- Netherlands Twin Register, Department of Biological PsychologyVrije UniversiteitAmsterdamThe Netherlands
| | - Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological PsychologyVrije UniversiteitAmsterdamThe Netherlands
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21
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Nieman DH, Chavez-Baldini U, Vulink NC, Smit DJA, van Wingen G, de Koning P, Sutterland AL, Mocking RJT, Bockting C, Verweij KJH, Lok A, Denys D. Protocol Across study: longitudinal transdiagnostic cognitive functioning, psychiatric symptoms, and biological parameters in patients with a psychiatric disorder. BMC Psychiatry 2020; 20:212. [PMID: 32393362 PMCID: PMC7216345 DOI: 10.1186/s12888-020-02624-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 04/26/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Patients with psychiatric disorders, such as major depressive disorder, schizophrenia or obsessive-compulsive disorder, often suffer from cognitive dysfunction. The nature of these dysfunctions and their relation with clinical symptoms and biological parameters is not yet clear. Traditionally, cognitive dysfunction is studied in patients with specific psychiatric disorders, disregarding the fact that cognitive deficits are shared across disorders. The Across study aims to investigate cognitive functioning and its relation with psychiatric symptoms and biological parameters transdiagnostically and longitudinally. METHODS The study recruits patients diagnosed with a variety of psychiatric disorders and has a longitudinal cohort design with an assessment at baseline and at one-year follow-up. The primary outcome measure is cognitive functioning. The secondary outcome measures include clinical symptoms, electroencephalographic, genetic and blood markers (e.g., fatty acids), and hair cortisol concentration levels. DISCUSSION The Across study provides an opportunity for a transdiagnostic, bottom-up, data-driven approach of investigating cognition in relation to symptoms and biological parameters longitudinally in patients with psychiatric disorders. The study may help to find new clusters of symptoms, biological markers, and cognitive dysfunctions that have better prognostic value than the current diagnostic categories. Furthermore, increased insight into the relationship among cognitive deficits, biological parameters, and psychiatric symptoms can lead to new treatment possibilities. TRIAL REGISTRATION Netherlands Trial Register (NTR): NL8170.
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Affiliation(s)
- Dorien H. Nieman
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - UnYoung Chavez-Baldini
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Nienke C. Vulink
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Dirk J. A. Smit
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Guido van Wingen
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Pelle de Koning
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Arjen L. Sutterland
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Roel J. T. Mocking
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Claudi Bockting
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Karin J. H. Verweij
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Anja Lok
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
| | - Damiaan Denys
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam University Medical Centers (location AMC), University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, Netherlands
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Prent N, Smit DJA. The dynamics of resting-state alpha oscillations predict individual differences in creativity. Neuropsychologia 2020; 142:107456. [PMID: 32283066 DOI: 10.1016/j.neuropsychologia.2020.107456] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 03/25/2020] [Accepted: 03/29/2020] [Indexed: 12/19/2022]
Abstract
The neuronal mechanisms underlying creativity are poorly understood. Arguably, the brain's ability to switch states would contribute to achieving novel ideas, and thus to creativity. Faster brain-state switching is reflected in the temporal dynamics of functional brain activity. Stronger autocorrelations in brain activity measures can make a brain stay in a certain state for longer periods, whereas low temporal autocorrelations reflect faster state switching. We established the brain's inherent tendency to switch or stay in a resting, no-task condition using 128 channel electroencephalography (EEG). We assessed temporal autocorrelations of the amplitude modulation of the dominant alpha oscillations (8-13 Hz). Creativity was measured by a self-rating, an examiner-rating and the alternative uses task in 40 healthy young adults, which was scored on dimensions of verbal fluency, originality, elaboration, usefulness, and flexibility. For each dimension, the total number of subject-reported alternative uses that matched the criterion was noted (the quantity measure), as well as the proportion of uses that matched the dimensional criterion. A principal components analysis confirmed the two-component structure of quantity and quality. Partial correlation analysis was used controlling for gender and age, and a cluster permutation test was performed to correct for multiple testing. A significant cluster over right central/temporal brain areas was found with a negative correlation between creativity and temporal autocorrelations were observed (p = 0.028). To our knowledge, this is the first demonstration that individual variation in the dynamically changing activity in the brain may offer a neuronal explanation for individual variation in creative ideation.
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Affiliation(s)
- Naomi Prent
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical Center Location AMC, Amsterdam Neuroscience, the Netherlands
| | - Dirk J A Smit
- Psychiatry Department, Amsterdam University Medical Center Location AMC, Amsterdam Neuroscience, the Netherlands.
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23
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Thompson PM, Jahanshad N, Ching CRK, Salminen LE, Thomopoulos SI, Bright J, Baune BT, Bertolín S, Bralten J, Bruin WB, Bülow R, Chen J, Chye Y, Dannlowski U, de Kovel CGF, Donohoe G, Eyler LT, Faraone SV, Favre P, Filippi CA, Frodl T, Garijo D, Gil Y, Grabe HJ, Grasby KL, Hajek T, Han LKM, Hatton SN, Hilbert K, Ho TC, Holleran L, Homuth G, Hosten N, Houenou J, Ivanov I, Jia T, Kelly S, Klein M, Kwon JS, Laansma MA, Leerssen J, Lueken U, Nunes A, Neill JO, Opel N, Piras F, Piras F, Postema MC, Pozzi E, Shatokhina N, Soriano-Mas C, Spalletta G, Sun D, Teumer A, Tilot AK, Tozzi L, van der Merwe C, Van Someren EJW, van Wingen GA, Völzke H, Walton E, Wang L, Winkler AM, Wittfeld K, Wright MJ, Yun JY, Zhang G, Zhang-James Y, Adhikari BM, Agartz I, Aghajani M, Aleman A, Althoff RR, Altmann A, Andreassen OA, Baron DA, Bartnik-Olson BL, Marie Bas-Hoogendam J, Baskin-Sommers AR, Bearden CE, Berner LA, Boedhoe PSW, Brouwer RM, Buitelaar JK, Caeyenberghs K, Cecil CAM, Cohen RA, Cole JH, Conrod PJ, De Brito SA, de Zwarte SMC, Dennis EL, Desrivieres S, Dima D, Ehrlich S, Esopenko C, Fairchild G, Fisher SE, Fouche JP, Francks C, Frangou S, Franke B, Garavan HP, Glahn DC, Groenewold NA, Gurholt TP, Gutman BA, Hahn T, Harding IH, Hernaus D, Hibar DP, Hillary FG, Hoogman M, Hulshoff Pol HE, Jalbrzikowski M, Karkashadze GA, Klapwijk ET, Knickmeyer RC, Kochunov P, Koerte IK, Kong XZ, Liew SL, Lin AP, Logue MW, Luders E, Macciardi F, Mackey S, Mayer AR, McDonald CR, McMahon AB, Medland SE, Modinos G, Morey RA, Mueller SC, Mukherjee P, Namazova-Baranova L, Nir TM, Olsen A, Paschou P, Pine DS, Pizzagalli F, Rentería ME, Rohrer JD, Sämann PG, Schmaal L, Schumann G, Shiroishi MS, Sisodiya SM, Smit DJA, Sønderby IE, Stein DJ, Stein JL, Tahmasian M, Tate DF, Turner JA, van den Heuvel OA, van der Wee NJA, van der Werf YD, van Erp TGM, van Haren NEM, van Rooij D, van Velzen LS, Veer IM, Veltman DJ, Villalon-Reina JE, Walter H, Whelan CD, Wilde EA, Zarei M, Zelman V. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries. Transl Psychiatry 2020; 10:100. [PMID: 32198361 PMCID: PMC7083923 DOI: 10.1038/s41398-020-0705-1] [Citation(s) in RCA: 280] [Impact Index Per Article: 70.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 12/11/2019] [Accepted: 12/20/2019] [Indexed: 02/07/2023] Open
Abstract
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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Affiliation(s)
- Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Joanna Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Sara Bertolín
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, Barcelona, Spain
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Willem B Bruin
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Jian Chen
- Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
| | - Yann Chye
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Carolien G F de Kovel
- Biometris Wageningen University and Research, Wageningen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Gary Donohoe
- The Center for Neuroimaging and Cognitive Genomics, School of Psychology, National University of Ireland, Galway, Ireland
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Desert-Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Pauline Favre
- INSERM Unit 955 Team 15 'Translational Psychiatry', Créteil, France
- NeuroSpin, UNIACT Lab, Psychiatry Team, CEA Saclay, Gif-Sur-Yvette, France
| | - Courtney A Filippi
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Daniel Garijo
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
| | - Yolanda Gil
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Katrina L Grasby
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- National Institute of Mental Health, Klecany, Czech Republic
| | - Laura K M Han
- Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, GGZ inGeest, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Sean N Hatton
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tiffany C Ho
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Psychiatry & Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Laurena Holleran
- The Center for Neuroimaging and Cognitive Genomics, School of Psychology, National University of Ireland, Galway, Ireland
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Norbert Hosten
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Josselin Houenou
- INSERM Unit 955 Team 15 'Translational Psychiatry', Créteil, France
- NeuroSpin, UNIACT Lab, Psychiatry Team, CEA Saclay, Gif-Sur-Yvette, France
- APHP, Mondor University Hospitals, School of Medicine, DMU Impact, Psychiatry Department, Créteil, France
| | - Iliyan Ivanov
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sinead Kelly
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
| | - Marieke Klein
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Max A Laansma
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jeanne Leerssen
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Abraham Nunes
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
| | - Joseph O' Neill
- Child & Adolescent Psychiatry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nils Opel
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federica Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Merel C Postema
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Elena Pozzi
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
| | - Natalia Shatokhina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, Barcelona, Spain
- CIBERSAM-G17, Madrid, Spain
- Department of Psychobiology and Methodology in Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Daqiang Sun
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Amanda K Tilot
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Leonardo Tozzi
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Celia van der Merwe
- Stanley Center for Psychiatric Research, The Broad Institute, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Eus J W Van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Psychiatry and Integrative Neurophysiology, VU University, Amsterdam UMC, Amsterdam, The Netherlands
| | - Guido A van Wingen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald, Germany
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
| | - Lei Wang
- Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Anderson M Winkler
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea
- Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Guohao Zhang
- Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, MD, USA
| | - Yanli Zhang-James
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Bhim M Adhikari
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Research & Innovation, GGZ InGeest, Amsterdam, The Netherlands
| | - André Aleman
- University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Robert R Althoff
- Psychiatry, Pediatrics, and Psychological Sciences, University of Vermont, Burlington, VT, USA
| | - Andre Altmann
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - David A Baron
- Provost and Senior Vice President, Western University of Health Sciences, Pomona, CA, USA
| | | | - Janna Marie Bas-Hoogendam
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | | | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Laura A Berner
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Premika S W Boedhoe
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Rachel M Brouwer
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC, Australia
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Ronald A Cohen
- Center for Cognitive Aging and Memory, University of Florida, Gainesville, FL, USA
- Clinical and Health Psychology, Gainesville, FL, USA
| | - James H Cole
- Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Patricia J Conrod
- Universite de Montreal, Centre de Recherche CHU Ste-Justine, Montreal, QC, Canada
| | - Stephane A De Brito
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Sonja M C de Zwarte
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Emily L Dennis
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvane Desrivieres
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Danai Dima
- Department of Psychology, School of Arts and Social Sciences, City, University of London, London, UK
- Department of Neuroimaging, Institute of Psychology, Psychiatry and Neurosciences, King's College London, London, UK
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Carrie Esopenko
- Department of Rehabilitation and Movement Sciences, School of Health Professions, Rutgers Biomedical Health Sciences, Newark, NJ, USA
| | | | - Simon E Fisher
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Jean-Paul Fouche
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- SU/UCT MRC Unit on Risk & Resilience in Mental Disorders, University of Stellenbosch, Stellenbosch, South Africa
| | - Clyde Francks
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- University of British Columbia, Vancouver, Canada
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hugh P Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, CT, USA
| | - Nynke A Groenewold
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Boris A Gutman
- Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
- Institute for Information Transmission Problems, Kharkevich Institute, Moscow, Russian Federation
| | - Tim Hahn
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Ian H Harding
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Dennis Hernaus
- Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Frank G Hillary
- Department of Psychology, Penn State University, University Park, PA, USA
- Social Life and Engineering Sciences Imaging Center, University Park, PA, USA
| | - Martine Hoogman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | | | - George A Karkashadze
- Research and Scientific Institute of Pediatrics and Child Health, CCH RAS, Ministry of Science and Higher Education, Moscow, Russian Federation
| | - Eduard T Klapwijk
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Rebecca C Knickmeyer
- Department of Pediatrics, Michigan State University, East Lansing, MI, USA
- Institute for Quantitative Health Science and Engineering, East Lansing, MI, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Inga K Koerte
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- CBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Xiang-Zhen Kong
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sook-Lei Liew
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Chan Division of Occupational Science and Occupational Therapy, Los Angeles, CA, USA
| | - Alexander P Lin
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mark W Logue
- National Center for PTSD at Boston VA Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
- Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA
| | - Eileen Luders
- School of Psychology, University of Auckland, Auckland, New Zealand
- Laboratory of Neuro Imaging, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | | | - Carrie R McDonald
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Psychiatry, San Diego, CA, USA
| | - Agnes B McMahon
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- The Kavli Foundation, Los Angeles, CA, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Gemma Modinos
- Department of Neuroimaging, Institute of Psychology, Psychiatry and Neurosciences, King's College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Rajendra A Morey
- Department of Psychiatry, Duke University School of Medicine, Durham, NC, USA
- Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Sven C Mueller
- Experimental Clinical & Health Psychology, Ghent University, Ghent, Belgium
- Department of Personality, Psychological Assessment and Treatment, University of Deusto, Bilbao, Spain
| | | | - Leyla Namazova-Baranova
- Research and Scientific Institute of Pediatrics and Child Health, CCH RAS, Ministry of Science and Higher Education, Moscow, Russian Federation
- Department of Pediatrics, Russian National Research Medical University MoH RF, Moscow, Russian Federation
| | - Talia M Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Daniel S Pine
- National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Fabrizio Pizzagalli
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | | | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry and Psychotherapy, Charite, Humboldt University, Berlin, Germany
| | - Mark S Shiroishi
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- Department of Radiology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, University College London, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Ida E Sønderby
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Dan J Stein
- Department of Psychiatry & Neuroscience Institute, SA MRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Jason L Stein
- Department of Genetics & UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, I. R., Iran
| | - David F Tate
- Department of Neurology, TBI and Concussion Center, Salt Lake City, UT, USA
- Missouri Institute of Mental Health, Berkeley, MO, USA
| | - Jessica A Turner
- Psychology Department & Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Odile A van den Heuvel
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Nic J A van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Ysbrand D van der Werf
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, USA
| | - Neeltje E M van Haren
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Daan van Rooij
- Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Laura S van Velzen
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Ilya M Veer
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Julio E Villalon-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Christopher D Whelan
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland
- Research and Early Development, Biogen Inc, Cambridge, MA, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- VA Salt Lake City Healthcare System, Salt Lake City, UT, USA
- Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, I. R., Iran
| | - Vladimir Zelman
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
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24
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Marees AT, Smit DJA, Ong JS, MacGregor S, An J, Denys D, Vorspan F, van den Brink W, Derks EM. Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health. Psychol Med 2020; 50:484-498. [PMID: 30874500 PMCID: PMC7083578 DOI: 10.1017/s0033291719000357] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 02/01/2019] [Accepted: 02/12/2019] [Indexed: 11/06/2022]
Abstract
BACKGROUND Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits. METHODS Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression. RESULTS We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity. CONCLUSIONS Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.
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Affiliation(s)
- Andries T. Marees
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
- Translational Neurogenomics Group, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Dirk J. A. Smit
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Jue-Sheng Ong
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jiyuan An
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Florence Vorspan
- Assistance Publique – Hôpitaux de Paris, Hôpital Fernand Widal, Département de Psychiatrie et de Médecine Addictologique, 200 rue du Faubourg Saint Denis, 75010Paris, France
- Inserm umr-s 1144, Université Paris Descartes, Université Paris Diderot, 4 avenue de l'Observatoire, 75006Paris, France
| | - Wim van den Brink
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Eske M. Derks
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
- Translational Neurogenomics Group, QIMR Berghofer Medical Research Institute, Brisbane, Australia
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25
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Abdellaoui A, Treur JL, Nivard MG, Smit DJA, Veul L, Vermeulen JM, Peyrot W, Penninx BWJH, Boomsma DI, van den Brink W, Denys D, Verweij KJH. [Genes and environment both important in psychological suffering]. Tijdschr Psychiatr 2020; 62:835-838. [PMID: 33184812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
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26
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Eijsker N, Schröder A, Smit DJA, van Wingen G, Denys D. Neural Basis of Response Bias on the Stop Signal Task in Misophonia. Front Psychiatry 2019; 10:765. [PMID: 31708818 PMCID: PMC6819955 DOI: 10.3389/fpsyt.2019.00765] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 09/23/2019] [Indexed: 12/25/2022] Open
Abstract
Objective: Misophonia is a newly described condition in which specific ordinary sounds provoke disproportionately strong negative affect. Since evidence for psychobiological dysfunction underlying misophonia is scarce, we tested whether misophonia patients, like many patients with impulse control or obsessive-compulsive spectrum disorders, show impaired ability to inhibit an ongoing motor response. Methods: We collected functional magnetic resonance imaging data during a stop signal task in 22 misophonia patients and 21 matched healthy controls. Results: Compared to controls, patients tended to show longer stop signal delays, which is the time between stimuli signaling response initiation and inhibition. Additionally, patients tended to activate left dorsolateral prefrontal cortex more during responding rather than successful inhibition, as was seen in controls. Furthermore, patients lacked inhibition success-related activity in posterior cingulate cortices and activated the superior medial frontal gyri less during inhibition success compared to failure, a feature correlated with stop signal delays over the sample. Conclusions: Misophonia patients did not show impaired response inhibition. However, they tended to show a response bias on the stop signal task, favoring accuracy over speed. This implies perfectionism and compulsive, rather than impulsive, behavior. Moreover, brain activations were in line with patients, compared to controls, engaging more cognitive control for slowing responses, while employing more attentional resources for successful inhibition.
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Affiliation(s)
- Nadine Eijsker
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Arjan Schröder
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Dirk J. A. Smit
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Guido van Wingen
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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27
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Fraga González G, Smit DJA, van der Molen MJW, Tijms J, de Geus EJC, van der Molen MW. Probability learning and feedback processing in dyslexia: A performance and heart rate analysis. Psychophysiology 2019; 56:e13460. [PMID: 31435961 DOI: 10.1111/psyp.13460] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 06/19/2019] [Accepted: 07/19/2019] [Indexed: 02/02/2023]
Abstract
Recent studies suggest that individuals with dyslexia may be impaired in probability learning and performance monitoring. These observations are consistent with findings indicating atypical neural activations in frontostriatal circuits in the brain, which are important for associative learning. The current study further examined probability learning and performance monitoring in adult individuals with dyslexia (n = 23) and typical readers (n = 31) using two varieties of a typical probabilistic learning task. In addition to performance measures, we measured heart rate, focusing on cardiac slowing with negative feedback as a manifestation of the automatic performance monitoring system. One task required participants to learn associations between artificial script and speech sounds and the other task required them to learn associations between geometric forms and bird sounds. Corrective feedback (informative or random) was provided in both tasks. Performance results indicated that individuals with dyslexia and typical readers learned the associations equally well in contrast to expectations. We found the typical cardiac response associated with feedback processing consisting of a heart rate slowing with the presentation of the feedback and a return to baseline thereafter. Interestingly, the heart rate slowing associated with feedback was less pronounced and the return to baseline was delayed in individuals with dyslexia relative to typical readers. These findings were interpreted in relation to current theorizing of performance monitoring linking the salience network in the brain to autonomic functioning.
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Affiliation(s)
- G Fraga González
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.,Rudolf Berlin Center, Amsterdam, The Netherlands.,Department of Child and Adolescent Psychiatry and Psychotherapy, University of Zurich, Zurich, Switzerland
| | - D J A Smit
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, The Netherlands
| | - M J W van der Molen
- Institute of Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - J Tijms
- Rudolf Berlin Center, Amsterdam, The Netherlands.,IWAL Institute, Amsterdam, The Netherlands
| | - E J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, The Netherlands
| | - M W van der Molen
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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28
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Vandenbosch MMLJZ, van 't Ent D, Boomsma DI, Anokhin AP, Smit DJA. EEG-based age-prediction models as stable and heritable indicators of brain maturational level in children and adolescents. Hum Brain Mapp 2019; 40:1919-1926. [PMID: 30609125 DOI: 10.1002/hbm.24501] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 12/06/2018] [Accepted: 12/09/2018] [Indexed: 12/31/2022] Open
Abstract
The human brain shows remarkable development of functional brain activity from childhood to adolescence. Here, we investigated whether electroencephalogram (EEG) recordings are suitable for predicting the age of children and adolescents. Moreover, we investigated whether overestimation or underestimation of age was stable over longer time periods, as stable prediction error can be interpreted as reflecting individual brain maturational level. Finally, we established whether the age-prediction error was genetically determined. Then, 3 min eyes-closed resting-state EEG data from the longitudinal EEG studies of Netherlands Twin Register (NTR; n = 836) and Washington University in St. Louis (n = 702) were used at ages 5, 7, 12, 14, 16, and 18. Longitudinal data were available within childhood (5-7 years) and adolescence (16-18 years). We calculated power in 1 Hz wide bins (1-24 Hz). Random forest (RF) regression and relevance vector machine with sixfold cross-validation were applied. The best mean absolute prediction error was obtained with RF (1.22 years). Classification of childhood versus puberty/adolescence reached over 94% accuracy. Prediction errors were moderately to highly stable over periods of 1.5-2.1 years (0.53 < r < 0.74) and signifcantly affected by genetic factors (heritability between 42 and 79%). Our results show that age prediction from low-cost EEG recordings is comparable in accuracy to those obtained with magnetic resonance imaging. Children and adolescents showed stable overestimation or underestimation of their age, which means that some participants have stable brain activity patterns that reflect those of an older or younger age, and could therefore reflect individual brain maturational level. This prediction error is heritable, suggesting that genes underlie maturational level of functional brain activity. We propose that age prediction based on EEG recordings can be used for tracking neurodevelopment in typically developing children, in preterm children, and in children with neurodevelopmental disorders.
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Affiliation(s)
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Andrey P Anokhin
- Washington University School of Medicine, Department of Psychiatry, St. Louis, Missouri
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam Universitair Medisch Centrum, Amsterdam Neuroscience, Amsterdam, The Netherlands
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29
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Fraga González G, Smit DJA, van der Molen MJW, Tijms J, Stam CJ, de Geus EJC, van der Molen MW. EEG Resting State Functional Connectivity in Adult Dyslexics Using Phase Lag Index and Graph Analysis. Front Hum Neurosci 2018; 12:341. [PMID: 30214403 PMCID: PMC6125304 DOI: 10.3389/fnhum.2018.00341] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Accepted: 08/10/2018] [Indexed: 11/13/2022] Open
Abstract
Developmental dyslexia may involve deficits in functional connectivity across widespread brain networks that enable fluent reading. We investigated the large-scale organization of electroencephalography (EEG) functional networks at rest in 28 dyslexics and 36 typically reading adults. For each frequency band (delta, theta alpha and beta), we assessed functional connectivity strength with the phase lag index (PLI). Network topology was examined using minimum spanning tree (MST) graphs derived from the functional connectivity matrices. We found significant group differences in the alpha band (8-13 Hz). The graph analysis indicated more interconnected nodes, in dyslexics compared to typical readers. The graph metrics were significantly correlated with age in dyslexics but not in typical readers, which may indicate more heterogeneity in maturation of brain networks in dyslexics. The present findings support the involvement of alpha oscillations in higher cognition and the sensitivity of graph metrics to characterize functional networks in adult dyslexia. Finally, the current results extend our previous findings on children.
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Affiliation(s)
- Gorka Fraga González
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Rudolf Berlin Center, Amsterdam, Netherlands
| | - Dirk J A Smit
- Department of Biological Psychology, VU University, Amsterdam, Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, Netherlands
| | - Melle J W van der Molen
- Institute of Psychology, Leiden University, Leiden, Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
| | - Jurgen Tijms
- Rudolf Berlin Center, Amsterdam, Netherlands.,IWAL Institute, Amsterdam, Netherlands
| | - Cornelis Jan Stam
- Department of Clinical Neuropsychology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, Netherlands.,Neuroscience Campus Amsterdam, VU University, Amsterdam, Netherlands
| | - Maurits W van der Molen
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.,Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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30
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Smit DJA, Wright MJ, Meyers JL, Martin NG, Ho YYW, Malone SM, Zhang J, Burwell SJ, Chorlian DB, de Geus EJC, Denys D, Hansell NK, Hottenga JJ, McGue M, van Beijsterveldt CEM, Jahanshad N, Thompson PM, Whelan CD, Medland SE, Porjesz B, Lacono WG, Boomsma DI. Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity. Hum Brain Mapp 2018; 39:4183-4195. [PMID: 29947131 PMCID: PMC6179948 DOI: 10.1002/hbm.24238] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 04/26/2018] [Accepted: 05/21/2018] [Indexed: 02/02/2023] Open
Abstract
Oscillatory activity is crucial for information processing in the brain, and has a long history as a biomarker for psychopathology. Variation in oscillatory activity is highly heritable, but current understanding of specific genetic influences remains limited. We performed the largest genome‐wide association study to date of oscillatory power during eyes‐closed resting electroencephalogram (EEG) across a range of frequencies (delta 1–3.75 Hz, theta 4–7.75 Hz, alpha 8–12.75 Hz, and beta 13–30 Hz) in 8,425 subjects. Additionally, we performed KGG positional gene‐based analysis and brain‐expression analyses. GABRA2—a known genetic marker for alcohol use disorder and epilepsy—significantly affected beta power, consistent with the known relation between GABAA interneuron activity and beta oscillations. Tissue‐specific SNP‐based imputation of gene‐expression levels based on the GTEx database revealed that hippocampal GABRA2 expression may mediate this effect. Twenty‐four genes at 3p21.1 were significant for alpha power (FDR q < .05). SNPs in this region were linked to expression of GLYCTK in hippocampal tissue, and GNL3 and ITIH4 in the frontal cortex–genes that were previously implicated in schizophrenia and bipolar disorder. In sum, we identified several novel genetic variants associated with oscillatory brain activity; furthermore, we replicated and advanced understanding of previously known genes associated with psychopathology (i.e., schizophrenia and alcohol use disorders). Importantly, these psychopathological liability genes affect brain functioning, linking the genes' expression to specific cortical/subcortical brain regions.
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Affiliation(s)
- Dirk J A Smit
- Psychiatry department, Amsterdam Neuroscience, Academic Medical Center, University of Amsterdam, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, Australia.,Centre of Advanced Imaging, University Queensland, Brisbane, Australia
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Lab., Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, New York
| | | | - Yvonne Y W Ho
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota
| | - Jian Zhang
- Henri Begleiter Neurodynamics Lab., Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, New York
| | - Scott J Burwell
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota
| | - David B Chorlian
- Henri Begleiter Neurodynamics Lab., Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, New York
| | - Eco J C de Geus
- Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, The Netherlands
| | - Damiaan Denys
- Psychiatry department, Amsterdam Neuroscience, Academic Medical Center, University of Amsterdam, The Netherlands
| | - Narelle K Hansell
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - Jouke-Jan Hottenga
- Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, The Netherlands
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota
| | | | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Marina del Rey, California
| | - Paul M Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Marina del Rey, California
| | - Christopher D Whelan
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Marina del Rey, California
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab., Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, New York
| | - William G Lacono
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota
| | - Dorret I Boomsma
- Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, The Netherlands
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31
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Bangel KA, van Buschbach S, Smit DJA, Mazaheri A, Olff M. Aberrant brain response after auditory deviance in PTSD compared to trauma controls: An EEG study. Sci Rep 2017; 7:16596. [PMID: 29185490 PMCID: PMC5707412 DOI: 10.1038/s41598-017-16669-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Accepted: 11/16/2017] [Indexed: 12/19/2022] Open
Abstract
Part of the symptomatology of post-traumatic stress disorder (PTSD) are alterations in arousal and reactivity which could be related to a maladaptive increase in the automated sensory change detection system of the brain. In the current EEG study we investigated whether the brain's response to a simple auditory sensory change was altered in patients with PTSD relative to trauma-exposed matched controls who did not develop the disorder. Thirteen male PTSD patients and trauma-exposed controls matched for age and educational level were presented with regular auditory pure tones (1000 Hz, 200 ms duration), with 11% of the tones deviating in both duration (50 ms) and frequency (1200 Hz) while watching a silent movie. Relative to the controls, patients who had developed PTSD showed enhanced mismatch negativity (MMN), increased theta power (5-7 Hz), and stronger suppression of upper alpha activity (13-15 Hz) after deviant vs. standard tones. Behaviourally, the alpha suppression in PTSD correlated with decreased spatial working memory performance suggesting it might reflect enhanced stimulus-feature representations in auditory memory. These results taken together suggest that PTSD patients and trauma-exposed controls can be distinguished by enhanced involuntary attention to changes in sensory patterns.
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Affiliation(s)
- Katrin A Bangel
- Department of Psychiatry, Academic Medical Centre, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands.
| | - Susanne van Buschbach
- Department of Psychiatry, Academic Medical Centre, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands
| | - Dirk J A Smit
- Department of Psychiatry, Academic Medical Centre, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands
| | - Ali Mazaheri
- Center for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, United Kingdom.
| | - Miranda Olff
- Department of Psychiatry, Academic Medical Centre, Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands
- Arq Psychotrauma Expert Group, 1112 XE Diemen, The Netherlands
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Demuru M, Gouw AA, Hillebrand A, Stam CJ, van Dijk BW, Scheltens P, Tijms BM, Konijnenberg E, Ten Kate M, den Braber A, Smit DJA, Boomsma DI, Visser PJ. Functional and effective whole brain connectivity using magnetoencephalography to identify monozygotic twin pairs. Sci Rep 2017; 7:9685. [PMID: 28852152 PMCID: PMC5575140 DOI: 10.1038/s41598-017-10235-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 08/01/2017] [Indexed: 01/08/2023] Open
Abstract
Resting-state functional connectivity patterns are highly stable over time within subjects. This suggests that such 'functional fingerprints' may have strong genetic component. We investigated whether the functional (FC) or effective (EC) connectivity patterns of one monozygotic twin could be used to identify the co-twin among a larger sample and determined the overlap in functional fingerprints within monozygotic (MZ) twin pairs using resting state magnetoencephalography (MEG). We included 32 cognitively normal MZ twin pairs from the Netherlands Twin Register who participate in the EMIF-AD preclinAD study (average age 68 years). Combining EC information across multiple frequency bands we obtained an identification rate over 75%. Since MZ twin pairs are genetically identical these results suggest a high genetic contribution to MEG-based EC patterns, leading to large similarities in brain connectivity patterns between two individuals even after 60 years of life or more.
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Affiliation(s)
- M Demuru
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - A A Gouw
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - A Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - C J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - B W van Dijk
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - P Scheltens
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - B M Tijms
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - E Konijnenberg
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - M Ten Kate
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - A den Braber
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - D J A Smit
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Department of Psychiatry, Academic Medical Center, Amsterdam, The Netherlands
| | - D I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - P J Visser
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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Abstract
BACKGROUND Genetic-epidemiological studies that estimate the contributions of genetic factors to variation in tic symptoms are scarce. We estimated the extent to which genetic and environmental influences contribute to tics, employing various phenotypic definitions ranging between mild and severe symptomatology, in a large population-based adult twin-family sample. METHOD In an extended twin-family design, we analysed lifetime tic data reported by adult mono- and dizygotic twins (n = 8323) and their family members (n = 7164; parents and siblings) from 7311 families in the Netherlands Twin Register. We measured tics by the abbreviated version of the Schedule for Tourette and Other Behavioral Syndromes. Heritability was estimated by genetic structural equation modeling for four tic disorder definitions: three dichotomous and one trichotomous phenotype, characterized by increasingly strictly defined criteria. RESULTS Prevalence rates of the different tic disorders in our sample varied between 0.3 and 4.5% depending on tic disorder definition. Tic frequencies decreased with increasing age. Heritability estimates varied between 0.25 and 0.37, depending on phenotypic definitions. None of the phenotypes showed evidence of assortative mating, effects of shared environment or non-additive genetic effects. CONCLUSIONS Heritabilities of mild and severe tic phenotypes were estimated to be moderate. Overlapping confidence intervals of the heritability estimates suggest overlapping genetic liabilities between the various tic phenotypes. The most lenient phenotype (defined only by tic characteristics, excluding criteria B, C and D of DSM-IV) rendered sufficiently reliable heritability estimates. These findings have implications in phenotypic definitions for future genetic studies.
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Affiliation(s)
- N R Zilhão
- Department of Biological Psychology,Vrije Universiteit,Amsterdam,The Netherlands
| | - M C Olthof
- Department of Psychology,University of Amsterdam,The Netherlands
| | - D J A Smit
- Department of Biological Psychology,Vrije Universiteit,Amsterdam,The Netherlands
| | - D C Cath
- Department of Clinical Psychology,Utrecht University,The Netherlands
| | - L Ligthart
- Department of Biological Psychology,Vrije Universiteit,Amsterdam,The Netherlands
| | - C A Mathews
- Department of Psychiatry,University of Florida,Gainesville, FL,USA
| | - K Delucchi
- Department of Psychiatry,University of California,San Francisco, CA,USA
| | - D I Boomsma
- Department of Biological Psychology,Vrije Universiteit,Amsterdam,The Netherlands
| | - C V Dolan
- Department of Biological Psychology,Vrije Universiteit,Amsterdam,The Netherlands
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den Braber A, Zilhão NR, Fedko IO, Hottenga JJ, Pool R, Smit DJA, Cath DC, Boomsma DI. Obsessive-compulsive symptoms in a large population-based twin-family sample are predicted by clinically based polygenic scores and by genome-wide SNPs. Transl Psychiatry 2016; 6:e731. [PMID: 26859814 PMCID: PMC4872426 DOI: 10.1038/tp.2015.223] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 11/26/2015] [Accepted: 12/05/2015] [Indexed: 11/09/2022] Open
Abstract
Variation in obsessive-compulsive symptoms (OCS) has a heritable basis, with genetic association studies starting to yield the first suggestive findings. We contribute to insights into the genetic basis of OCS by performing an extensive series of genetic analyses in a homogeneous, population-based sample from the Netherlands. First, phenotypic and genetic longitudinal correlations over a 6-year period were estimated by modeling OCS data from twins and siblings. Second, polygenic risk scores (PRS) for 6931 subjects with genotype and OCS data were calculated based on meta-analysis results from IOCDF-GC, to investigate their predictive value. Third, the contribution of measured single nucleotide polymorphisms (SNPs) to the heritability was estimated using random-effects modeling. Last, we performed an exploratory genome-wide association study (GWAS) of OCS, testing for SNP- and for gene-based associations. Stability in OCS (test-retest correlation 0.63) was mainly explained by genetic stability. The PRS based on clinical samples predicted OCS in our population-based twin-family sample. SNP-based heritability was estimated at 14%. GWAS revealed one SNP (rs8100480), located within the MEF2BNB gene, associated with OCS (P=2.56 × 10(-8)). Additional gene-based testing resulted in four significantly associated genes, which are located in the same chromosomal region on chromosome 19p13.11: MEF2BNB, RFXANK, MEF2BNB-MEF2B and MEF2B. Thus, common genetic variants explained a significant proportion of OCS trait variation. Genes significantly associated with OCS are expressed in the brain and involved in development and control of immune system functions (RFXANK) and regulation of gene expression of muscle-specific genes (MEF2BNB). MEF2BNB also showed a suggestive association with OCD in an independent case-control study, suggesting a role for this gene in the development of OCS.
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Affiliation(s)
- A den Braber
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands,Alzheimer Center & Department of Neurology, VU University Medical Center and Neuroscience Campus, Amsterdam, The Netherlands,Department of Biological Psychology, VU University Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands. E-mail:
| | - N R Zilhão
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands,Department of Clinical and Health Psychology, Utrecht University, Utrecht, The Netherlands
| | - I O Fedko
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - J-J Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - R Pool
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - D J A Smit
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - D C Cath
- Department of Clinical and Health Psychology, Utrecht University, Utrecht, The Netherlands,Altrecht Academic Anxiety Disorders Center, Utrecht, The Netherlands
| | - D I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
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35
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Brouwer RM, Hedman AM, van Haren NEM, Schnack HG, Brans RGH, Smit DJA, Kahn RS, Boomsma DI, Hulshoff Pol HE. Heritability of brain volume change and its relation to intelligence. Neuroimage 2014; 100:676-83. [PMID: 24816534 DOI: 10.1016/j.neuroimage.2014.04.072] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2014] [Revised: 04/09/2014] [Accepted: 04/28/2014] [Indexed: 11/19/2022] Open
Abstract
Human brain volumes change throughout life, are highly heritable, and have been associated with general cognitive functioning. Cross-sectionally, this association between volume and cognition can largely be attributed to the same genes influencing both traits. We address the question whether longitudinal changes in brain volume or in surface area in young adults are under genetic control and whether these changes are also related to general cognitive functioning. We measured change in brain volume and surface area over a 5-year interval in 176 monozygotic and dizygotic twins and their non-twin siblings aged 19 to 56, using magnetic resonance imaging. Results show that changes in volumes of total brain (mean = -6.4 ml; 0.5% loss), cerebellum (1.4 ml, 1.0% increase), cerebral white matter (4.4 ml, 0.9% increase), lateral ventricles (0.6 ml; 4.8% increase) and in surface area (-19.7 cm(2),1.1% contraction) are heritable (h(2) = 43%; 52%; 29%; 31%; and 33%, respectively). An association between IQ (available for 91 participants) and brain volume change was observed, which was attributed to genes involved in both the variation in change in brain volume and in intelligence. Thus, dynamic changes in brain structure are heritable and may have cognitive significance in adulthood.
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Affiliation(s)
- Rachel M Brouwer
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Anna M Hedman
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Neeltje E M van Haren
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hugo G Schnack
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rachel G H Brans
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dirk J A Smit
- Department of Biological Psychology, Free University, Amsterdam, The Netherlands; Neuroscience Campus, VU University, Amsterdam, The Netherlands
| | - Rene S Kahn
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Free University, Amsterdam, The Netherlands
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
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36
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Vink JM, Bartels M, van Beijsterveldt TCEM, van Dongen J, van Beek JHDA, Distel MA, de Moor MHM, Smit DJA, Minica CC, Ligthart L, Geels LM, Abdellaoui A, Middeldorp CM, Hottenga JJ, Willemsen G, de Geus EJC, Boomsma DI. Sex differences in genetic architecture of complex phenotypes? PLoS One 2012; 7:e47371. [PMID: 23272036 PMCID: PMC3525575 DOI: 10.1371/journal.pone.0047371] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2012] [Accepted: 09/11/2012] [Indexed: 12/02/2022] Open
Abstract
We examined sex differences in familial resemblance for a broad range of behavioral, psychiatric and health related phenotypes (122 complex traits) in children and adults. There is a renewed interest in the importance of genotype by sex interaction in, for example, genome-wide association (GWA) studies of complex phenotypes. If different genes play a role across sex, GWA studies should consider the effect of genetic variants separately in men and women, which affects statistical power. Twin and family studies offer an opportunity to compare resemblance between opposite-sex family members to the resemblance between same-sex relatives, thereby presenting a test of quantitative and qualitative sex differences in the genetic architecture of complex traits. We analyzed data on lifestyle, personality, psychiatric disorder, health, growth, development and metabolic traits in dizygotic (DZ) same-sex and opposite-sex twins, as these siblings are perfectly matched for age and prenatal exposures. Sample size varied from slightly over 300 subjects for measures of brain function such as EEG power to over 30,000 subjects for childhood psychopathology and birth weight. For most phenotypes, sample sizes were large, with an average sample size of 9027 individuals. By testing whether the resemblance in DZ opposite-sex pairs is the same as in DZ same-sex pairs, we obtain evidence for genetic qualitative sex-differences in the genetic architecture of complex traits for 4% of phenotypes. We conclude that for most traits that were examined, the current evidence is that same the genes are operating in men and women.
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Affiliation(s)
- Jacqueline M Vink
- Netherlands Twin Register, Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.
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Smit DJA, Boersma M, Schnack HG, Micheloyannis S, Boomsma DI, Hulshoff Pol HE, Stam CJ, de Geus EJC. The brain matures with stronger functional connectivity and decreased randomness of its network. PLoS One 2012; 7:e36896. [PMID: 22615837 PMCID: PMC3352942 DOI: 10.1371/journal.pone.0036896] [Citation(s) in RCA: 92] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2011] [Accepted: 04/09/2012] [Indexed: 11/19/2022] Open
Abstract
We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years) by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998) graph parameters C (local clustering) and L (global path length) for alpha (~10 Hz), beta (~20 Hz), and theta (~4 Hz) oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ~50 yrs). Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ~18 yrs). Older age (55+) was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05), while path length was related to both white matter (alpha: max. r = 38, p<001) and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001) volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain.
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Affiliation(s)
- Dirk J A Smit
- Biological Psychology, VU University, Amsterdam, The Netherlands.
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38
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Boersma M, Smit DJA, de Bie HMA, Van Baal GCM, Boomsma DI, de Geus EJC, Delemarre-van de Waal HA, Stam CJ. Network analysis of resting state EEG in the developing young brain: structure comes with maturation. Hum Brain Mapp 2011; 32:413-25. [PMID: 20589941 DOI: 10.1002/hbm.21030] [Citation(s) in RCA: 153] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
During childhood, brain structure and function changes substantially. Recently, graph theory has been introduced to model connectivity in the brain. Small-world networks, such as the brain, combine optimal properties of both ordered and random networks, i.e., high clustering and short path lengths. We used graph theoretical concepts to examine changes in functional brain networks during normal development in young children. Resting-state eyes-closed electroencephalography (EEG) was recorded (14 channels) from 227 children twice at 5 and 7 years of age. Synchronization likelihood (SL) was calculated in three different frequency bands and between each pair of electrodes to obtain SL-weighted graphs. Mean normalized clustering index, average path length and weight dispersion were calculated to characterize network organization. Repeated measures analysis of variance tested for time and gender effects. For all frequency bands mean SL decreased from 5 to 7 years. Clustering coefficient increased in the alpha band. Path length increased in all frequency bands. Mean normalized weight dispersion decreased in beta band. Girls showed higher synchronization for all frequency bands and a higher mean clustering in alpha and beta bands. The overall decrease in functional connectivity (SL) might reflect pruning of unused synapses and preservation of strong connections resulting in more cost-effective networks. Accordingly, we found increases in average clustering and path length and decreased weight dispersion indicating that normal brain maturation is characterized by a shift from random to more organized small-world functional networks. This developmental process is influenced by gender differences early in development.
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Affiliation(s)
- Maria Boersma
- Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, The Netherlands.
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39
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Smit DJA, Luciano M, Bartels M, van Beijsterveldt CEM, Wright MJ, Hansell NK, Brunner HG, Estourgie-van Burk GF, de Geus EJC, Martin NG, Boomsma DI. Heritability of head size in Dutch and Australian twin families at ages 0-50 years. Twin Res Hum Genet 2011; 13:370-80. [PMID: 20707707 DOI: 10.1375/twin.13.4.370] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
We assessed the heritability of head circumference, an approximation of brain size, in twin-sib families of different ages. Data from the youngest participants were collected a few weeks after birth and from the oldest participants around age 50 years. In nearly all age groups the largest part of the variation in head circumference was explained by genetic differences. Heritability estimates were 90% in young infants (4 to 5 months), 85-88% in early childhood, 83-87% in adolescence, 75% in young and mid adulthood. In infants younger than 3 months, heritability was very low or absent. Quantitative sex differences in heritability were observed in 15- and 18-year-olds, but there was no evidence for qualitative sex differences, that is, the same genes were expressed in both males and females. Longitudinal analysis of the data between 5, 7, and 18 years of age showed high genetic stability (.78 > R(G) > .98). These results indicate that head circumference is a highly heritable biometric trait and a valid target for future GWA studies.
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Affiliation(s)
- Dirk J A Smit
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands.
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40
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Sharma A, Sauer H, Smit DJA, Bender S, Weisbrod M. Genetic liability to schizophrenia measured by p300 in concordant and discordant monozygotic twins. Psychopathology 2011; 44:398-406. [PMID: 21968749 DOI: 10.1159/000325883] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2010] [Accepted: 02/01/2011] [Indexed: 11/19/2022]
Abstract
BACKGROUND Differential effects of genes and environment can contribute to etiological heterogeneity in schizophrenia. Twins concordant and discordant for schizophrenia may differ in genetic predisposition to schizophrenia with concordant twins having a higher genetic liability and discordant twins having a lower genetic liability to schizophrenia. We aimed to investigate whether P300 amplitude (which has been postulated as a genetic marker for schizophrenia) reflected this heterogeneity. SAMPLING AND METHODS We compared P300 amplitudes across 36 monozygotic twin pairs (6 concordant for schizophrenia/schizoaffective disorder, 11 discordant and 19 healthy control pairs) performing an auditory oddball task, using multiple regression (age, gender, birth order, premorbid IQ as covariates). We further looked at the correlation between the Brief Psychiatric Rating Scale (BPRS) and P300 amplitude in affected twins, and compared concordant and discordant affected twins on the Global Assessment Scale (GAS). RESULTS Multiple regression yielded a highly significant model (p = 0.004) though the explained variance was limited (21%). The main effect of the group on P300 amplitude was significant (p = 0.0001): affected concordant twins showed a significantly lower P300 amplitude as compared to affected discordant (p = 0.005, Cohen's d = 1.08) and control twins (p = 0.000, d = 1.16). Discordant affected and unaffected twins did not differ significantly from each other or from control twins. P300 did not correlate significantly with the BPRS and the affected groups did not differ across the GAS. CONCLUSIONS Our results provide evidence for etiological heterogeneity within schizophrenia pointing to different pathophysiological mechanisms that may underlie more and less genetically determined forms of schizophrenia. They also indicate that P300 correlates with a differing degree of genetic liability to schizophrenia independently of the psychopathological status and even in the presence of similar functional profiles.
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Affiliation(s)
- Anuradha Sharma
- Department of General Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Germany. Anuradha.Sharma @ med.uni-heidelberg.de
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Smit DJA, Boersma M, van Beijsterveldt CEM, Posthuma D, Boomsma DI, Stam CJ, de Geus EJC. Endophenotypes in a dynamically connected brain. Behav Genet 2010; 40:167-77. [PMID: 20111993 PMCID: PMC2829652 DOI: 10.1007/s10519-009-9330-8] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2009] [Accepted: 12/29/2009] [Indexed: 02/08/2023]
Abstract
We examined the longitudinal genetic architecture of three parameters of functional brain connectivity. One parameter described overall connectivity (synchronization likelihood, SL). The two others were derived from graph theory and described local (clustering coefficient, CC) and global (average path length, L) aspects of connectivity. We measured resting state EEG in 1,438 subjects from four age groups of about 16, 18, 25 and 50 years. Developmental curves for SL and L indicate that connectivity is more random at adolescence and old age, and more structured in middle-aged adulthood. Individual variation in SL and L were moderately to highly heritable at each age (SL: 40–82%; L: 29–63%). Genetic factors underlying these phenotypes overlapped. CC was also heritable (25–49%) but showed no systematic overlap with SL and L. SL, CC, and L in the alpha band showed high phenotypic and genetic stability from 16 to 25 years. Heritability for parameters in the beta band was lower, and less stable across ages, but genetic stability was high. We conclude that the connectivity parameters SL, CC, and L in the alpha band show the hallmarks of a good endophenotype for behavior and developmental disorders.
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Affiliation(s)
- D J A Smit
- Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.
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Smit DJA, Stam CJ, Posthuma D, Boomsma DI, de Geus EJC. Heritability of "small-world" networks in the brain: a graph theoretical analysis of resting-state EEG functional connectivity. Hum Brain Mapp 2009; 29:1368-78. [PMID: 18064590 DOI: 10.1002/hbm.20468] [Citation(s) in RCA: 167] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Recent studies have shown that resting-state functional networks as studied with fMRI, EEG, and MEG may be so-called small-world networks. We investigated to what extent the characteristic features of small-world networks are genetically determined. To represent functional connectivity between brain areas, we measured resting EEG in 574 twins and their siblings and calculated the synchronization likelihood between each pair of electrodes. We applied a threshold to obtain a binary graph from which we calculated the clustering coefficient C (describing local interconnectedness) and average path length L (describing global interconnectedness) for each individual. Modeling of MZ and DZ twin and sibling resemblance indicated that across various frequency bands 46-89% of the individual differences in C and 37-62% of the individual differences in L are heritable. It is asserted that C, L, and a small-world organization are viable markers of genetic differences in brain organization.
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Affiliation(s)
- Dirk J A Smit
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.
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Smit DJA, Posthuma D, Boomsma DI, De Geus EJC. Phenotypic and genetic correlations between evoked EEG/ERP measures during the response anticipation period of a delayed response task. Psychophysiology 2009; 46:344-56. [PMID: 19170951 DOI: 10.1111/j.1469-8986.2008.00777.x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
We investigated the relationship between three electrophysiological indices of response anticipation in a spatial delayed response task with a low and high memory load manipulation: a slow cortical potential (SCP), theta desynchronization, and upper alpha synchronization. Individual differences in these three measures were examined in 531 adult twins and siblings. Heritability of the SCP at occipital-parietal leads varied from 30% to 43%. Heritability of upper alpha synchronization (35% to 65%) and theta desynchronization (31% to 50%) was significant at all leads. Theta desynchronization and upper alpha synchronization were significantly correlated (r approximately 43%), but SCP was not correlated with either. The effect of working memory load on all three measures was not heritable. Response anticipation reliably evokes an SCP, upper alpha synchronization and theta desynchronization, but variation in these measures reflects different (genetic) sources.
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Affiliation(s)
- Dirk J A Smit
- Biological Psychology, Cognitive Research, VU University Amsterdam, 1081 BT Amsterdam, The Netherlands.
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Abstract
Previous studies in young and adolescent twins suggested substantial genetic contributions to the amplitude and latency of the P3 evoked by targets in an oddball paradigm. Here we examined whether these findings can be generalized to adult samples. A total of 651 twins and siblings from 292 families participated in a visual oddball task. In half of the subjects the age centered around 26 (young adult cohort), in the other half the age centered around 49 (middle-aged adult cohort). P3 peak amplitude and latency were scored for 3 midline leads Pz, Cz, and Fz. No cohort differences in heritability were found. P3 amplitude (approximately 50%) and latency (approximately 45%) were moderately heritable for the 3 leads. A single genetic factor influenced latency at all electrodes, suggesting a single P3 timing mechanism. Specific genetic factors influenced amplitude at each lead, suggesting local modulation of the P3 once triggered. Genetic analysis of the full event-related potential waveform showed that P3 heritability barely changes from about 100 ms before to 100 ms after the peak. Age differences are restricted to differences in means and variances, but the proportion of genetic variance as part of the total variance of midline P3 amplitude and latency does not change from young to middle-aged adulthood.
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Affiliation(s)
- Dirk J A Smit
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands.
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Smit DJA, Posthuma D, Boomsma DI, De Geus EJC. Heritability of anterior and posterior visual N1. Int J Psychophysiol 2007; 66:196-204. [PMID: 17669532 DOI: 10.1016/j.ijpsycho.2007.06.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2006] [Revised: 06/19/2007] [Accepted: 06/28/2007] [Indexed: 11/24/2022]
Abstract
Previous studies have reported that individual variation in N1 amplitude is related to attentional problems and alcoholism. Using data from 651 twins and siblings from 292 families we examined whether variation in N1 amplitude and latency can be explained by genetic factors. In half of the subjects the age centered around 26 (young adult cohort), in the other half the age centered around 49 (middle-aged adult cohort). Two visual N1 components were identified by a spatial PCA -- an early anterior component peaking from 88 to 168 ms after stimulus presentation and a posterior one peaking from 132 to 220 ms. Significant heritability was found for anterior N1 amplitude (22%) and posterior amplitude (50%), and for anterior latency (45%) and posterior latency (43%). We conclude that visual N1 amplitude and latency may serve as endophenotypes to detect genetic variation in susceptibility to psychiatric disorders.
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Affiliation(s)
- D J A Smit
- Department of Biological Psychology, Vrije Universiteit Amsterdam, The Netherlands.
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Smit DJA, Posthuma D, Boomsma DI, De Geus EJC. The relation between frontal EEG asymmetry and the risk for anxiety and depression. Biol Psychol 2007; 74:26-33. [PMID: 16875773 DOI: 10.1016/j.biopsycho.2006.06.002] [Citation(s) in RCA: 67] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2005] [Revised: 06/06/2006] [Accepted: 06/16/2006] [Indexed: 10/24/2022]
Abstract
Frontal asymmetry of EEG alpha power (FA) may index the risk for anxiety and depression. Evidence linking FA to the underlying biological mechanisms is scarce. This is unfortunate because FA has potential as a biological marker to support gene finding in anxiety and depression. We examined the heritability of FA in 732 twins and their singleton siblings, and established the genetic and environmental contribution to the relation between FA and the risk for anxiety and depression. Multivariate models showed that FA is heritable only in young adults (males 32% and females 37%) but not in middle-aged adults. A significant relation between FA and the risk for anxiety and depression was only found in young adult females. This relation was explained by shared genes influencing both EEG and disease risk. Future studies on asymmetry of left and right frontal brain activation should carefully consider the effects of sex and age.
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Affiliation(s)
- D J A Smit
- Department of Biological Psychology, Vrije Universiteit of Amsterdam, van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands.
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Abstract
We estimated the genetic and nongenetic (environmental) contributions to individual differences in the background EEG power spectrum in two age cohorts with mean ages of 26.2 and 49.4 years. Nineteen-lead EEG was recorded with eyes closed from 142 monozygotic and 167 dizygotic twin pairs and their siblings, totaling 760 subjects. We obtained power spectra in 24 bins of 1 Hz ranging from 1.0 to 25.0 Hz. Generally, heritability was highest around the alpha peak frequency and lower in the theta and delta bands. In the beta band heritability gradually decreased with increasing frequency, especially in the temporal regions. Genetic correlations between power in the classical broad bands indicated that half to three-quarters of the genetic variance can be attributed to a common source. We conclude that across the scalp and most of the frequency spectrum, individual differences in adult EEG are largely determined by genetic factors.
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Affiliation(s)
- D J A Smit
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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Posthuma D, de Geus EJC, Mulder EJCM, Smit DJA, Boomsma DI, Stam CJ. Genetic components of functional connectivity in the brain: the heritability of synchronization likelihood. Hum Brain Mapp 2006; 26:191-8. [PMID: 15929086 PMCID: PMC6871713 DOI: 10.1002/hbm.20156] [Citation(s) in RCA: 46] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Cognitive functions require the integrated activity of multiple specialized, distributed brain areas. Such functional coupling depends on the existence of anatomical connections between the various brain areas as well as physiological processes whereby the activity in one area influences the activity in another area. Recently, the Synchronization Likelihood (SL) method was developed as a general method to study both linear and nonlinear aspects of coupling. In the present study the genetic architecture of the SL in different frequency bands was investigated. Using a large genetically informative sample of 569 subjects from 282 extended twin families we found that the SL is moderately to highly heritable (41-67%) especially in the alpha frequency (8-13 Hz) range. This index of functional connectivity of the brain has been associated with a number of pathological states of the brain. The significant heritability found here suggests that SL can be used to examine the genetic susceptibility to these conditions.
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Affiliation(s)
- Danielle Posthuma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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