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Wootton O, Shadrin AA, Bjella T, Smeland OB, van der Meer D, Frei O, O'Connell KS, Ueland T, Andreassen OA, Stein DJ, Dalvie S. Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia. Sci Rep 2024; 14:15356. [PMID: 38961113 PMCID: PMC11222449 DOI: 10.1038/s41598-024-66085-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 06/26/2024] [Indexed: 07/05/2024] Open
Abstract
Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.
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Affiliation(s)
- Olivia Wootton
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
| | - Alexey A Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Thomas Bjella
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Blindern, Oslo, Norway
| | - Kevin S O'Connell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torill Ueland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- SAMRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Shareefa Dalvie
- Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa
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2
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Holen B, Kutrolli G, Shadrin AA, Icick R, Hindley G, Rødevand L, O'Connell KS, Frei O, Parker N, Tesfaye M, Deak JD, Jahołkowski P, Dale AM, Djurovic S, Andreassen OA, Smeland OB. Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability. Drug Alcohol Depend 2024; 256:111058. [PMID: 38244365 DOI: 10.1016/j.drugalcdep.2023.111058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 11/09/2023] [Accepted: 12/03/2023] [Indexed: 01/22/2024]
Abstract
BACKGROUND Opioid use disorder (OUD), a serious health burden worldwide, is associated with lower cognitive function. Recent studies have demonstrated a negative genetic correlation between OUD and general cognitive ability (COG), indicating a shared genetic basis. However, the specific genetic variants involved, and the underlying molecular mechanisms remain poorly understood. Here, we aimed to quantify and identify the genetic basis underlying OUD and COG. METHODS We quantified the extent of genetic overlap between OUD and COG using a bivariate causal mixture model (MiXeR) and identified specific genetic loci applying conditional/conjunctional FDR. Finally, we investigated biological function and expression of implicated genes using available resources. RESULTS We estimated that ~94% of OUD variants (4.8k out of 5.1k variants) also influence COG. We identified three novel OUD risk loci and one locus shared between OUD and COG. Loci identified implicated biological substrates in the basal ganglia. CONCLUSION We provide new insights into the complex genetic risk architecture of OUD and its genetic relationship with COG.
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Affiliation(s)
- Børge Holen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway.
| | - Gleda Kutrolli
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Alexey A Shadrin
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Romain Icick
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway; INSERM UMR-S1144, Université Paris Cité, F-75006, France
| | - Guy Hindley
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Linn Rødevand
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Kevin S O'Connell
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Oleksandr Frei
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Nadine Parker
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Markos Tesfaye
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway; NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Joseph D Deak
- Yale School of Medicine, New Haven, CT, USA; VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Piotr Jahołkowski
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA; Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA 92093, USA; Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway
| | - Olav B Smeland
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo 0407, Norway.
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3
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Koch E, Pardiñas AF, O'Connell KS, Selvaggi P, Camacho Collados J, Babic A, Marshall SE, Van der Eycken E, Angulo C, Lu Y, Sullivan PF, Dale AM, Molden E, Posthuma D, White N, Schubert A, Djurovic S, Heimer H, Stefánsson H, Stefánsson K, Werge T, Sønderby I, O'Donovan MC, Walters JTR, Milani L, Andreassen OA. How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry. Biol Psychiatry 2024:S0006-3223(24)00003-9. [PMID: 38185234 DOI: 10.1016/j.biopsych.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 01/09/2024]
Abstract
Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.
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Affiliation(s)
- Elise Koch
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Kevin S O'Connell
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pierluigi Selvaggi
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - José Camacho Collados
- CardiffNLP, School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
| | | | | | - Erik Van der Eycken
- Global Alliance of Mental Illness Advocacy Networks-Europe, Brussels, Belgium
| | - Cecilia Angulo
- Global Alliance of Mental Illness Advocacy Networks-Europe, Brussels, Belgium
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden; Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill, North Carolina
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, California; Departments of Radiology, Psychiatry, and Neurosciences, University of California, San Diego, La Jolla, California
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Nathan White
- CorTechs Laboratories, Inc., San Diego, California
| | | | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; The Norwegian Centre for Mental Disorders Research Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Hakon Heimer
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Nordic Society of Human Genetics and Precision Medicine, Copenhagen, Denmark
| | | | | | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark; Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Ida Sønderby
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia; Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway.
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4
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Jaholkowski P, Hindley GFL, Shadrin AA, Tesfaye M, Bahrami S, Nerhus M, Rahman Z, O’Connell KS, Holen B, Parker N, Cheng W, Lin A, Rødevand L, Karadag N, Frei O, Djurovic S, Dale AM, Smeland OB, Andreassen OA. Genome-wide Association Analysis of Schizophrenia and Vitamin D Levels Shows Shared Genetic Architecture and Identifies Novel Risk Loci. Schizophr Bull 2023; 49:1654-1664. [PMID: 37163672 PMCID: PMC10686370 DOI: 10.1093/schbul/sbad063] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Low vitamin D (vitD) levels have been consistently reported in schizophrenia (SCZ) suggesting a role in the etiopathology. However, little is known about the role of underlying shared genetic mechanisms. We applied a conditional/conjunctional false discovery rate approach (FDR) on large, nonoverlapping genome-wide association studies for SCZ (N cases = 53 386, N controls = 77 258) and vitD serum concentration (N = 417 580) to evaluate shared common genetic variants. The identified genomic loci were characterized using functional analyses and biological repositories. We observed cross-trait SNP enrichment in SCZ conditioned on vitD and vice versa, demonstrating shared genetic architecture. Applying the conjunctional FDR approach, we identified 72 loci jointly associated with SCZ and vitD at conjunctional FDR < 0.05. Among the 72 shared loci, 40 loci have not previously been reported for vitD, and 9 were novel for SCZ. Further, 64% had discordant effects on SCZ-risk and vitD levels. A mixture of shared variants with concordant and discordant effects with a predominance of discordant effects was in line with weak negative genetic correlation (rg = -0.085). Our results displayed shared genetic architecture between SCZ and vitD with mixed effect directions, suggesting overlapping biological pathways. Shared genetic variants with complex overlapping mechanisms may contribute to the coexistence of SCZ and vitD deficiency and influence the clinical picture.
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Affiliation(s)
- Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Guy F L Hindley
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology and Neuroscience, King’s College
London, London, UK
| | - Alexey A Shadrin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and
Oslo University Hospital, Oslo, Norway
| | - Markos Tesfaye
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Department of Psychiatry, St. Paul’s Hospital Millennium Medical
College, Addis Ababa, Ethiopia
| | - Shahram Bahrami
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Mari Nerhus
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Department of Special Psychiatry, Akershus University
Hospital, Lørenskog, Norway
- Division of Health Services Research and Psychiatry,
Institute of Clinical Medicine, Campus Ahus, University of Oslo,
Oslo, Norway
| | - Zillur Rahman
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Kevin S O’Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Børge Holen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Nadine Parker
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Weiqiu Cheng
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Aihua Lin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Linn Rødevand
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Naz Karadag
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of
Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital,
Oslo, Norway
- NORMENT Centre, Department of Clinical Science, University of
Bergen, Bergen, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego,
La Jolla, CA
- Multimodal Imaging Laboratory, University of California San
Diego, La Jolla, CA
- Department of Psychiatry, University of California, San
Diego, La Jolla, CA
- Department of Neurosciences, University of California San
Diego, La Jolla, CA
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health
and Addiction, Oslo University Hospital, and Institute of Clinical Medicine,
University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and
Oslo University Hospital, Oslo, Norway
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5
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Fryar-Williams S, Strobel J, Clements P. Molecular Mechanisms Provide a Landscape for Biomarker Selection for Schizophrenia and Schizoaffective Psychosis. Int J Mol Sci 2023; 24:15296. [PMID: 37894974 PMCID: PMC10607016 DOI: 10.3390/ijms242015296] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 10/07/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
Research evaluating the role of the 5,10-methylenetetrahydrofolate reductase (MTHFR C677T) gene in schizophrenia has not yet provided an extended understanding of the proximal pathways contributing to the 5-10-methylenetetrahydrofolate reductase (MTHFR) enzyme's activity and the distal pathways being affected by its activity. This review investigates these pathways, describing mechanisms relevant to riboflavin availability, trace mineral interactions, and the 5-methyltetrahydrofolate (5-MTHF) product of the MTHFR enzyme. These factors remotely influence vitamin cofactor activation, histamine metabolism, catecholamine metabolism, serotonin metabolism, the oxidative stress response, DNA methylation, and nicotinamide synthesis. These biochemical components form a broad interactive landscape from which candidate markers can be drawn for research inquiry into schizophrenia and other forms of mental illness. Candidate markers drawn from this functional biochemical background have been found to have biomarker status with greater than 90% specificity and sensitivity for achieving diagnostic certainty in schizophrenia and schizoaffective psychosis. This has implications for achieving targeted treatments for serious mental illness.
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Affiliation(s)
- Stephanie Fryar-Williams
- Youth in Mind Research Institute, Unley Annexe, Mary Street, Unley, SA 5061, Australia
- Department of Nanoscale BioPhotonics, School of Biomedicine, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA 5000, Australia
| | - Jörg Strobel
- Department of Psychiatry, Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA 5000, Australia;
| | - Peter Clements
- Department of Paediatrics, Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA 5000, Australia;
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6
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Wang F, Wang H, Yuan Y, Han B, Qiu S, Hu Y, Zang T. Integration of multiple-omics data to reveal the shared genetic architecture of educational attainment, intelligence, cognitive performance, and Alzheimer's disease. Front Genet 2023; 14:1243879. [PMID: 37900179 PMCID: PMC10601659 DOI: 10.3389/fgene.2023.1243879] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 09/01/2023] [Indexed: 10/31/2023] Open
Abstract
Growing evidence suggests the effect of educational attainment (EA) on Alzheimer's disease (AD), but less is known about the shared genetic architecture between them. Here, leveraging genome-wide association studies (GWAS) for AD (N = 21,982/41,944), EA (N = 1,131,881), cognitive performance (N = 257,828), and intelligence (N = 78,308), we investigated their causal association with the linkage disequilibrium score (LDSC) and Mendelian randomization and their shared loci with the conjunctional false discovery rate (conjFDR), transcriptome-wide association studies (TWAS), and colocalization. We observed significant genetic correlations of EA (rg = -0.22, p = 5.07E-05), cognitive performance (rg = -0.27, p = 2.44E-05), and intelligence (rg = -0.30, p = 3.00E-04) with AD, and a causal relationship between EA and AD (OR = 0.74, 95% CI: 0.58-0.94, p = 0.013). We identified 13 shared loci at conjFDR <0.01, of which five were novel, and prioritized three causal genes. These findings inform early prevention strategies for AD.
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Affiliation(s)
- Fuxu Wang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Haoyan Wang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Ye Yuan
- Beidahuang Industry Group General Hospital, Harbin, China
| | - Bing Han
- Aier Eye Hospital, Harbin, China
| | - Shizheng Qiu
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Yang Hu
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Tianyi Zang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
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7
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Sha Z, Warrier V, Bethlehem RA, Schultz LM, Merikangas A, Sun KY, Gur RC, Gur RE, Shinohara RT, Seidlitz J, Almasy L, Andreassen OA, Alexander-Bloch AF. The overlapping genetic architecture of psychiatric disorders and cortical brain structure. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.05.561040. [PMID: 37873315 PMCID: PMC10592957 DOI: 10.1101/2023.10.05.561040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Both psychiatric vulnerability and cortical structure are shaped by the cumulative effect of common genetic variants across the genome. However, the shared genetic underpinnings between psychiatric disorders and brain structural phenotypes, such as thickness and surface area of the cerebral cortex, remains elusive. In this study, we employed pleiotropy-informed conjunctional false discovery rate analysis to investigate shared loci across genome-wide association scans of regional cortical thickness, surface area, and seven psychiatric disorders in approximately 700,000 individuals of European ancestry. Aggregating regional measures, we identified 50 genetic loci shared between psychiatric disorders and surface area, as well as 26 genetic loci shared with cortical thickness. Risk alleles exhibited bidirectional effects on both cortical thickness and surface area, such that some risk alleles for each disorder increased regional brain size while other risk alleles decreased regional brain size. Due to bidirectional effects, in many cases we observed extensive pleiotropy between an imaging phenotype and a psychiatric disorder even in the absence of a significant genetic correlation between them. The impact of genetic risk for psychiatric disorders on regional brain structure did exhibit a consistent pattern across highly comorbid psychiatric disorders, with 80% of the genetic loci shared across multiple disorders displaying consistent directions of effect. Cortical patterning of genetic overlap revealed a hierarchical genetic architecture, with the association cortex and sensorimotor cortex representing two extremes of shared genetic influence on psychiatric disorders and brain structural variation. Integrating multi-scale functional annotations and transcriptomic profiles, we observed that shared genetic loci were enriched in active genomic regions, converged on neurobiological and metabolic pathways, and showed differential expression in postmortem brain tissue from individuals with psychiatric disorders. Cumulatively, these findings provide a significant advance in our understanding of the overlapping polygenic architecture between psychopathology and cortical brain structure.
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Affiliation(s)
- Zhiqiang Sha
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | | | - Laura M. Schultz
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Alison Merikangas
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kevin Y. Sun
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
- Center for Biomedical Image Computing and Analytics (CBICA), Department of Radiology, Perelman School of Medicine, United States
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Laura Almasy
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aaron F. Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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8
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Tesfaye M, Jaholkowski P, Hindley GFL, Shadrin AA, Rahman Z, Bahrami S, Lin A, Holen B, Parker N, Cheng W, Rødevand L, Frei O, Djurovic S, Dale AM, Smeland OB, O'Connell KS, Andreassen OA. Shared genetic architecture between irritable bowel syndrome and psychiatric disorders reveals molecular pathways of the gut-brain axis. Genome Med 2023; 15:60. [PMID: 37528461 PMCID: PMC10391890 DOI: 10.1186/s13073-023-01212-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/12/2023] [Indexed: 08/03/2023] Open
Abstract
BACKGROUND Irritable bowel syndrome (IBS) often co-occurs with psychiatric and gastrointestinal disorders. A recent genome-wide association study (GWAS) identified several genetic risk variants for IBS. However, most of the heritability remains unidentified, and the genetic overlap with psychiatric and somatic disorders is not quantified beyond genome-wide genetic correlations. Here, we characterize the genetic architecture of IBS, further, investigate its genetic overlap with psychiatric and gastrointestinal phenotypes, and identify novel genomic risk loci. METHODS Using GWAS summary statistics of IBS (53,400 cases and 433,201 controls), and psychiatric and gastrointestinal phenotypes, we performed bivariate casual mixture model analysis to characterize the genetic architecture and genetic overlap between these phenotypes. We leveraged identified genetic overlap to boost the discovery of genomic loci associated with IBS, and to identify specific shared loci associated with both IBS and psychiatric and gastrointestinal phenotypes, using the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework. We used functional mapping and gene annotation (FUMA) for functional analyses. RESULTS IBS was highly polygenic with 12k trait-influencing variants. We found extensive polygenic overlap between IBS and psychiatric disorders and to a lesser extent with gastrointestinal diseases. We identified 132 independent IBS-associated loci (condFDR < 0.05) by conditioning on psychiatric disorders (n = 127) and gastrointestinal diseases (n = 24). Using conjFDR, 70 unique loci were shared between IBS and psychiatric disorders. Functional analyses of shared loci revealed enrichment for biological pathways of the nervous and immune systems. Genetic correlations and shared loci between psychiatric disorders and IBS subtypes were different. CONCLUSIONS We found extensive polygenic overlap of IBS and psychiatric and gastrointestinal phenotypes beyond what was revealed with genetic correlations. Leveraging the overlap, we discovered genetic loci associated with IBS which implicate a wide range of biological pathways beyond the gut-brain axis. Genetic differences may underlie the clinical subtype of IBS. These results increase our understanding of the pathophysiology of IBS which may form the basis for the development of individualized interventions.
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Affiliation(s)
- Markos Tesfaye
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- NORMENT, Department of Clinical Sciences, University of Bergen, Bergen, Norway.
| | - Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy F L Hindley
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Alexey A Shadrin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Zillur Rahman
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aihua Lin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Børge Holen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nadine Parker
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Weiqiu Cheng
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Linn Rødevand
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- NORMENT, Department of Clinical Sciences, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kevin S O'Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway.
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9
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O'Connell KS, Koch E, Lenk HÇ, Akkouh IA, Hindley G, Jaholkowski P, Smith RL, Holen B, Shadrin AA, Frei O, Smeland OB, Steen NE, Dale AM, Molden E, Djurovic S, Andreassen OA. Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia. Psychiatry Res 2023; 325:115217. [PMID: 37146461 PMCID: PMC10788293 DOI: 10.1016/j.psychres.2023.115217] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 04/03/2023] [Accepted: 04/21/2023] [Indexed: 05/07/2023]
Abstract
Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.
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Affiliation(s)
- Kevin S O'Connell
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Elise Koch
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Hasan Çağın Lenk
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway; Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Ibrahim A Akkouh
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Guy Hindley
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, United Kingdom
| | - Piotr Jaholkowski
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Robert Løvsletten Smith
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
| | - Børge Holen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alexey A Shadrin
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Center for Bioinformatics, Department of Informatics, University of Oslo, 0316 Oslo, Norway
| | - Olav B Smeland
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA; Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway; Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway.
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10
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Fominykh V, Shadrin AA, Jaholkowski PP, Bahrami S, Athanasiu L, Wightman DP, Uffelmann E, Posthuma D, Selbæk G, Dale AM, Djurovic S, Frei O, Andreassen OA. Shared genetic loci between Alzheimer's disease and multiple sclerosis: Crossroads between neurodegeneration and immune system. Neurobiol Dis 2023:106174. [PMID: 37286172 DOI: 10.1016/j.nbd.2023.106174] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/27/2023] [Accepted: 05/26/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND Neuroinflammation is involved in the pathophysiology of Alzheimer's disease (AD), including immune-linked genetic variants and molecular pathways, microglia and astrocytes. Multiple Sclerosis (MS) is a chronic, immune-mediated disease with genetic and environmental risk factors and neuropathological features. There are clinical and pathobiological similarities between AD and MS. Here, we investigated shared genetic susceptibility between AD and MS to identify putative pathological mechanisms shared between neurodegeneration and the immune system. METHODS We analysed GWAS data for late-onset AD (N cases = 64,549, N controls = 634,442) and MS (N cases = 14,802, N controls = 26,703). Gaussian causal mixture modelling (MiXeR) was applied to characterise the genetic architecture and overlap between AD and MS. Local genetic correlation was investigated with Local Analysis of [co]Variant Association (LAVA). The conjunctional false discovery rate (conjFDR) framework was used to identify the specific shared genetic loci, for which functional annotation was conducted with FUMA and Open Targets. RESULTS MiXeR analysis showed comparable polygenicities for AD and MS (approximately 1800 trait-influencing variants) and genetic overlap with 20% of shared trait-influencing variants despite negligible genetic correlation (rg = 0.03), suggesting mixed directions of genetic effects across shared variants. conjFDR analysis identified 16 shared genetic loci, with 8 having concordant direction of effects in AD and MS. Annotated genes in shared loci were enriched in molecular signalling pathways involved in inflammation and the structural organisation of neurons. CONCLUSIONS Despite low global genetic correlation, the current results provide evidence for polygenic overlap between AD and MS. The shared loci between AD and MS were enriched in pathways involved in inflammation and neurodegeneration, highlighting new opportunities for future investigation.
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Affiliation(s)
- Vera Fominykh
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Alexey A Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Piotr P Jaholkowski
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lavinia Athanasiu
- NORMENT Centre, 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
| | - Douglas P Wightman
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Emil Uffelmann
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Pediatric Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam, the Netherlands
| | - Geir Selbæk
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Vestfold Hospital Trust, Norwegian National Centre for Ageing and Health, Tonsberg, Vestfold, Norway
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA; Multimodal Imaging Laboratory, University of California San Diego, La Jolla, California, USA; Department of Psychiatry, University of California San Diego, La Jolla, California, USA; Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Srdjan Djurovic
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Informatics, Centre for Bioinformatics, University of Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; 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
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11
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Chen Y, Guo H, Yue W. Shared genetic loci and causal relations between schizophrenia and obsessive-compulsive disorder. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:20. [PMID: 37029179 PMCID: PMC10082206 DOI: 10.1038/s41537-023-00348-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 03/15/2023] [Indexed: 04/09/2023]
Abstract
Based on the clinical overlap between schizophrenia (SCZ) and obsessive-compulsive disorder (OCD), both disorders may share neurobiological substrates. In this study, we first analyzed recent large genome-wide associations studies (GWAS) on SCZ (n = 53,386, Psychiatric Genomics Consortium Wave 3) and OCD (n = 2688, the International Obsessive-Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) and the OCD Collaborative Genetics Association Study (OCGAS)) using a conjunctional false discovery rate (FDR) approach to evaluate overlap in common genetic variants of European descent. Using a variety of biological resources, we functionally characterized the identified genomic loci. Then we used two-sample Mendelian randomization (MR) to estimate the bidirectional causal association between SCZ and OCD. Results showed that there is a positive genetic correlation between SCZ and OCD (rg = 0.36, P = 0.02). We identified that one genetic locus (lead SNP rs5757717 in an intergenic region at CACNA1I) was jointly associated with SCZ and OCD (conjFDR = 2.12 × 10-2). Mendelian randomization results showed that variants associated with increased risk for SCZ also increased the risk of OCD. This study broadens our understanding of the genetic architectures underpinning SCZ and OCD and suggests that the same molecular genetic processes may be responsible for shared pathophysiological and clinical characteristics between the two disorders.
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Affiliation(s)
- Yu Chen
- Department of Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, 453002, China
| | - Hua Guo
- Zhumadian second people's hospital, Henan, 463899, China.
| | - Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
- Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
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12
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Cheng W, van der Meer D, Parker N, Hindley G, O'Connell KS, Wang Y, Shadrin AA, Alnæs D, Bahrami S, Lin A, Karadag N, Holen B, Fernandez-Cabello S, Fan CC, Dale AM, Djurovic S, Westlye LT, Frei O, Smeland OB, Andreassen OA. Shared genetic architecture between schizophrenia and subcortical brain volumes implicates early neurodevelopmental processes and brain development in childhood. Mol Psychiatry 2022; 27:5167-5176. [PMID: 36100668 DOI: 10.1038/s41380-022-01751-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 08/10/2022] [Accepted: 08/12/2022] [Indexed: 01/14/2023]
Abstract
Patients with schizophrenia have consistently shown brain volumetric abnormalities, implicating both etiological and pathological processes. However, the genetic relationship between schizophrenia and brain volumetric abnormalities remains poorly understood. Here, we applied novel statistical genetic approaches (MiXeR and conjunctional false discovery rate analysis) to investigate genetic overlap with mixed effect directions using independent genome-wide association studies of schizophrenia (n = 130,644) and brain volumetric phenotypes, including subcortical brain and intracranial volumes (n = 33,735). We found brain volumetric phenotypes share substantial genetic variants (74-96%) with schizophrenia, and observed 107 distinct shared loci with sign consistency in independent samples. Genes mapped by shared loci revealed (1) significant enrichment in neurodevelopmental biological processes, (2) three co-expression clusters with peak expression at the prenatal stage, and (3) genetically imputed thalamic expression of CRHR1 and ARL17A was associated with the thalamic volume as early as in childhood. Together, our findings provide evidence of shared genetic architecture between schizophrenia and brain volumetric phenotypes and suggest that altered early neurodevelopmental processes and brain development in childhood may be involved in schizophrenia development.
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Affiliation(s)
- Weiqiu Cheng
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Nadine Parker
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy Hindley
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Kevin S O'Connell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Yunpeng Wang
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Centre for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Alexey A Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aihua Lin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Naz Karadag
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Børge Holen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Sara Fernandez-Cabello
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Chun-Chieh Fan
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92093, USA.,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, USA
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92093, USA.,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, USA.,Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
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13
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Zheng H, Sun J, Pang T, Liu J, Lu L, Chang S. Identify novel, shared and disorder-specific genetic architecture of major depressive disorder, insomnia and chronic pain. J Psychiatr Res 2022; 155:511-517. [PMID: 36191519 DOI: 10.1016/j.jpsychires.2022.09.036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 08/01/2022] [Accepted: 09/16/2022] [Indexed: 12/12/2022]
Abstract
Major depressive disorder (MDD), insomnia (INS) and chronic pain (CP) often have high comorbidity and show high genetic correlation. Here we aimed to better characterize their novel, shared and disorder-specific genetic architecture. Based on genome-wide association study (GWAS) summary data, we applied the conditional false discovery rate (condFDR) and conjunctional FDR (conjFDR) approach to investigate the novel and overlapped genetic loci for MDD, INS and CP. In addition, putative disorder-specific SNP associations were analyzed by conditioning the other two traits. The functions of the identified genomic loci were explored by performing gene set enrichment analysis (GSEA) for the loci mapped genes. We identified 22, 43 and 91 novel risk loci for MDD, INS and CP. GSEA for the loci mapped genes highlighted olfactory signaling pathway for MDD novel loci, breast cancer related gene set for both INS and CP novel loci, and nervous system related development, structure and activity for CP. Furthermore, we identified three loci jointly associated with the three disorders, including 13q14.3 locus with nearby gene OLFM4, 14q21.1 locus with nearby gene LRFN5 and 5q21.2 locus located in intergenic region. In addition, we identified one specific loci for MDD, 7 for INS and 11 for CP respectively by conditioning the other two traits, which were mapped to 68 genes for MDD, 85 for INS and 100 for CP. The MDD specific genes are enriched in immune system related pathways. This study increases understanding of the genetic architectures underlying MDD, INS and CP. The shared underlying genetic risk may help to explain the high comorbidity rates of the disorders.
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Affiliation(s)
- Haohao Zheng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Jie Sun
- Center for Pain Medicine, Peking University Third Hospital, Beijing, 100191, China
| | - Tao Pang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Jiajia Liu
- School of Nursing, Peking University, Beijing, 100191, China
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Chinese Academy of Medical Sciences Research Unit (No.2018RU006), Peking University, Beijing, 100191, China; National Institute on Drug Dependence, Peking University, Beijing, 100191, China
| | - Suhua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Chinese Academy of Medical Sciences Research Unit (No.2018RU006), Peking University, Beijing, 100191, China.
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14
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Wu Y, Li Y, Zhu J, Long J. Shared genetics and causality underlying epilepsy and attention-deficit hyperactivity disorder. Psychiatry Res 2022; 316:114794. [PMID: 35994864 DOI: 10.1016/j.psychres.2022.114794] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/06/2022] [Accepted: 08/12/2022] [Indexed: 11/18/2022]
Abstract
The prevalence of attention deficit hyperactivity disorder (ADHD) in patients with epilepsy was much higher than prevalence in general population, and vice versa. The mechanisms underlying comorbid ADHD and epilepsy remained largely unknown. Here, we systematically analyzed the genetic correlation, causality, shared genetics and specific trait related tissues by using linkage disequilibrium score regression (LDSC), two sample Mendelian randomization (TwoSampleMR), bivariate causal mixture model (MiXeR), conjunctional false discovery rate (conjFDR) and LDSC applied to specifically expressed genes based on genome wide association studies (GWASs) data of ADHD and epilepsy. We found that ADHD had significant positive genetic association with epilepsy. Two-sample Mendelian randomization analysis with genome wide significant single nucleotide polymorphisms (SNPs) as instrument variables suggested a positively causal effect of ADHD on epilepsy. Using MiXeR, which estimates the total amount of shared variants, we observed 1 K causal variants overlapped between ADHD and epilepsy. At conjFDR <0.05, ADHD shared 2 distinct genomic loci with Epilepsy. Further disease-relevant tissues analysis showed that cortex, substantia nigra, amygdala and hippocampus were both associated with ADHD and epilepsy. Our results suggested that ADHD was genetically correlated with epilepsy, which might be due to the fact that they shared common pathogenic sites and tissues origin.
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Affiliation(s)
- Yong Wu
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei 430012, China
| | - Yichen Li
- Radiology Department, Wuhan Mental Health Center, Wuhan, Hubei 430012, China
| | - Junhong Zhu
- Department of Mental Rehabilitation, Wuhan Mental Health Center, Wuhan, Hubei 430012, China.
| | - Jingyi Long
- Department of Child & Adolescent Psychiatry, Wuhan Mental Health Center, Wuhan, Hubei 430012, China.
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15
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van der Meer D, Shadrin AA, O'Connell K, Bettella F, Djurovic S, Wolfers T, Alnæs D, Agartz I, Smeland OB, Melle I, Sánchez JM, Linden DEJ, Dale AM, Westlye LT, Andreassen OA, Frei O, Kaufmann T. Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology. Biol Psychiatry 2022; 92:291-298. [PMID: 35164939 DOI: 10.1016/j.biopsych.2021.12.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/06/2021] [Accepted: 12/09/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. METHODS We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls. RESULTS We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios. CONCLUSIONS Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue-specific genetic variants and its use in polygenic risk frameworks.
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Affiliation(s)
- Dennis van der Meer
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands.
| | - Alexey A Shadrin
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kevin O'Connell
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Thomas Wolfers
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jennifer Monereo Sánchez
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - David E J Linden
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
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16
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The psychiatric risk gene BRD1 modulates mitochondrial bioenergetics by transcriptional regulation. Transl Psychiatry 2022; 12:319. [PMID: 35941107 PMCID: PMC9359996 DOI: 10.1038/s41398-022-02053-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 06/24/2022] [Accepted: 07/01/2022] [Indexed: 12/03/2022] Open
Abstract
Bromodomain containing 1 (BRD1) encodes an epigenetic regulator that controls the expression of genetic networks linked to mental illness. BRD1 is essential for normal brain development and its role in psychopathology has been demonstrated in genetic and preclinical studies. However, the neurobiology that bridges its molecular and neuropathological effects remains poorly explored. Here, using publicly available datasets, we find that BRD1 targets nuclear genes encoding mitochondrial proteins in cell lines and that modulation of BRD1 expression, irrespective of whether it is downregulation or upregulation of one or the other existing BRD1 isoforms (BRD1-L and BRD1-S), leads to distinct shifts in the expression profile of these genes. We further show that the expression of nuclear genes encoding mitochondrial proteins is negatively correlated with the expression of BRD1 mRNA during human brain development. In accordance, we identify the key gate-keeper of mitochondrial metabolism, Peroxisome proliferator-activated receptor (PPAR) among BRD1's co-transcription factors and provide evidence that BRD1 acts as a co-repressor of PPAR-mediated transcription. Lastly, when using quantitative PCR, mitochondria-targeted fluorescent probes, and the Seahorse XFe96 Analyzer, we demonstrate that modulation of BRD1 expression in cell lines alters mitochondrial physiology (mtDNA content and mitochondrial mass), metabolism (reducing power), and bioenergetics (among others, basal, maximal, and spare respiration) in an expression level- and isoform-dependent manner. Collectively, our data suggest that BRD1 is a transcriptional regulator of nuclear-encoded mitochondrial proteins and that disruption of BRD1's genomic actions alters mitochondrial functions. This may be the mechanism underlying the cellular and atrophic changes of neurons previously associated with BRD1 deficiency and suggests that mitochondrial dysfunction may be a possible link between genetic variation in BRD1 and psychopathology in humans.
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17
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Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes. Biomedicines 2022; 10:biomedicines10020368. [PMID: 35203577 PMCID: PMC8962243 DOI: 10.3390/biomedicines10020368] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 01/27/2022] [Accepted: 01/29/2022] [Indexed: 02/04/2023] Open
Abstract
Accumulating evidence suggests a relationship between type 2 diabetes mellitus and sleep problems. A comprehensive study is needed to decipher whether shared polygenic risk variants exist between diabetic traits and sleep traits. Methods: We integrated summary statistics from different genome-wide association studies and investigated overlap in single-nucleotide polymorphisms (SNPs) associated with diabetes-related traits (type 2 diabetes, fasting glucose, fasting insulin, and glycated hemoglobin) and sleep traits (insomnia symptoms, sleep duration, and chronotype) using a conditional/conjunctional false discovery rate approach. Pleiotropic genes were further evaluated for differential expression analysis, and we assessed their expression pattern effects on type 2 diabetes by Mendelian randomization (MR) analysis. Results: We observed extensive polygenic pleiotropy between diabetic traits and sleep traits. Fifty-eight independent genetic loci jointly influenced the risk of type 2 diabetes and the sleep traits of insomnia, sleep duration, and chronotype. The strongest shared locus between type 2 diabetes and sleep straits was FTO (lead SNP rs8047587). Type 2 diabetes (z score, 16.19; P = 6.29 × 10−59) and two sleep traits, sleep duration (z score, −6.66; P = 2.66 × 10−11) and chronotype (z score, 7.42; P = 1.19 × 10−13), were shared. Two of the pleiotropic genes, ENSA and PMPCA, were validated to be differentially expressed in type 2 diabetes, and PMPCA showed a slight protective effect on type 2 diabetes in MR analysis. Conclusions: Our study provided evidence for the polygenic overlap between diabetic traits and sleep traits, of which the expression of PMPCA may play a crucial role and provide support of the hazardous effect of being an “evening” person on diabetes risk.
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18
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Characterizing the Genetic Overlap Between Psychiatric Disorders and Sleep-Related Phenotypes. Biol Psychiatry 2021; 90:621-631. [PMID: 34482950 DOI: 10.1016/j.biopsych.2021.07.007] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 07/05/2021] [Accepted: 07/07/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND A range of sleep disturbances are commonly experienced by patients with psychiatric disorders, and genome-wide genetic analyses have shown some significant genetic correlations between these traits. Here, we applied novel statistical genetic methodologies to better characterize the potential shared genetic architecture between sleep-related phenotypes and psychiatric disorders. METHODS Using the MiXeR method, which can estimate polygenic overlap beyond genetic correlation, the shared genetic architecture between major psychiatric disorders (bipolar disorder [N = 51,710], depression [N = 480,359], and schizophrenia [N = 77,096]) and sleep-related phenotypes (chronotype [N = 449,734], insomnia [N = 386,533] and sleep duration [N = 446,118]) were quantified on the basis of genetic summary statistics. Furthermore, the conditional/conjunctional false discovery rate framework was used to identify specific shared loci between these phenotypes, for which positional and functional annotation were conducted with FUMA. RESULTS Extensive genetic overlap between the sleep-related phenotypes and bipolar disorder (63%-77%), depression (76%-79%), and schizophrenia (64%-79%) was identified, with moderate levels of congruence between most investigated traits (47%-58%). Specific shared loci were identified for all bivariate analyses, and a subset of 70 credible genes were mapped to these shared loci. CONCLUSIONS The current results provide evidence for substantial polygenic overlap between psychiatric disorders and sleep-related phenotypes, beyond genetic correlation (|rg| = 0.02 to 0.42). Moderate congruency within the shared genetic components suggests a complex genetic relationship and potential subgroups with higher or lower genetic concordance. This work provides new insights and understanding of the shared genetic etiology of sleep-related phenotypes and psychiatric disorders and highlights new opportunities and avenues for future investigation.
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19
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O'Connell KS, Coombes BJ. Genetic contributions to bipolar disorder: current status and future directions. Psychol Med 2021; 51:2156-2167. [PMID: 33879273 PMCID: PMC8477227 DOI: 10.1017/s0033291721001252] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 03/12/2021] [Accepted: 03/19/2021] [Indexed: 12/12/2022]
Abstract
Bipolar disorder (BD) is a highly heritable mental disorder and is estimated to affect about 50 million people worldwide. Our understanding of the genetic etiology of BD has greatly increased in recent years with advances in technology and methodology as well as the adoption of international consortiums and large population-based biobanks. It is clear that BD is also highly heterogeneous and polygenic and shows substantial genetic overlap with other psychiatric disorders. Genetic studies of BD suggest that the number of associated loci is expected to substantially increase in larger future studies and with it, improved genetic prediction of the disorder. Still, a number of challenges remain to fully characterize the genetic architecture of BD. First among these is the need to incorporate ancestrally-diverse samples to move research away from a Eurocentric bias that has the potential to exacerbate health disparities already seen in BD. Furthermore, incorporation of population biobanks, registry data, and electronic health records will be required to increase the sample size necessary for continued genetic discovery, while increased deep phenotyping is necessary to elucidate subtypes within BD. Lastly, the role of rare variation in BD remains to be determined. Meeting these challenges will enable improved identification of causal variants for the disorder and also allow for equitable future clinical applications of both genetic risk prediction and therapeutic interventions.
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Affiliation(s)
- Kevin S. O'Connell
- Division of Mental Health and Addiction, NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo University Hospital, 0407Oslo, Norway
| | - Brandon J. Coombes
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
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20
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Hutchinson A, Reales G, Willis T, Wallace C. Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR. PLoS Genet 2021; 17:e1009853. [PMID: 34669738 PMCID: PMC8559959 DOI: 10.1371/journal.pgen.1009853] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/01/2021] [Accepted: 09/30/2021] [Indexed: 12/15/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified thousands of genetic variants that are associated with complex traits. However, a stringent significance threshold is required to identify robust genetic associations. Leveraging relevant auxiliary covariates has the potential to boost statistical power to exceed the significance threshold. Particularly, abundant pleiotropy and the non-random distribution of SNPs across various functional categories suggests that leveraging GWAS test statistics from related traits and/or functional genomic data may boost GWAS discovery. While type 1 error rate control has become standard in GWAS, control of the false discovery rate can be a more powerful approach. The conditional false discovery rate (cFDR) extends the standard FDR framework by conditioning on auxiliary data to call significant associations, but current implementations are restricted to auxiliary data satisfying specific parametric distributions, typically GWAS p-values for related traits. We relax these distributional assumptions, enabling an extension of the cFDR framework that supports auxiliary covariates from arbitrary continuous distributions ("Flexible cFDR"). Our method can be applied iteratively, thereby supporting multi-dimensional covariate data. Through simulations we show that Flexible cFDR increases sensitivity whilst controlling FDR after one or several iterations. We further demonstrate its practical potential through application to an asthma GWAS, leveraging various functional genomic data to find additional genetic associations for asthma, which we validate in the larger, independent, UK Biobank data resource.
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Affiliation(s)
- Anna Hutchinson
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | - Guillermo Reales
- Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), University of Cambridge, Cambridge, United Kingdom
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Thomas Willis
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | - Chris Wallace
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
- Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), University of Cambridge, Cambridge, United Kingdom
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
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21
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Cheng W, Frei O, van der Meer D, Wang Y, O’Connell KS, Chu Y, Bahrami S, Shadrin AA, Alnæs D, Hindley GFL, Lin A, Karadag N, Fan CC, Westlye LT, Kaufmann T, Molden E, Dale AM, Djurovic S, Smeland OB, Andreassen OA. Genetic Association Between Schizophrenia and Cortical Brain Surface Area and Thickness. JAMA Psychiatry 2021; 78:1020-1030. [PMID: 34160554 PMCID: PMC8223140 DOI: 10.1001/jamapsychiatry.2021.1435] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 04/28/2021] [Indexed: 01/03/2023]
Abstract
Importance Schizophrenia is a complex heritable disorder associated with many genetic variants, each with a small effect. While cortical differences between patients with schizophrenia and healthy controls are consistently reported, the underlying molecular mechanisms remain elusive. Objective To investigate the extent of shared genetic architecture between schizophrenia and brain cortical surface area (SA) and thickness (TH) and to identify shared genomic loci. Design, Setting, and Participants Independent genome-wide association study data on schizophrenia (Psychiatric Genomics Consortium and CLOZUK: n = 105 318) and SA and TH (UK Biobank: n = 33 735) were obtained. The extent of polygenic overlap was investigated using MiXeR. The specific shared genomic loci were identified by conditional/conjunctional false discovery rate analysis and were further examined in 3 independent cohorts. Data were collected from December 2019 to February 2021, and data analysis was performed from May 2020 to February 2021. Main Outcomes and Measures The primary outcomes were estimated fractions of polygenic overlap between schizophrenia, total SA, and average TH and a list of functionally characterized shared genomic loci. Results Based on genome-wide association study data from 139 053 participants, MiXeR estimated schizophrenia to be more polygenic (9703 single-nucleotide variants [SNVs]) than total SA (2101 SNVs) and average TH (1363 SNVs). Most SNVs associated with total SA (1966 of 2101 [93.6%]) and average TH (1322 of 1363 [97.0%]) may be associated with the development of schizophrenia. Subsequent conjunctional false discovery rate analysis identified 44 and 23 schizophrenia risk loci shared with total SA and average TH, respectively. The SNV associations of shared loci between schizophrenia and total SA revealed en masse concordant association between the discovery and independent cohorts. After removing high linkage disequilibrium regions, such as the major histocompatibility complex region, the shared loci were enriched in immunologic signature gene sets. Polygenic overlap and shared loci between schizophrenia and schizophrenia-associated regions of interest for SA (superior frontal and middle temporal gyri) and for TH (superior temporal, inferior temporal, and superior frontal gyri) were also identified. Conclusions and Relevance This study demonstrated shared genetic loci between cortical morphometry and schizophrenia, among which a subset are associated with immunity. These findings provide an insight into the complex genetic architecture and associated with schizophrenia.
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Affiliation(s)
- Weiqiu Cheng
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Yunpeng Wang
- Centre for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Kevin S. O’Connell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Yunhan Chu
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alexey A. Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Guy F. L. Hindley
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King’s College London, London, United Kingdom
| | - Aihua Lin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Naz Karadag
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Chun-Chieh Fan
- Population Neuroscience and Genetics Lab, University of California, San Diego, La Jolla
- Center for Human Development, University of California, San Diego, La Jolla
| | - Lars T. Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway
- Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Anders M. Dale
- Department of Radiology, University of California, San Diego, La Jolla
- Department of Psychiatry, University of California, San Diego, La Jolla
- Department of Neurosciences, University of California San Diego, La Jolla
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Olav B. Smeland
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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22
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O'Connell KS, Shadrin A, Bahrami S, Smeland OB, Bettella F, Frei O, Krull F, Askeland RB, Walters GB, Davíðsdóttir K, Haraldsdóttir GS, Guðmundsson ÓÓ, Stefánsson H, Fan CC, Steen NE, Reichborn-Kjennerud T, Dale AM, Stefánsson K, Djurovic S, Andreassen OA. Identification of genetic overlap and novel risk loci for attention-deficit/hyperactivity disorder and bipolar disorder. Mol Psychiatry 2021; 26:4055-4065. [PMID: 31792363 DOI: 10.1038/s41380-019-0613-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 11/07/2019] [Accepted: 11/15/2019] [Indexed: 12/13/2022]
Abstract
Differential diagnosis between childhood onset attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) remains a challenge, mainly due to overlapping symptoms and high rates of comorbidity. Despite this, genetic correlation reported for these disorders is low and non-significant. Here we aimed to better characterize the genetic architecture of these disorders utilizing recent large genome-wide association studies (GWAS). We analyzed independent GWAS summary statistics for ADHD (19,099 cases and 34,194 controls) and BD (20,352 cases and 31,358 controls) applying the conditional/conjunctional false discovery rate (condFDR/conjFDR) statistical framework that increases the power to detect novel phenotype-specific and shared loci by leveraging the combined power of two GWAS. We observed cross-trait polygenic enrichment for ADHD conditioned on associations with BD, and vice versa. Leveraging this enrichment, we identified 19 novel ADHD risk loci and 40 novel BD risk loci at condFDR <0.05. Further, we identified five loci jointly associated with ADHD and BD (conjFDR < 0.05). Interestingly, these five loci show concordant directions of effect for ADHD and BD. These results highlight a shared underlying genetic risk for ADHD and BD which may help to explain the high comorbidity rates and difficulties in differentiating between ADHD and BD in the clinic. Improving our understanding of the underlying genetic architecture of these disorders may aid in the development of novel stratification tools to help reduce these diagnostic difficulties.
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Affiliation(s)
- Kevin S O'Connell
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.
| | - Alexey Shadrin
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Olav B Smeland
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Francesco Bettella
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Florian Krull
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Ragna B Askeland
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - G Bragi Walters
- deCODE genetics/Amgen, Reykjavík, Iceland.,Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Katrín Davíðsdóttir
- The Centre for Child Development and Behaviour, Capital Area Primary Health Care, Reykjavik, Iceland
| | - Gyða S Haraldsdóttir
- The Centre for Child Development and Behaviour, Capital Area Primary Health Care, Reykjavik, Iceland
| | - Ólafur Ó Guðmundsson
- deCODE genetics/Amgen, Reykjavík, Iceland.,Faculty of Medicine, University of Iceland, Reykjavík, Iceland.,Department of Child and Adolescent Psychiatry, National University Hospital, Reykjavik, Iceland
| | | | - Chun C Fan
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA.,Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Nils Eiel Steen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA.,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, 92093, USA.,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, USA
| | - Kári Stefánsson
- deCODE genetics/Amgen, Reykjavík, Iceland.,Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway. .,Departments of Neurology and Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
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23
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Identification of pleiotropy at the gene level between psychiatric disorders and related traits. Transl Psychiatry 2021; 11:410. [PMID: 34326310 PMCID: PMC8322263 DOI: 10.1038/s41398-021-01530-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 04/08/2021] [Accepted: 06/21/2021] [Indexed: 01/22/2023] Open
Abstract
Major mental disorders are highly prevalent and make a substantial contribution to the global disease burden. It is known that mental disorders share clinical characteristics, and genome-wide association studies (GWASs) have recently provided evidence for shared genetic factors as well. Genetic overlaps are usually identified at the single-marker level. Here, we aimed to identify genetic overlaps at the gene level between 7 mental disorders (schizophrenia, autism spectrum disorder, major depressive disorder, anorexia nervosa, ADHD, bipolar disorder and anxiety), 8 brain morphometric traits, 2 cognitive traits (educational attainment and general cognitive function) and 9 personality traits (subjective well-being, depressive symptoms, neuroticism, extraversion, openness to experience, agreeableness and conscientiousness, children's aggressive behaviour, loneliness) based on publicly available GWASs. We performed systematic conditional regression analyses to identify independent signals and select loci associated with more than one trait. We identified 48 genes containing independent markers associated with several traits (pleiotropy at the gene level). We also report 9 genes with different markers that show independent associations with single traits (allelic heterogeneity). This study demonstrates that mental disorders and related traits do show pleiotropy at the gene level as well as the single-marker level. The identification of these genes might be important for prioritizing further deep genotyping, functional studies, or drug targeting.
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24
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Genetic loci shared between major depression and intelligence with mixed directions of effect. Nat Hum Behav 2021; 5:795-801. [PMID: 33462475 PMCID: PMC8217082 DOI: 10.1038/s41562-020-01031-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 12/04/2020] [Indexed: 01/29/2023]
Abstract
Genome-wide association studies (GWAS) have identified several common genetic variants influencing major depression and general cognitive abilities, but little is known about whether the two share any of their genetic aetiology. Here we investigate shared genomic architectures between major depression (MD) and general intelligence (INT) with the MiXeR statistical tool and their overlapping susceptibility loci with conjunctional false discovery rate (conjFDR), which evaluate the level of overlap in genetic variants and improve the power for gene discovery between two phenotypes. We analysed GWAS data on MD (n = 480,359) and INT (n = 269,867) to characterize polygenic architecture and identify genetic loci shared between these phenotypes. Despite non-significant genetic correlation (rg = -0.0148, P = 0.50), we observed large polygenic overlap and identified 92 loci shared between MD and INT at conjFDR < 0.05. Among the shared loci, 69 and 64 are new for MD and INT, respectively. Our study demonstrates polygenic overlap between these phenotypes with a balanced mixture of effect.
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25
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Paternoster V, Edhager AV, Qvist P, Donskov JG, Shliaha P, Jensen ON, Mors O, Nielsen AL, Børglum AD, Palmfeldt J, Christensen JH. Inactivation of the Schizophrenia-associated BRD1 gene in Brain Causes Failure-to-thrive, Seizure Susceptibility and Abnormal Histone H3 Acetylation and N-tail Clipping. Mol Neurobiol 2021; 58:4495-4505. [PMID: 34056693 DOI: 10.1007/s12035-021-02432-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 05/14/2021] [Indexed: 10/21/2022]
Abstract
Genetic studies have repeatedly shown that the Bromodomain containing 1 gene, BRD1, is involved in determining mental health, and the importance of the BRD1 protein for normal brain function has been studied in both cell models and constitutive haploinsufficient Brd1+/- mice. Homozygosity for inactivated Brd1 alleles is lethal during embryonic development in mice. In order to further characterize the molecular functions of BRD1 in the brain, we have developed a novel Brd1 knockout mouse model (Brd1-/-) with bi-allelic conditional inactivation of Brd1 in the central nervous system. Brd1-/- mice were viable but smaller and with reduced muscle strength. They showed reduced exploratory behavior and increased sensitivity to pentylenetetrazole-induced seizures supporting the previously described GABAergic dysfunction in constitutive Brd1+/- mice. Because BRD1 takes part in protein complexes with histone binding and modifying functions, we investigated the effect of BRD1 depletion on the global histone modification pattern in mouse brain by mass spectrometry. We found decreased levels of histone H3 acetylation (H3K9ac, H3K14ac, and H3K18ac) and increased N-tail clipping in consequence of BRD1 depletion. Collectively, the presented results support that BRD1 controls gene expression at the epigenetic level by regulating histone H3 proteoforms in the brain.
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Affiliation(s)
- Veerle Paternoster
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark.,Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark.,Centre for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark
| | - Anders Valdemar Edhager
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Research Unit for Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Per Qvist
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark.,Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark.,Centre for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark
| | - Julie Grinderslev Donskov
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark.,Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark.,Centre for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark
| | - Pavel Shliaha
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Ole Nørregaard Jensen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Ole Mors
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.,Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark.,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Psychosis Research Unit, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Anders Lade Nielsen
- Department of Biomedicine, Aarhus University, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
| | - Anders Dupont Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark.,Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark.,Centre for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark
| | - Johan Palmfeldt
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Research Unit for Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Jane Hvarregaard Christensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark. .,Department of Biomedicine, Aarhus University, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark. .,Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark. .,Centre for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark.
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26
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Liley J, Wallace C. Accurate error control in high-dimensional association testing using conditional false discovery rates. Biom J 2021; 63:1096-1130. [PMID: 33682201 PMCID: PMC7612315 DOI: 10.1002/bimj.201900254] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Revised: 12/05/2020] [Accepted: 12/30/2020] [Indexed: 01/13/2023]
Abstract
High-dimensional hypothesis testing is ubiquitous in the biomedical sciences, and informative covariates may be employed to improve power. The conditional false discovery rate (cFDR) is a widely used approach suited to the setting where the covariate is a set of p-values for the equivalent hypotheses for a second trait. Although related to the Benjamini–Hochberg procedure, it does not permit any easy control of type-1 error rate and existing methods are over-conservative. We propose a newmethod for type-1 error rate control based on identifyingmappings from the unit square to the unit interval defined by the estimated cFDR and splitting observations so that each map is independent of the observations it is used to test. We also propose an adjustment to the existing cFDR estimator which further improves power. We show by simulation that the new method more than doubles potential improvement in power over unconditional analyses compared to existing methods. We demonstrate our method on transcriptome-wide association studies and show that the method can be used in an iterative way, enabling the use of multiple covariates successively. Our methods substantially improve the power and applicability of cFDR analysis.
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Affiliation(s)
- James Liley
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.,Department of Medicine, Addenbrookes Hospital, University of Cambridge, Cambridge, UK
| | - Chris Wallace
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.,Department of Medicine, Addenbrookes Hospital, University of Cambridge, Cambridge, UK.,Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
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27
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Shadrin AA, Mucha S, Ellinghaus D, Makarious MB, Blauwendraat C, Sreelatha AAK, Heras-Garvin A, Ding J, Hammer M, Foubert-Samier A, Meissner WG, Rascol O, Pavy-Le Traon A, Frei O, O'Connell KS, Bahrami S, Schreiber S, Lieb W, Müller-Nurasyid M, Schminke U, Homuth G, Schmidt CO, Nöthen MM, Hoffmann P, Gieger C, Wenning G, Gibbs JR, Franke A, Hardy J, Stefanova N, Gasser T, Singleton A, Houlden H, Scholz SW, Andreassen OA, Sharma M. Shared Genetics of Multiple System Atrophy and Inflammatory Bowel Disease. Mov Disord 2020; 36:449-459. [PMID: 33107653 PMCID: PMC8985479 DOI: 10.1002/mds.28338] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 09/01/2020] [Accepted: 09/21/2020] [Indexed: 11/22/2022] Open
Abstract
Background: Multiple system atrophy (MSA) is a rare neurodegenerative disease characterized by intracellular accumulations of α-synuclein and nerve cell loss in striatonigral and olivopontocerebellar structures. Epidemiological and clinical studies have reported potential involvement of autoimmune mechanisms in MSA pathogenesis. However, genetic etiology of this interaction remains unknown. We aimed to investigate genetic overlap between MSA and 7 autoimmune diseases and to identify shared genetic loci. Methods: Genome-wide association study summary statistics of MSA and 7 autoimmune diseases were combined in cross-trait conjunctional false discovery rate analysis to explore overlapping genetic background. Expression of selected candidate genes was compared in transgenic MSA mice and wild-type mice. Genetic variability of candidate genes was further investigated using independent whole-exome genotyping data from large cohorts of MSA and autoimmune disease patients and healthy controls. Results: We observed substantial polygenic overlap between MSA and inflammatory bowel disease and identified 3 shared genetic loci with leading variants upstream of the DENND1B and RSP04 genes, and in intron of the C7 gene. Further, the C7 gene showed significantly dysregulated expression in the degenerating midbrain of transgenic MSA mice compared with wild-type mice and had elevated burden of protein-coding variants in independent MSA and inflammatory bowel disease cohorts. Conclusion: Our study provides evidence of shared genetic etiology between MSA and inflammatory bowel disease with an important role of the C7 gene in both phenotypes, with the implication of immune and gut dysfunction in MSA pathophysiology.
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Affiliation(s)
- Alexey A Shadrin
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Sören Mucha
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Mary B Makarious
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and, Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Ashwin A K Sreelatha
- Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Applied Biometry, University of Tübingen, Tübingen, Germany
| | | | - Jinhui Ding
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Monia Hammer
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Alexandra Foubert-Samier
- Service de Neurologie, CRMR Atrophie Multisystématisée, CHU Bordeaux, Bordeaux, France.,Inserm, UMR1219, Bordeaux Population Health Research Center, Bordeaux University, ISPED, Bordeaux, France
| | - Wassilios G Meissner
- Service de Neurologie, CRMR Atrophie Multisystématisée, CHU Bordeaux, Bordeaux, France.,Univ. de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, CNRS, Bordeaux, France
| | - Olivier Rascol
- Centre de Reference Maladie Rare Atrophie MultiSystématisée, Centre d'Investigation, Clinique CIC 1436, Services de Pharmacologie Clinique et Neurosciences, NeuroToul COEN Center, Toulouse, France.,Centre Hospitalo-Universitaire de Toulouse, 3, INSERM, Toulouse, France
| | - Anne Pavy-Le Traon
- Neurology Department, French Reference Centre for MSA, University Hospital of Toulouse and INSERM U 1048, Institute of Cardiovascular and Metabolic Diseases, Toulouse, France
| | - Oleksandr Frei
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kevin S O'Connell
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Shahram Bahrami
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.,First Medical Department, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank PopGen, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany.,Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Ulf Schminke
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - Carsten O Schmidt
- Institute for Community Medicine, Study of Health in Pomerania/KEF, University Medicine Greifswald, Greifswald, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Gregor Wenning
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - J Raphael Gibbs
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - John Hardy
- Rita Lila Weston Institute, University College London, London, UK
| | - Nadia Stefanova
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Thomas Gasser
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Andrew Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Henry Houlden
- Rita Lila Weston Institute, University College London, London, UK
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and, Stroke, National Institutes of Health, Bethesda, Maryland, USA.,Department of Neurology, Johns Hopkins University Medical Center, Baltimore, Maryland, USA
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Manu Sharma
- Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Applied Biometry, University of Tübingen, Tübingen, Germany
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28
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Rajkumar AP, Qvist P, Donskov JG, Lazarus R, Pallesen J, Nava N, Winther G, Liebenberg N, Cour SHL, Paternoster V, Fryland T, Palmfeldt J, Fejgin K, Mørk A, Nyegaard M, Pakkenberg B, Didriksen M, Nyengaard JR, Wegener G, Mors O, Christensen JH, Børglum AD. Reduced Brd1 expression leads to reversible depression-like behaviors and gene-expression changes in female mice. Transl Psychiatry 2020; 10:239. [PMID: 32681022 PMCID: PMC7367888 DOI: 10.1038/s41398-020-00914-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 06/20/2020] [Accepted: 06/30/2020] [Indexed: 12/30/2022] Open
Abstract
The schizophrenia-associated gene, BRD1, encodes an epigenetic regulator in which chromatin interactome is enriched with genes implicated in mental health. Alterations in histone modifications and epigenetic regulation contribute to brain transcriptomic changes in affective disorders and preclinical data supports a role for BRD1 in psychopathology. However, the implication of BRD1 on affective pathology remains poorly understood. In this study, we assess affective behaviors and associated neurobiology in Brd1+/- mice along with their responses to Fluoxetine and Imipramine. This involves behavioral, neurostructural, and neurochemical characterizations along with regional cerebral gene expression profiling combined with integrative functional genomic analyses. We report behavioral changes in female Brd1+/- mice with translational value to depressive symptomatology that can be alleviated by the administration of antidepressant medications. Behavioral changes are accompanied by altered brain morphometry and imbalances in monoaminergic systems. In accordance, gene expression changes across brain tissues reveal altered neurotransmitter signaling and cluster in functional pathways associated with depression including 'Adrenergic-, GPCR-, cAMP-, and CREB/CREM-signaling'. Integrative gene expression analysis specifically links changes in amygdaloid intracellular signaling activity to the behavioral treatment response in Brd1+/- mice. Collectively, our study highlights the importance of BRD1 as a modulator of affective pathology and adds to our understanding of the molecular mechanisms underlying affective disorders and their treatment response.
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Affiliation(s)
- Anto P. Rajkumar
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark ,grid.4563.40000 0004 1936 8868Division of Psychiatry and Applied Psychology, University of Nottingham, Nottingham, UK ,grid.13097.3c0000 0001 2322 6764Department of Old Age Psychiatry, Institute of Psychiatry, Psychology, & Neuroscience, King’s College London, London, UK
| | - Per Qvist
- IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. .,Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark. .,Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark. .,Synaptic Transmission, H. Lundbeck A/S, Copenhagen, Denmark.
| | - Julie G. Donskov
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Ross Lazarus
- grid.1051.50000 0000 9760 5620Computational Biology, Baker IDI Heart and Diabetes institute, Melbourne, VIC Australia
| | - Jonatan Pallesen
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Nicoletta Nava
- grid.154185.c0000 0004 0512 597XTranslational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Core Centre for Molecular Morphology, Section for Stereology and Microscopy, Department of Clinical Medicine, Centre for Stochastic Geometry and Advanced Bioimaging, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Gudrun Winther
- grid.154185.c0000 0004 0512 597XTranslational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Nico Liebenberg
- grid.154185.c0000 0004 0512 597XTranslational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Sanne H. la Cour
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Veerle Paternoster
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Tue Fryland
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Johan Palmfeldt
- grid.154185.c0000 0004 0512 597XResearch Unit for Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Kim Fejgin
- grid.424580.f0000 0004 0476 7612Synaptic Transmission, H. Lundbeck A/S, Copenhagen, Denmark
| | - Arne Mørk
- grid.424580.f0000 0004 0476 7612Synaptic Transmission, H. Lundbeck A/S, Copenhagen, Denmark
| | - Mette Nyegaard
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Bente Pakkenberg
- grid.411702.10000 0000 9350 8874Research Laboratory for Stereology and Neuroscience, Bispebjerg University Hospital, Copenhagen, Denmark
| | - Michael Didriksen
- grid.424580.f0000 0004 0476 7612Synaptic Transmission, H. Lundbeck A/S, Copenhagen, Denmark
| | - Jens R. Nyengaard
- grid.7048.b0000 0001 1956 2722Core Centre for Molecular Morphology, Section for Stereology and Microscopy, Department of Clinical Medicine, Centre for Stochastic Geometry and Advanced Bioimaging, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Gregers Wegener
- grid.154185.c0000 0004 0512 597XTranslational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Ole Mors
- grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark ,grid.154185.c0000 0004 0512 597XPsychosis Research Unit, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Jane H. Christensen
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
| | - Anders D. Børglum
- grid.452548.a0000 0000 9817 5300IPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Department of Biomedicine and Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center for Genomics and Personalized Medicine, Aarhus University, Aarhus, Denmark
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O'Connell KS, Shadrin A, Smeland OB, Bahrami S, Frei O, Bettella F, Krull F, Fan CC, Askeland RB, Knudsen GPS, Halmøy A, Steen NE, Ueland T, Walters GB, Davíðsdóttir K, Haraldsdóttir GS, Guðmundsson ÓÓ, Stefánsson H, Reichborn-Kjennerud T, Haavik J, Dale AM, Stefánsson K, Djurovic S, Andreassen OA. Identification of Genetic Loci Shared Between Attention-Deficit/Hyperactivity Disorder, Intelligence, and Educational Attainment. Biol Psychiatry 2020; 87:1052-1062. [PMID: 32061372 PMCID: PMC7255939 DOI: 10.1016/j.biopsych.2019.11.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 11/15/2019] [Accepted: 11/19/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is consistently associated with lower levels of educational attainment. A recent large genome-wide association study identified common gene variants associated with ADHD, but most of the genetic architecture remains unknown. METHODS We analyzed independent genome-wide association study summary statistics for ADHD (19,099 cases and 34,194 controls), educational attainment (N = 842,499), and general intelligence (N = 269,867) using a conditional/conjunctional false discovery rate (FDR) statistical framework that increases power of discovery by conditioning the FDR on overlapping associations. The genetic variants identified were characterized in terms of function, expression, and biological processes. RESULTS We identified 58 linkage disequilibrium-independent ADHD-associated loci (conditional FDR < 0.01), of which 30 were shared between ADHD and educational attainment or general intelligence (conjunctional FDR < 0.01) and 46 were novel risk loci for ADHD. CONCLUSIONS These results expand on previous genetic and epidemiological studies and support the hypothesis of a shared genetic basis between these phenotypes. Although the clinical utility of the identified loci remains to be determined, they can be used as resources to guide future studies aiming to disentangle the complex etiologies of ADHD, educational attainment, and general intelligence.
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Affiliation(s)
- Kevin S O'Connell
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
| | - Alexey Shadrin
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Shahram Bahrami
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Florian Krull
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Chun C Fan
- Department of Radiology, University of California, San Diego, La Jolla, California; Department of Cognitive Science, University of California, San Diego, La Jolla, California
| | - Ragna B Askeland
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Gun Peggy S Knudsen
- Division of Health Data and Digitalisation, Norwegian Institute of Public Health, Oslo, Norway
| | - Anne Halmøy
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Nils Eiel Steen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Torill Ueland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - G Bragi Walters
- deCODE Genetics/Amgen, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Katrín Davíðsdóttir
- The Centre for Child Development and Behaviour, Capital Area Primary Health Care, Reykjavik, Iceland
| | - Gyða S Haraldsdóttir
- The Centre for Child Development and Behaviour, Capital Area Primary Health Care, Reykjavik, Iceland
| | - Ólafur Ó Guðmundsson
- deCODE Genetics/Amgen, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland; Department of Child and Adolescent Psychiatry, National University Hospital, Reykjavik, Iceland
| | | | - Ted Reichborn-Kjennerud
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Jan Haavik
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway; Department of Biomedicine, University of Bergen, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, California; Department of Psychiatry, University of California, San Diego, La Jolla, California; Department of Neurosciences, University of California, San Diego, La Jolla, California; Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, California
| | - Kári Stefánsson
- deCODE Genetics/Amgen, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Srdjan Djurovic
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, University of Bergen, Bergen, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
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30
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van der Meer D, Frei O, Kaufmann T, Chen CH, Thompson WK, O'Connell KS, Monereo Sánchez J, Linden DEJ, Westlye LT, Dale AM, Andreassen OA. Quantifying the Polygenic Architecture of the Human Cerebral Cortex: Extensive Genetic Overlap between Cortical Thickness and Surface Area. Cereb Cortex 2020; 30:5597-5603. [PMID: 32483632 PMCID: PMC7472200 DOI: 10.1093/cercor/bhaa146] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 04/20/2020] [Accepted: 05/10/2020] [Indexed: 12/13/2022] Open
Abstract
The thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remain unknown. Our ability to identify causal genetic variants can be improved by employing brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, that is, lower polygenicity and higher discoverability. Using Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area, as well as the polygenicity and discoverability of regional measures. We made use of UK Biobank data from 30 880 healthy White European individuals (mean age 64.3, standard deviation 7.5, 52.1% female). We found large genetic overlap between total surface area and mean thickness, sharing 4016 out of 7941 causal variants. Regional surface area was more discoverable (P = 2.6 × 10−6) and less polygenic (P = 0.004) than regional thickness measures. These findings may serve as a roadmap for improved future GWAS studies; knowledge of which measures are most discoverable may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.
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Affiliation(s)
- Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Chi-Hua Chen
- Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA 92037, USA
| | - Wesley K Thompson
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Family Medicine and Public Health, University of California at San Diego, La Jolla, CA 92037, USA
| | - Kevin S O'Connell
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jennifer Monereo Sánchez
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - David E J Linden
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA 92037, USA
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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31
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van der Meer D, Rokicki J, Kaufmann T, Córdova-Palomera A, Moberget T, Alnæs D, Bettella F, Frei O, Doan NT, Sønderby IE, Smeland OB, Agartz I, Bertolino A, Bralten J, Brandt CL, Buitelaar JK, Djurovic S, van Donkelaar M, Dørum ES, Espeseth T, Faraone SV, Fernández G, Fisher SE, Franke B, Haatveit B, Hartman CA, Hoekstra PJ, Håberg AK, Jönsson EG, Kolskår KK, Le Hellard S, Lund MJ, Lundervold AJ, Lundervold A, Melle I, Monereo Sánchez J, Norbom LC, Nordvik JE, Nyberg L, Oosterlaan J, Papalino M, Papassotiropoulos A, Pergola G, de Quervain DJF, Richard G, Sanders AM, Selvaggi P, Shumskaya E, Steen VM, Tønnesen S, Ulrichsen KM, Zwiers MP, Andreassen OA, Westlye LT. Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes. Mol Psychiatry 2020; 25:3053-3065. [PMID: 30279459 PMCID: PMC6445783 DOI: 10.1038/s41380-018-0262-7] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Revised: 08/09/2018] [Accepted: 09/06/2018] [Indexed: 11/09/2022]
Abstract
The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10-16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.
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Affiliation(s)
- Dennis van der Meer
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Jaroslav Rokicki
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aldo Córdova-Palomera
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.168010.e0000000419368956Department of Pediatrics, Stanford University School of Medicine, Stanford University, Stanford, USA
| | - Torgeir Moberget
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Francesco Bettella
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nhat Trung Doan
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ida E. Sønderby
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B. Smeland
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Alessandro Bertolino
- grid.7644.10000 0001 0120 3326Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy ,Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Janita Bralten
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Nijmegen, Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Christine L. Brandt
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jan K. Buitelaar
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Srdjan Djurovic
- grid.55325.340000 0004 0389 8485Department of Medical Genetics, Oslo University Hospital, Oslo, Norway ,grid.7914.b0000 0004 1936 7443NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Marjolein van Donkelaar
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Nijmegen, Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Erlend S. Dørum
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway ,grid.416731.60000 0004 0612 1014Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Thomas Espeseth
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway
| | - Stephen V. Faraone
- grid.411023.50000 0000 9159 4457Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY USA
| | - Guillén Fernández
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Simon E. Fisher
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands ,grid.419550.c0000 0004 0501 3839Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
| | - Barbara Franke
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Nijmegen, Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Beathe Haatveit
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway
| | - Catharina A. Hartman
- grid.4494.d0000 0000 9558 4598University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation, Groningen, The Netherlands
| | - Pieter J. Hoekstra
- grid.4494.d0000 0000 9558 4598University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, Netherlands
| | - Asta K. Håberg
- grid.5947.f0000 0001 1516 2393Department of Neuromedicine and Movement Science, NTNU – Norwegian University of Science and Technology, Trondheim, Norway ,grid.52522.320000 0004 0627 3560Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Erik G. Jönsson
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.4714.60000 0004 1937 0626Centre for Psychiatric Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Knut K. Kolskår
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway ,grid.416731.60000 0004 0612 1014Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Stephanie Le Hellard
- grid.7914.b0000 0004 1936 7443NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway ,grid.412008.f0000 0000 9753 1393Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Martina J. Lund
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Astri J. Lundervold
- grid.7914.b0000 0004 1936 7443Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Arvid Lundervold
- grid.7914.b0000 0004 1936 7443Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Ingrid Melle
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jennifer Monereo Sánchez
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Linn C. Norbom
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway
| | - Jan E. Nordvik
- grid.416731.60000 0004 0612 1014Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Lars Nyberg
- grid.12650.300000 0001 1034 3451Departments of Radiation Sciences and Integrative Medical Biology, Umeå Center for Functional Brain Imaging (UFB), Umeå University, Umeå, Sweden
| | - Jaap Oosterlaan
- Amsterdam UMC, University of Amsterdam & Vrije Universiteit Amsterdam, Emma Neuroscience Group at Emma Children’s Hospital, department of Pediatrics, Amsterdam Reproduction & Development, Amsterdam, The Netherlands
| | - Marco Papalino
- grid.7644.10000 0001 0120 3326Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Andreas Papassotiropoulos
- grid.6612.30000 0004 1937 0642Division of Molecular Neuroscience, Department of Psychology, University of Basel, Basel, Switzerland ,grid.6612.30000 0004 1937 0642Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, Basel, Switzerland ,grid.6612.30000 0004 1937 0642Life Sciences Training Facility, Department Biozentrum, University of Basel, Basel, Switzerland
| | - Giulio Pergola
- grid.7644.10000 0001 0120 3326Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Dominique J. F. de Quervain
- grid.6612.30000 0004 1937 0642Division of Cognitive Neuroscience, Department of Psychology, University of Basel, Basel, Switzerland
| | - Geneviève Richard
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway ,grid.416731.60000 0004 0612 1014Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Anne-Marthe Sanders
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway ,grid.416731.60000 0004 0612 1014Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Pierluigi Selvaggi
- grid.7644.10000 0001 0120 3326Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy ,grid.13097.3c0000 0001 2322 6764Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Elena Shumskaya
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Nijmegen, Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Vidar M. Steen
- grid.7914.b0000 0004 1936 7443NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway ,grid.412008.f0000 0000 9753 1393Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Siren Tønnesen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kristine M. Ulrichsen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway ,grid.416731.60000 0004 0612 1014Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Marcel P. Zwiers
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway
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Duan J, Sanders AR, Gejman PV. From Schizophrenia Genetics to Disease Biology: Harnessing New Concepts and Technologies. JOURNAL OF PSYCHIATRY AND BRAIN SCIENCE 2019; 4:e190014. [PMID: 31555746 PMCID: PMC6760308 DOI: 10.20900/jpbs.20190014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Schizophrenia (SZ) is a severe mental disorder afflicting around 1% of the population. It is highly heritable but with complex genetics. Recent research has unraveled a plethora of risk loci for SZ. Accordingly, our conceptual understanding of SZ genetics has been rapidly evolving, from oligogenic models towards polygenic or even omnigenic models. A pressing challenge to the field, however, is the translation of the many genetic findings of SZ into disease biology insights leading to more effective treatments. Bridging this gap requires the integration of genetic findings and functional genomics using appropriate cellular models. Harnessing new technologies, such as the development of human induced pluripotent stem cells (hiPSC) and the CRISPR/Cas-based genome/epigenome editing approach are expected to change our understanding of SZ disease biology to a fundamentally higher level. Here, we discuss some new developments.
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Affiliation(s)
- Jubao Duan
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL 60637, USA
| | - Alan R. Sanders
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL 60637, USA
| | - Pablo V. Gejman
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL 60637, USA
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Smeland OB, Frei O, Shadrin A, O'Connell K, Fan CC, Bahrami S, Holland D, Djurovic S, Thompson WK, Dale AM, Andreassen OA. Discovery of shared genomic loci using the conditional false discovery rate approach. Hum Genet 2019; 139:85-94. [PMID: 31520123 DOI: 10.1007/s00439-019-02060-2] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 08/08/2019] [Indexed: 02/07/2023]
Abstract
In recent years, genome-wide association study (GWAS) sample sizes have become larger, the statistical power has improved and thousands of trait-associated variants have been uncovered, offering new insights into the genetic etiology of complex human traits and disorders. However, a large fraction of the polygenic architecture underlying most complex phenotypes still remains undetected. We here review the conditional false discovery rate (condFDR) method, a model-free strategy for analysis of GWAS summary data, which has improved yield of existing GWAS and provided novel findings of genetic overlap between a wide range of complex human phenotypes, including psychiatric, cardiovascular, and neurological disorders, as well as psychological and cognitive traits. The condFDR method was inspired by Empirical Bayes approaches and leverages auxiliary genetic information to improve statistical power for discovery of single-nucleotide polymorphisms (SNPs). The cross-trait condFDR strategy analyses separate GWAS data, and leverages overlapping SNP associations, i.e., cross-trait enrichment, to increase discovery of trait-associated SNPs. The extension of the condFDR approach to conjunctional FDR (conjFDR) identifies shared genomic loci between two phenotypes. The conjFDR approach allows for detection of shared genomic associations irrespective of the genetic correlation between the phenotypes, often revealing a mixture of antagonistic and agonistic directional effects among the shared loci. This review provides a methodological comparison between condFDR and other relevant cross-trait analytical tools and demonstrates how condFDR analysis may provide novel insights into the genetic relationship between complex phenotypes.
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Affiliation(s)
- Olav B Smeland
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Kevin O'Connell
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Chun-Chieh Fan
- Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA
| | - Shahram Bahrami
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Dominic Holland
- Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Wesley K Thompson
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, 92093, USA
| | - Anders M Dale
- Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
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Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer's disease. Acta Neuropathol 2019; 137:209-226. [PMID: 30413934 PMCID: PMC6358498 DOI: 10.1007/s00401-018-1928-6] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Revised: 10/28/2018] [Accepted: 10/28/2018] [Indexed: 01/01/2023]
Abstract
Cardiovascular (CV)- and lifestyle-associated risk factors (RFs) are increasingly recognized as important for Alzheimer's disease (AD) pathogenesis. Beyond the ε4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV-associated genes also increase risk for AD. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV-associated RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), triglycerides (TG), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TG, TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 90 SNPs on 19 different chromosomes that were jointly associated with AD and CV-associated outcomes. In meta-analyses across three independent cohorts, we found four novel loci within MBLAC1 (chromosome 7, meta-p = 1.44 × 10-9), MINK1 (chromosome 17, meta-p = 1.98 × 10-7) and two chromosome 11 SNPs within the MTCH2/SPI1 region (closest gene = DDB2, meta-p = 7.01 × 10-7 and closest gene = MYBPC3, meta-p = 5.62 × 10-8). In a large 'AD-by-proxy' cohort from the UK Biobank, we replicated three of the four novel AD/CV pleiotropic SNPs, namely variants within MINK1, MBLAC1, and DDB2. Expression of MBLAC1, SPI1, MINK1 and DDB2 was differentially altered within postmortem AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid-associated RFs. We pinpoint a subset of cardiovascular-associated genes that strongly increase the risk for AD. Our collective findings support a disease model in which cardiovascular biology is integral to the development of clinical AD in a subset of individuals.
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Paternoster V, Svanborg M, Edhager AV, Rajkumar AP, Eickhardt EA, Pallesen J, Grove J, Qvist P, Fryland T, Wegener G, Nyengaard JR, Mors O, Palmfeldt J, Børglum AD, Christensen JH. Brain proteome changes in female Brd1 +/- mice unmask dendritic spine pathology and show enrichment for schizophrenia risk. Neurobiol Dis 2018; 124:479-488. [PMID: 30590179 DOI: 10.1016/j.nbd.2018.12.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Revised: 11/23/2018] [Accepted: 12/18/2018] [Indexed: 12/12/2022] Open
Abstract
Genetic and molecular studies have implicated the Bromodomain containing 1 (BRD1) gene in the pathogenesis of schizophrenia and bipolar disorder. Accordingly, mice heterozygous for a targeted deletion of Brd1 (Brd1+/- mice) show behavioral phenotypes with broad translational relevance to psychiatric disorders. BRD1 encodes a scaffold protein that affects the expression of many genes through modulation of histone acetylation. BRD1 target genes have been identified in cell lines; however the impact of reduced Brd1 levels on the brain proteome is largely unknown. In this study, we applied label-based quantitative mass spectrometry to profile the frontal cortex, hippocampus and striatum proteome and synaptosomal proteome of female Brd1+/- mice. We successfully quantified between 1537 and 2196 proteins and show widespread changes in protein abundancies and compartmentalization. By integrative analysis of human genetic data, we find that the differentially abundant proteins in frontal cortex and hippocampus are enriched for schizophrenia risk further linking the actions of BRD1 to psychiatric disorders. Affected proteins were further enriched for proteins involved in processes known to influence neuronal and dendritic spine morphology e.g. regulation of cytoskeleton dynamics and mitochondrial function. Directly prompted in these findings, we investigated dendritic spine morphology of pyramidal neurons in anterior cingulate cortex and found them significantly altered, including reduced size of small dendritic spines and decreased number of the mature mushroom type. Collectively, our study describes known as well as new mechanisms related to BRD1 dysfunction and its role in psychiatric disorders, and provides evidence for the molecular and cellular dysfunctions underlying altered neurosignalling and cognition in Brd1+/- mice.
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Affiliation(s)
- Veerle Paternoster
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark; Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark.
| | - Maria Svanborg
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | | | - Anto P Rajkumar
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark; Mental Health of Older Adults and Dementia Clinical Academic Group, South London and Maudsley NHS Foundation Trust, London, UK; Department of Old Age Psychiatry, Psychology, & Neuroscience, King's College London, Institute of Psychiatry, London, UK
| | - Esben Ahlburg Eickhardt
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Jonatan Pallesen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark; Bioinformatics Research Centre, BiRC, Aarhus University, Aarhus, Denmark
| | - Per Qvist
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Tue Fryland
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Gregers Wegener
- Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark
| | - Jens Randel Nyengaard
- Stereology and Electron Microscopy Laboratory, Centre for Stochastic Geometry and Advanced Bioimaging, Aarhus University Hospital, Aarhus, Denmark
| | - Ole Mors
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark
| | - Johan Palmfeldt
- Research Unit for Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Anders Dupont Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Jane Hvarregaard Christensen
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark; Department of Biomedicine, Aarhus University, Aarhus, Denmark
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36
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Qvist P, Eskildsen SF, Hansen B, Baragji M, Ringgaard S, Roovers J, Paternoster V, Molgaard S, Corydon TJ, Stødkilde-Jørgensen H, Glerup S, Mors O, Wegener G, Nyengaard JR, Børglum AD, Christensen JH. Brain volumetric alterations accompanied with loss of striatal medium-sized spiny neurons and cortical parvalbumin expressing interneurons in Brd1 +/- mice. Sci Rep 2018; 8:16486. [PMID: 30405140 PMCID: PMC6220279 DOI: 10.1038/s41598-018-34729-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 10/22/2018] [Indexed: 12/17/2022] Open
Abstract
Schizophrenia is a common and severe mental disorder arising from complex gene-environment interactions affecting brain development and functioning. While a consensus on the neuroanatomical correlates of schizophrenia is emerging, much of its fundamental pathobiology remains unknown. In this study, we explore brain morphometry in mice with genetic susceptibility and phenotypic relevance to schizophrenia (Brd1+/− mice) using postmortem 3D MR imaging coupled with histology, immunostaining and regional mRNA marker analysis. In agreement with recent large-scale schizophrenia neuroimaging studies, Brd1+/− mice displayed subcortical abnormalities, including volumetric reductions of amygdala and striatum. Interestingly, we demonstrate that structural alteration in striatum correlates with a general loss of striatal neurons, differentially impacting subpopulations of medium-sized spiny neurons and thus potentially striatal output. Akin to parvalbumin interneuron dysfunction in patients, a decline in parvalbumin expression was noted in the developing cortex of Brd1+/− mice, mainly driven by neuronal loss within or near cortical layer V, which is rich in corticostriatal projection neurons. Collectively, our study highlights the translational value of the Brd1+/− mouse as a pre-clinical tool for schizophrenia research and provides novel insight into its developmental, structural, and cellular pathology.
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Affiliation(s)
- Per Qvist
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. .,Department of Biomedicine, Aarhus University, Aarhus, Denmark. .,iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark.
| | - Simon F Eskildsen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Brian Hansen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | | | - Steffen Ringgaard
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Jolien Roovers
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Veerle Paternoster
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Aarhus, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
| | - Simon Molgaard
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Thomas Juhl Corydon
- Department of Biomedicine, Aarhus University, Aarhus, Denmark. .,Department of Ophthalmology, Aarhus University Hospital, Aarhus, Denmark.
| | | | - Simon Glerup
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Ole Mors
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark.,Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Gregers Wegener
- Translational Neuropsychiatry Unit, Aarhus University Hospital, Aarhus, Denmark
| | - Jens R Nyengaard
- Core Center for Molecular Morphology, Section for Stereology and Microscopy, Centre for Stochastic Geometry and Advanced Bioimaging, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Anders D Børglum
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Aarhus, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark.,Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Jane H Christensen
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Department of Biomedicine, Aarhus University, Aarhus, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark
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37
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Smeland OB, Andreassen OA. How can genetics help understand the relationship between cognitive dysfunction and schizophrenia? Scand J Psychol 2018; 59:26-31. [PMID: 29356008 DOI: 10.1111/sjop.12407] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 08/14/2017] [Indexed: 01/05/2023]
Abstract
Despite the consistent finding that cognitive dysfunction is a core characteristic of schizophrenia (SCZ), little is known about the underlying pathophysiology. Recent progress in human genetics, driven by large genome-wide association studies (GWAS), has provided new data about the genetic architecture of complex human traits, including cognition and SCZ. Novel analytical tools have provided unprecedented opportunities to leverage the large amount of information from GWAS. Here we review the latest findings related to genetic architecture and risk genes of SCZ and cognitive functions, and recent findings of overlapping genetic factors. The recent GWAS of SCZ implicate over 100 risk gene loci, each with a small effect. A similar genetic architecture seems to be present in cognitive domains, suggesting that these phenotypes are highly polygenic. Further, GWAS have revealed more than 20 gene loci associated with cognitive traits, including intelligence, general cognition (g-factor), reaction time and verbal-numerical reasoning. Several gene loci have been implicated in educational attainment, a proxy measure of cognitive function. Recently, overlapping gene loci were found between education and SCZ, and between SCZ and cognitive traits, suggesting common genetic risk between SCZ and cognitive dysfunction. Mathematical modeling of GWAS of cognition and SCZ indicate that only a fraction of the heritability is identified. The evidence suggests a polygenic architecture for SCZ and cognitive functions, and a large degree of shared genetic risk. This indicates novel molecular genetic mechanisms and strengthens the notion that SCZ is more likely a part of the normal distribution and not a separate entity.
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Affiliation(s)
- Olav B Smeland
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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38
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Rund BR. The research evidence for schizophrenia as a neurodevelopmental disorder. Scand J Psychol 2018; 59:49-58. [PMID: 29356007 DOI: 10.1111/sjop.12414] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 04/26/2017] [Indexed: 01/27/2023]
Abstract
Schizophrenia is a neurodevelopmental disorder that starts very early. In this review we describe the empirical evidence for the neurodevelopmental model. First, by outlining the roots of psychological research that laid the foundation of the model. Thereafter, describing cognitive dysfunction observed in schizophrenia, and the course of cognitive functioning in the illness. Then, research findings that speak for and studies that speak against the view that schizophrenia is a degenerative process is discussed. We find that there is ample evidence that cognitive disturbance is a core element in schizophrenia. However, we have limited understanding of what initiates the abnormal development. This the paper ends with pointing out some of the factors that may trigger the deviant neurocognitive development in schizophrenia.
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Affiliation(s)
- Bjorn Rishovd Rund
- Department of Psychology, University of Oslo, Oslo, Norway.,Vestre Viken Hospital Trust, Drammen, Norway
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39
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Srinivasan S, Bettella F, Frei O, Hill WD, Wang Y, Witoelar A, Schork AJ, Thompson WK, Davies G, Desikan RS, Deary IJ, Melle I, Ueland T, Dale AM, Djurovic S, Smeland OB, Andreassen OA. Enrichment of genetic markers of recent human evolution in educational and cognitive traits. Sci Rep 2018; 8:12585. [PMID: 30135563 PMCID: PMC6105609 DOI: 10.1038/s41598-018-30387-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Accepted: 07/30/2018] [Indexed: 12/13/2022] Open
Abstract
Higher cognitive functions are regarded as one of the main distinctive traits of humans. Evidence for the cognitive evolution of human beings is mainly based on fossil records of an expanding cranium and an increasing complexity of material culture artefacts. However, the molecular genetic factors involved in the evolution are still relatively unexplored. Here, we investigated whether genomic regions that underwent positive selection in humans after divergence from Neanderthals are enriched for genetic association with phenotypes related to cognitive functions. We used genome wide association data from a study of college completion (N = 111,114), one of educational attainment (N = 293,623) and two different studies of general cognitive ability (N = 269,867 and 53,949). We found nominally significant polygenic enrichment of associations with college completion (p = 0.025), educational attainment (p = 0.043) and general cognitive ability (p = 0.015 and 0.025, respectively), suggesting that variants influencing these phenotypes are more prevalent in evolutionarily salient regions. The enrichment remained significant after controlling for other known genetic enrichment factors, and for affiliation to genes highly expressed in the brain. These findings support the notion that phenotypes related to higher order cognitive skills typical of humans have a recent genetic component that originated after the separation of the human and Neanderthal lineages.
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Affiliation(s)
- Saurabh Srinivasan
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Francesco Bettella
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Yunpeng Wang
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Aree Witoelar
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Andrew J Schork
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Wesley K Thompson
- Institute of Biological Psychiatry, Mental Health Center St. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Rahul S Desikan
- Neuroradiology Section, Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, USA
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ingrid Melle
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Torill Ueland
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA
- Center for Human Development, University of California at San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Olav B Smeland
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
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40
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Smeland OB, Wang Y, Frei O, Li W, Hibar DP, Franke B, Bettella F, Witoelar A, Djurovic S, Chen CH, Thompson PM, Dale AM, Andreassen OA. Genetic Overlap Between Schizophrenia and Volumes of Hippocampus, Putamen, and Intracranial Volume Indicates Shared Molecular Genetic Mechanisms. Schizophr Bull 2018; 44:854-864. [PMID: 29136250 PMCID: PMC6007549 DOI: 10.1093/schbul/sbx148] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, we explored whether brain structure volumes and SCZ share genetic risk factors. Using conditional false discovery rate (FDR) analysis, we integrated genome-wide association study (GWAS) data on SCZ (n = 82315) and GWAS data on 7 subcortical brain volumes and ICV (n = 11840). By conditioning the FDR on overlapping associations, this statistical approach increases power to discover genetic loci. To assess the credibility of our approach, we studied the identified loci in larger GWAS samples on ICV (n = 26577) and hippocampal volume (n = 26814). We observed polygenic overlap between SCZ and volumes of hippocampus, putamen, and ICV. Based on conjunctional FDR < 0.05, we identified 2 loci shared between SCZ and ICV implicating genes FOXO3 (rs10457180) and ITIH4 (rs4687658), 2 loci shared between SCZ and hippocampal volume implicating SLC4A10 (rs4664442) and SPATS2L (rs1653290), and 2 loci shared between SCZ and volume of putamen implicating DCC (rs4632195) and DLG2 (rs11233632). The loci shared between SCZ and hippocampal volume or ICV had not reached significance in the primary GWAS on brain phenotypes. Proving our point of increased power, 2 loci did reach genome-wide significance with ICV (rs10457180) and hippocampal volume (rs4664442) in the larger GWAS. Three of the 6 identified loci are novel for SCZ. Altogether, the findings provide new insights into the relationship between SCZ and brain structure volumes, suggesting that their genetic architectures are not independent.
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Affiliation(s)
- Olav B Smeland
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Neurosciences, University of California San Diego, La Jolla, CA,To whom correspondence should be addressed; Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Kirkeveien 166, 0424 Oslo, Norway; tel: +1-858-568-4915, fax: +47-230-273-33, e-mail:
| | - Yunpeng Wang
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Radiology, University of California San Diego, La Jolla, CA,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA
| | - Oleksandr Frei
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Wen Li
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Derrek P Hibar
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands,Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands,Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Francesco Bettella
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Aree Witoelar
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway,NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Chi-Hua Chen
- Department of Radiology, University of California San Diego, La Jolla, CA,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA
| | - Anders M Dale
- Department of Neurosciences, University of California San Diego, La Jolla, CA,Department of Radiology, University of California San Diego, La Jolla, CA,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA,Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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Shadrin AA, Smeland OB, Zayats T, Schork AJ, Frei O, Bettella F, Witoelar A, Li W, Eriksen JA, Krull F, Djurovic S, Faraone SV, Reichborn-Kjennerud T, Thompson WK, Johansson S, Haavik J, Dale AM, Wang Y, Andreassen OA. Novel Loci Associated With Attention-Deficit/Hyperactivity Disorder Are Revealed by Leveraging Polygenic Overlap With Educational Attainment. J Am Acad Child Adolesc Psychiatry 2018; 57:86-95. [PMID: 29413154 PMCID: PMC5806128 DOI: 10.1016/j.jaac.2017.11.013] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Revised: 11/11/2017] [Accepted: 11/21/2017] [Indexed: 01/08/2023]
Abstract
OBJECTIVE Attention-deficit/hyperactivity disorder (ADHD) is a common and highly heritable psychiatric condition. By exploiting the reported relationship between ADHD and educational attainment (EA), we aimed to improve discovery of ADHD-associated genetic variants and to investigate genetic overlap between these phenotypes. METHOD A conditional/conjunctional false discovery rate (condFDR/conjFDR) method was applied to genome-wide association study (GWAS) data on ADHD (2,064 trios, 896 cases, and 2,455 controls) and EA (n=328,917) to identify ADHD-associated loci and loci overlapping between ADHD and EA. Identified single nucleotide polymorphisms (SNPs) were tested for association in an independent population-based study of ADHD symptoms (n=17,666). Genetic correlation between ADHD and EA was estimated using LD score regression and Pearson correlation. RESULTS At levels of condFDR<0.01 and conjFDR<0.05, we identified 5 ADHD-associated loci, 3 of these being shared between ADHD and EA. None of these loci had been identified in the primary ADHD GWAS, demonstrating the increased power provided by the condFDR/conjFDR analysis. Leading SNPs for 4 of 5 identified regions are in introns of protein coding genes (KDM4A, MEF2C, PINK1, RUNX1T1), whereas the remaining one is an intergenic SNP on chromosome 2 at 2p24. Consistent direction of effects in the independent study of ADHD symptoms was shown for 4 of 5 identified loci. A polygenic overlap between ADHD and EA was supported by significant genetic correlation (rg=-0.403, p=7.90×10-8) and >10-fold mutual enrichment of SNPs associated with both traits. CONCLUSION We identified 5 novel loci associated with ADHD and provided evidence for a shared genetic basis between ADHD and EA. These findings could aid understanding of the genetic risk architecture of ADHD and its relation to EA.
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Affiliation(s)
- Alexey A Shadrin
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
| | - Olav B Smeland
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Tetyana Zayats
- K.G. Jebsen Centre for Neuropsychiatric Disorders, University of Bergen, Bergen, Norway
| | - Andrew J Schork
- University of California, San Diego and Institute of Biological Psychiatry, Medical Health Center, Sct. Hans Hospital and University of Copenhagen, Copenhagen, Denmark
| | - Oleksandr Frei
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Francesco Bettella
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Aree Witoelar
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Wen Li
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jon A Eriksen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Florian Krull
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Srdjan Djurovic
- Oslo University Hospital, Oslo, and NORMENT, KG Jebsen Centre for Psychosis Research, University of Bergen
| | - Stephen V Faraone
- KG Jebsen Centre for Neuropsychiatric Disorders, University of Bergen, SUNY Upstate Medical University, Syracuse, New York
| | - Ted Reichborn-Kjennerud
- Division of Mental Health, Norwegian Institute of Public Health, Oslo, and Institute of Clinical Medicine, University of Oslo
| | | | - Stefan Johansson
- K.G. Jebsen Centre for Neuropsychiatric Disorders, University of Bergen, Bergen, Norway; Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Jan Haavik
- K.G. Jebsen Centre for Neuropsychiatric Disorders, University of Bergen, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital
| | - Anders M Dale
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, and University of California, San Diego
| | - Yunpeng Wang
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; University of California, San Diego, La Jolla, CA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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McGrath LM. Two GWASs Are Better Than One: Enhancing Genetic Discovery for Developmental Phenotypes. J Am Acad Child Adolesc Psychiatry 2018; 57:77-79. [PMID: 29413150 PMCID: PMC6178947 DOI: 10.1016/j.jaac.2017.11.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Accepted: 11/28/2017] [Indexed: 11/22/2022]
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Lin E, Lin CH, Lai YL, Huang CH, Huang YJ, Lane HY. Combination of G72 Genetic Variation and G72 Protein Level to Detect Schizophrenia: Machine Learning Approaches. Front Psychiatry 2018; 9:566. [PMID: 30459659 PMCID: PMC6232512 DOI: 10.3389/fpsyt.2018.00566] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 10/18/2018] [Indexed: 11/15/2022] Open
Abstract
The D-amino acid oxidase activator (DAOA, also known as G72) gene is a strong schizophrenia susceptibility gene. Higher G72 protein levels have been implicated in patients with schizophrenia. The current study aimed to differentiate patients with schizophrenia from healthy individuals using G72 single nucleotide polymorphisms (SNPs) and G72 protein levels by leveraging computational artificial intelligence and machine learning tools. A total of 149 subjects with 89 patients with schizophrenia and 60 healthy controls were recruited. Two G72 genotypes (including rs1421292 and rs2391191) and G72 protein levels were measured with the peripheral blood. We utilized three machine learning algorithms (including logistic regression, naive Bayes, and C4.5 decision tree) to build the optimal predictive model for distinguishing schizophrenia patients from healthy controls. The naive Bayes model using two factors, including G72 rs1421292 and G72 protein, appeared to be the best model for disease susceptibility (sensitivity = 0.7969, specificity = 0.9372, area under the receiver operating characteristic curve (AUC) = 0.9356). However, a model integrating G72 rs1421292 only slightly increased the discriminative power than a model with G72 protein alone (sensitivity = 0.7941, specificity = 0.9503, AUC = 0.9324). Among the three models with G72 protein alone, the naive Bayes with G72 protein alone had the best specificity (0.9503), while logistic regression with G72 protein alone was the most sensitive (0.8765). The findings remained similar after adjusting for age and gender. This study suggests that G72 protein alone, without incorporating the two G72 SNPs, may have been suitable enough to identify schizophrenia patients. We also recommend applying both naive Bayes and logistic regression models for the best specificity and sensitivity, respectively. Larger-scale studies are warranted to confirm the findings.
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Affiliation(s)
- Eugene Lin
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, United States.,Department of Biostatistics, University of Washington, Seattle, WA, United States.,Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
| | - Chieh-Hsin Lin
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan.,Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.,School of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yi-Lun Lai
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
| | - Chiung-Hsien Huang
- Department of Medicine Research, China Medical University Hospital, Taichung, Taiwan
| | - Yu-Jhen Huang
- Department of Psychiatry, China Medical University Hospital, Taichung, Taiwan
| | - Hsien-Yuan Lane
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan.,Department of Psychiatry, China Medical University Hospital, Taichung, Taiwan.,Brain Disease Research Center, China Medical University Hospital, Taichung, Taiwan.,Department of Psychology, College of Medical and Health Sciences, Asia University, Taichung, Taiwan
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Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure. Sci Rep 2017; 7:15736. [PMID: 29147026 PMCID: PMC5691156 DOI: 10.1038/s41598-017-15705-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 10/31/2017] [Indexed: 12/21/2022] Open
Abstract
Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5′UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10−8). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen.
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Smeland OB, Frei O, Kauppi K, Hill WD, Li W, Wang Y, Krull F, Bettella F, Eriksen JA, Witoelar A, Davies G, Fan CC, Thompson WK, Lam M, Lencz T, Chen CH, Ueland T, Jönsson EG, Djurovic S, Deary IJ, Dale AM, Andreassen OA. Identification of Genetic Loci Jointly Influencing Schizophrenia Risk and the Cognitive Traits of Verbal-Numerical Reasoning, Reaction Time, and General Cognitive Function. JAMA Psychiatry 2017; 74:1065-1075. [PMID: 28746715 PMCID: PMC5710474 DOI: 10.1001/jamapsychiatry.2017.1986] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
IMPORTANCE Schizophrenia is associated with widespread cognitive impairments. Although cognitive deficits are one of the factors most strongly associated with functional outcome in schizophrenia, current treatment strategies largely fail to ameliorate these impairments. To develop more efficient treatment strategies in patients with schizophrenia, a better understanding of the pathogenesis of these cognitive deficits is needed. Accumulating evidence indicates that genetic risk of schizophrenia may contribute to cognitive dysfunction. OBJECTIVE To identify genomic regions jointly influencing schizophrenia and the cognitive domains of reaction time and verbal-numerical reasoning, as well as general cognitive function, a phenotype that captures the shared variation in performance across cognitive domains. DESIGN, SETTING, AND PARTICIPANTS Combining data from genome-wide association studies from multiple phenotypes using conditional false discovery rate analysis provides increased power to discover genetic variants and could elucidate shared molecular genetic mechanisms. Data from the following genome-wide association studies, published from July 24, 2014, to January 17, 2017, were combined: schizophrenia in the Psychiatric Genomics Consortium cohort (n = 79 757 [cases, 34 486; controls, 45 271]); verbal-numerical reasoning (n = 36 035) and reaction time (n = 111 483) in the UK Biobank cohort; and general cognitive function in CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) (n = 53 949) and COGENT (Cognitive Genomics Consortium) (n = 27 888). MAIN OUTCOMES AND MEASURES Genetic loci identified by conditional false discovery rate analysis. Brain messenger RNA expression and brain expression quantitative trait locus functionality were determined. RESULTS Among the participants in the genome-wide association studies, 21 loci jointly influencing schizophrenia and cognitive traits were identified: 2 loci shared between schizophrenia and verbal-numerical reasoning, 6 loci shared between schizophrenia and reaction time, and 14 loci shared between schizophrenia and general cognitive function. One locus was shared between schizophrenia and 2 cognitive traits and represented the strongest shared signal detected (nearest gene TCF20; chromosome 22q13.2), and was shared between schizophrenia (z score, 5.01; P = 5.53 × 10-7), general cognitive function (z score, -4.43; P = 9.42 × 10-6), and verbal-numerical reasoning (z score, -5.43; P = 5.64 × 10-8). For 18 loci, schizophrenia risk alleles were associated with poorer cognitive performance. The implicated genes are expressed in the developmental and adult human brain. Replicable expression quantitative trait locus functionality was identified for 4 loci in the adult human brain. CONCLUSIONS AND RELEVANCE The discovered loci improve the understanding of the common genetic basis underlying schizophrenia and cognitive function, suggesting novel molecular genetic mechanisms.
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Affiliation(s)
- Olav B. Smeland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Neuroscience, University of California San Diego, La Jolla
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Karolina Kauppi
- Department of Radiology, University of California San Diego, La Jolla,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla,Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - W. David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom,Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Wen Li
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Yunpeng Wang
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Radiology, University of California San Diego, La Jolla,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla
| | - Florian Krull
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jon A. Eriksen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Aree Witoelar
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom,Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Chun C. Fan
- Department of Radiology, University of California San Diego, La Jolla,Department of Cognitive Science, University of California, San Diego, La Jolla
| | - Wesley K. Thompson
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla,Institute of Biological Psychiatry, Roskilde, Denmark
| | - Max Lam
- Institute of Mental Health, Singapore
| | - Todd Lencz
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, New York,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, New York
| | - Chi-Hua Chen
- Department of Radiology, University of California San Diego, La Jolla,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla
| | - Torill Ueland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychology, University of Oslo, Olso, Norway
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway,NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom,Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Anders M. Dale
- Department of Neuroscience, University of California San Diego, La Jolla,Department of Radiology, University of California San Diego, La Jolla,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla,Department of Psychiatry, University of California, San Diego, La Jolla
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
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Javidfar B, Park R, Kassim BS, Bicks LK, Akbarian S. The epigenomics of schizophrenia, in the mouse. Am J Med Genet B Neuropsychiatr Genet 2017; 174:631-640. [PMID: 28699694 PMCID: PMC5573750 DOI: 10.1002/ajmg.b.32566] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2017] [Revised: 05/04/2017] [Accepted: 06/12/2017] [Indexed: 01/02/2023]
Abstract
Large-scale consortia including the Psychiatric Genomics Consortium, the Common Minds Consortium, BrainSeq and PsychENCODE, and many other studies taken together provide increasingly detailed insights into the genetic and epigenetic risk architectures of schizophrenia (SCZ) and offer vast amounts of molecular information, but with largely unexplored therapeutic potential. Here we discuss how epigenomic studies in human brain could guide animal work to test the impact of disease-associated alterations in chromatin structure and function on cognition and behavior. For example, transcription factors such as MYOCYTE-SPECIFIC ENHANCER FACTOR 2C (MEF2C), or multiple regulators of the open chromatin mark, methyl-histone H3-lysine 4, are associated with the genetic risk architectures of common psychiatric disease and alterations in chromatin structure and function in diseased brain tissue. Importantly, these molecules also affect cognition and behavior in genetically engineered mice, including virus-mediated expression changes in prefrontal cortex (PFC) and other key nodes in the circuitry underlying psychosis. Therefore, preclinical and small laboratory animal work could target genomic sequences affected by chromatin alterations in SCZ. To this end, in vivo editing of enhancer and other regulatory non-coding DNA by RNA-guided nucleases including CRISPR-Cas, and designer transcription factors, could be expected to deliver pipelines for novel therapeutic approaches aimed at improving cognitive dysfunction and other core symptoms of SCZ.
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Affiliation(s)
| | | | | | - Lucy K. Bicks
- Department of Psychiatry; Friedman Brain Institute; Icahn School of Medicine at Mount Sinai; New York New York
| | - Schahram Akbarian
- Department of Psychiatry; Friedman Brain Institute; Icahn School of Medicine at Mount Sinai; New York New York
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The Schizophrenia-Associated BRD1 Gene Regulates Behavior, Neurotransmission, and Expression of Schizophrenia Risk Enriched Gene Sets in Mice. Biol Psychiatry 2017; 82:62-76. [PMID: 27837920 DOI: 10.1016/j.biopsych.2016.08.037] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Revised: 08/18/2016] [Accepted: 08/29/2016] [Indexed: 11/21/2022]
Abstract
BACKGROUND The schizophrenia-associated BRD1 gene encodes a transcriptional regulator whose comprehensive chromatin interactome is enriched with schizophrenia risk genes. However, the biology underlying the disease association of BRD1 remains speculative. METHODS This study assessed the transcriptional drive of a schizophrenia-associated BRD1 risk variant in vitro. Accordingly, to examine the effects of reduced Brd1 expression, we generated a genetically modified Brd1+/- mouse and subjected it to behavioral, electrophysiological, molecular, and integrative genomic analyses with focus on schizophrenia-relevant parameters. RESULTS Brd1+/- mice displayed cerebral histone H3K14 hypoacetylation and a broad range of behavioral changes with translational relevance to schizophrenia. These behaviors were accompanied by striatal dopamine/serotonin abnormalities and cortical excitation-inhibition imbalances involving loss of parvalbumin immunoreactive interneurons. RNA-sequencing analyses of cortical and striatal micropunches from Brd1+/- and wild-type mice revealed differential expression of genes enriched for schizophrenia risk, including several schizophrenia genome-wide association study risk genes (e.g., calcium channel subunits [Cacna1c and Cacnb2], cholinergic muscarinic receptor 4 [Chrm4)], dopamine receptor D2 [Drd2], and transcription factor 4 [Tcf4]). Integrative analyses further found differentially expressed genes to cluster in functional networks and canonical pathways associated with mental illness and molecular signaling processes (e.g., glutamatergic, monoaminergic, calcium, cyclic adenosine monophosphate [cAMP], dopamine- and cAMP-regulated neuronal phosphoprotein 32 kDa [DARPP-32], and cAMP responsive element binding protein signaling [CREB]). CONCLUSIONS Our study bridges the gap between genetic association and pathogenic effects and yields novel insights into the unfolding molecular changes in the brain of a new schizophrenia model that incorporates genetic risk at three levels: allelic, chromatin interactomic, and brain transcriptomic.
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Steen VM, Skrede S, Polushina T, López M, Andreassen OA, Fernø J, Hellard SL. Genetic evidence for a role of the SREBP transcription system and lipid biosynthesis in schizophrenia and antipsychotic treatment. Eur Neuropsychopharmacol 2017; 27:589-598. [PMID: 27492885 DOI: 10.1016/j.euroneuro.2016.07.011] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Revised: 07/15/2016] [Accepted: 07/19/2016] [Indexed: 12/21/2022]
Abstract
Schizophrenia is a serious psychotic disorder, with disabling symptoms and markedly reduced life expectancy. The onset is usually in late adolescence or early adulthood, which in time overlaps with the maturation of the brain including the myelination process. Interestingly, there seems to be a link between myelin abnormalities and schizophrenia. The oligodendrocyte-derived myelin membranes in the CNS are highly enriched for lipids (cholesterol, phospholipids and glycosphingolipids), thereby pointing at lipid homeostasis as a relevant target for studying the genetics and pathophysiology of schizophrenia. The biosynthesis of fatty acids and cholesterol is regulated by the sterol regulatory element binding protein (SREBP) transcription factors SREBP1 and SREBP2, which are encoded by the SREBF1 and SREBF2 genes on chromosome 17p11.2 and 22q13.2, respectively. Here we review the evidence for the involvement of SREBF1 and SREBF2 as genetic risk factors in schizophrenia and discuss the role of myelination and SREBP-mediated lipid biosynthesis in the etiology, pathophysiology and drug treatment of schizophrenia.
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Affiliation(s)
- Vidar M Steen
- NORMENT, K.G. Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway.
| | - Silje Skrede
- NORMENT, K.G. Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Tatiana Polushina
- NORMENT, K.G. Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Miguel López
- Department of Physiology, CIMUS, University of Santiago de Compostela-Instituto de Investigación Sanitaria, Santiago de Compostela 15782, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Santiago de Compostela 15706, Spain
| | - Ole A Andreassen
- NORMENT, K.G. Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Johan Fernø
- NORMENT, K.G. Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Stephanie Le Hellard
- NORMENT, K.G. Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
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Smeland OB, Wang Y, Lo MT, Li W, Frei O, Witoelar A, Tesli M, Hinds DA, Tung JY, Djurovic S, Chen CH, Dale AM, Andreassen OA. Identification of genetic loci shared between schizophrenia and the Big Five personality traits. Sci Rep 2017; 7:2222. [PMID: 28533504 PMCID: PMC5440373 DOI: 10.1038/s41598-017-02346-3] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Accepted: 04/10/2017] [Indexed: 11/25/2022] Open
Abstract
Schizophrenia is associated with differences in personality traits, and recent studies suggest that personality traits and schizophrenia share a genetic basis. Here we aimed to identify specific genetic loci shared between schizophrenia and the Big Five personality traits using a Bayesian statistical framework. Using summary statistics from genome-wide association studies (GWAS) on personality traits in the 23andMe cohort (n = 59,225) and schizophrenia in the Psychiatric Genomics Consortium cohort (n = 82,315), we evaluated overlap in common genetic variants. The Big Five personality traits neuroticism, extraversion, openness, agreeableness and conscientiousness were measured using a web implementation of the Big Five Inventory. Applying the conditional false discovery rate approach, we increased discovery of genetic loci and identified two loci shared between neuroticism and schizophrenia and six loci shared between openness and schizophrenia. The study provides new insights into the relationship between personality traits and schizophrenia by highlighting genetic loci involved in their common genetic etiology.
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Affiliation(s)
- Olav B Smeland
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.
| | - Yunpeng Wang
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
- Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, United States of America
| | - Min-Tzu Lo
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, United States of America
| | - Wen Li
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Aree Witoelar
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Martin Tesli
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
- Lovisenberg Diakonale Hospital, 0456, Oslo, Norway
| | - David A Hinds
- 23andMe, Inc., Mountain View, CA, 94041, United States of America
| | - Joyce Y Tung
- 23andMe, Inc., Mountain View, CA, 94041, United States of America
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Chi-Hua Chen
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, United States of America
| | - Anders M Dale
- Department of Neurosciences, University of California San Diego, La Jolla, CA, 92093, United States of America
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, United States of America
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.
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Le Hellard S, Wang Y, Witoelar A, Zuber V, Bettella F, Hugdahl K, Espeseth T, Steen VM, Melle I, Desikan R, Schork AJ, Thompson WK, Dale AM, Djurovic S, Andreassen OA. Identification of Gene Loci That Overlap Between Schizophrenia and Educational Attainment. Schizophr Bull 2017; 43:654-664. [PMID: 27338279 PMCID: PMC5463752 DOI: 10.1093/schbul/sbw085] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
There is evidence for genetic overlap between cognitive abilities and schizophrenia (SCZ), and genome-wide association studies (GWAS) demonstrate that both SCZ and general cognitive abilities have a strong polygenic component with many single-nucleotide polymorphisms (SNPs) each with a small effect. Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold <0.01, we identified 18 genomic loci associated with SCZ after conditioning on College and 15 loci associated with SCZ after conditioning on EduYears. Ten of these loci overlapped. Using conjunctional FDR, we identified 10 loci shared between SCZ and College, and 29 loci shared between SCZ and EduYears. The majority of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation. Importantly, our methods enable identification of bi-directional effects, which highlight the complex relationship between SCZ and educational attainment, and support polygenic mechanisms underlying both cognitive dysfunction and creativity in SCZ.
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Affiliation(s)
- Stéphanie Le Hellard
- NORMENT—KG Jebsen Centre, Department of Clinical Science, University of Bergen, Bergen, Norway;,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Yunpeng Wang
- NORMENT—KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway;,NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,Multimodal Imaging Lab, University of California at San Diego, La Jolla, CA;,Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Aree Witoelar
- NORMENT—KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway;,NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Verena Zuber
- NORMENT—KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway;,NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,NCMM, University of Oslo, Oslo, Norway
| | - Francesco Bettella
- NORMENT—KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway;,NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kenneth Hugdahl
- NORMENT, Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway;,Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Thomas Espeseth
- NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,Department of Psychology, University of Oslo, Oslo, Norway
| | - Vidar M. Steen
- NORMENT—KG Jebsen Centre, Department of Clinical Science, University of Bergen, Bergen, Norway;,Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Ingrid Melle
- NORMENT—KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway;,NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Rahul Desikan
- Multimodal Imaging Lab, University of California at San Diego, La Jolla, CA;,Department of Radiology, University of California at San Diego, La Jolla, CA
| | - Andrew J. Schork
- Multimodal Imaging Lab, University of California at San Diego, La Jolla, CA;,Department of Cognitive Science, University of California San Diego, La Jolla, CA
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
| | - Anders M. Dale
- Multimodal Imaging Lab, University of California at San Diego, La Jolla, CA;,Department of Cognitive Science, University of California San Diego, La Jolla, CA;,Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Srdjan Djurovic
- NORMENT—KG Jebsen Centre, Department of Clinical Science, University of Bergen, Bergen, Norway;,NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Ole A. Andreassen
- NORMENT—KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway;,NORMENT—KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,Multimodal Imaging Lab, University of California at San Diego, La Jolla, CA
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