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Qvist P, Rajkumar AP, Redrobe JP, Nyegaard M, Christensen JH, Mors O, Wegener G, Didriksen M, Børglum AD. Mice heterozygous for an inactivated allele of the schizophrenia associated Brd1 gene display selective cognitive deficits with translational relevance to schizophrenia. Neurobiol Learn Mem 2017; 141:44-52. [PMID: 28341151 DOI: 10.1016/j.nlm.2017.03.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 03/14/2017] [Accepted: 03/15/2017] [Indexed: 10/19/2022]
Abstract
Schizophrenia is a debilitating brain disorder characterized by disturbances of emotion, perception and cognition. Cognitive impairments predict functional outcome in schizophrenia and are detectable even in the prodromal stage of the disorder. However, our understanding of the underlying neurobiology is limited and procognitive treatments remain elusive. We recently demonstrated that mice heterozygous for an inactivated allele of the schizophrenia-associated Brd1 gene (Brd1+/- mice) display behaviors reminiscent of schizophrenia, including impaired social cognition and long-term memory. Here, we further characterize performance of these mice by following the preclinical guidelines recommended by the 'Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS)' and 'Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS)' initiatives to maximize translational value. Brd1+/- mice exhibit relational encoding deficits, compromised working and long term memory, as well as impaired executive cognitive functioning with cognitive behaviors relying on medial prefrontal cortex being particularly affected. Akin to patients with schizophrenia, the cognitive deficits displayed by Brd1+/- mice are not global, but selective. Our results underline the value of Brd1+/- mice as a promising tool for studying the neurobiology of cognitive deficits in schizophrenia.
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Affiliation(s)
- Per Qvist
- Department of Biomedicine, Aarhus University, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark; H. Lundbeck A/S, Synaptic Transmission, Valby, Denmark
| | - Anto P Rajkumar
- Department of Biomedicine, Aarhus University, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark; Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Denmark; Department of Old Age Psychiatry, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK
| | | | - Mette Nyegaard
- Department of Biomedicine, Aarhus University, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark
| | - Jane H Christensen
- Department of Biomedicine, Aarhus University, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark
| | - Ole Mors
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark; Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Gregers Wegener
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Denmark
| | | | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark.
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Dyrvig M, Qvist P, Lichota J, Larsen K, Nyegaard M, Børglum AD, Christensen JH. DNA Methylation Analysis of BRD1 Promoter Regions and the Schizophrenia rs138880 Risk Allele. PLoS One 2017; 12:e0170121. [PMID: 28095495 PMCID: PMC5240986 DOI: 10.1371/journal.pone.0170121] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 12/29/2016] [Indexed: 01/19/2023] Open
Abstract
The bromodomain containing 1 gene, BRD1 is essential for embryogenesis and CNS development. It encodes a protein that participates in histone modifying complexes and thereby regulates the expression of a large number of genes. Genetic variants in the BRD1 locus show association with schizophrenia and bipolar disorder and risk alleles in the promoter region correlate with reduced BRD1 expression. Insights into the transcriptional regulation of BRD1 and the pathogenic mechanisms associated with BRD1 risk variants, however, remain sparse. By studying transcripts in human HeLa and SH-SY5Y cells we provide evidence for differences in relative expression of BRD1 transcripts with three alternative 5’ UTRs (exon 1C, 1B, and 1A). We further show that expression of these transcript variants covaries negatively with DNA methylation proportions in their upstream promoter regions suggesting that promoter usage might be regulated by DNA methylation. In line with findings that the risk allele of the rs138880 SNP in the BRD1 promoter region correlates with reduced BRD1 expression, we find that it is also associated with moderate regional BRD1 promoter hypermethylation in both adipose tissue and blood. Importantly, we demonstrate by inspecting available DNA methylation and expression data that these regions undergo changes in methylation during fetal brain development and that differences in their methylation proportions in fetal compared to postnatal frontal cortex correlate significantly with BRD1 expression. These findings suggest that BRD1 may be dysregulated in both the developing and mature brain of risk allele carriers. Finally, we demonstrate that commonly used mood stabilizers Lithium, Valproate, and Carbamazepine affect the expression of BRD1 in SH-SY5Y cells. Altogether this study indicates a link between genetic risk and epigenetic dysregulation of BRD1 which raises interesting perspectives for targeting the mechanisms pharmacologically.
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Affiliation(s)
- Mads Dyrvig
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Per Qvist
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - Jacek Lichota
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Knud Larsen
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Mette Nyegaard
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - Anders D. Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - Jane H. Christensen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- * E-mail:
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Srinivasan S, Bettella F, Hassani S, Wang Y, Witoelar A, Schork AJ, Thompson WK, Collier DA, Desikan RS, Melle I, Dale AM, Djurovic S, Andreassen OA. Probing the Association between Early Evolutionary Markers and Schizophrenia. PLoS One 2017; 12:e0169227. [PMID: 28081145 PMCID: PMC5231388 DOI: 10.1371/journal.pone.0169227] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 12/13/2016] [Indexed: 12/31/2022] Open
Abstract
Schizophrenia is suggested to be a by-product of the evolution in humans, a compromise for our language, creative thinking and cognitive abilities, and thus, essentially, a human disorder. The time of its origin during the course of human evolution remains unclear. Here we investigate several markers of early human evolution and their relationship to the genetic risk of schizophrenia. We tested the schizophrenia evolutionary hypothesis by analyzing genome-wide association studies of schizophrenia and other human phenotypes in a statistical framework suited for polygenic architectures. We analyzed evolutionary proxy measures: human accelerated regions, segmental duplications, and ohnologs, representing various time periods of human evolution for overlap with the human genomic loci associated with schizophrenia. Polygenic enrichment plots suggest a higher prevalence of schizophrenia associations in human accelerated regions, segmental duplications and ohnologs. However, the enrichment is mostly accounted for by linkage disequilibrium, especially with functional elements like introns and untranslated regions. Our results did not provide clear evidence that markers of early human evolution are more likely associated with schizophrenia. While SNPs associated with schizophrenia are enriched in HAR, Ohno and SD regions, the enrichment seems to be mediated by affiliation to known genomic enrichment categories. Taken together with previous results, these findings suggest that schizophrenia risk may have mainly developed more recently in human evolution.
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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
| | - Sahar Hassani
- 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
| | - 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
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, United States of America
- Cognitive Sciences Graduate Program, University of California, San Diego, La Jolla, CA, United States of America
- Center for Human Development, University of California at San Diego, La Jolla, CA, United States of America
| | - Wesley K. Thompson
- Institute of Biological Psychiatry, Mental Health Center St. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - David A. Collier
- Eli Lilly & Co, Erl Wood Manor, Windlesham, Surrey, United Kingdom
| | - Rahul S. Desikan
- Neuroradiology Section, Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States of America
| | - 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
| | - Anders M. Dale
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, United States of America
- Center for Human Development, University of California at San Diego, La Jolla, CA, United States of America
- Department of Neuroscience, University of California at San Diego, La Jolla, CA, United States of America
- Neuroradiology Section, Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, 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
| | - 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
- Institute of Biological Psychiatry, Mental Health Center St. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- * E-mail:
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Wang Y, Bos SD, Harbo HF, Thompson WK, Schork AJ, Bettella F, Witoelar A, Lie BA, Li W, McEvoy LK, Djurovic S, Desikan RS, Dale AM, Andreassen OA. Genetic overlap between multiple sclerosis and several cardiovascular disease risk factors. Mult Scler 2016; 22:1783-1793. [PMID: 26920376 PMCID: PMC5001937 DOI: 10.1177/1352458516635873] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Revised: 01/26/2016] [Accepted: 02/07/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND Epidemiological findings suggest a relationship between multiple sclerosis (MS) and cardiovascular disease (CVD) risk factors, although the nature of this relationship is not well understood. OBJECTIVE We used genome-wide association study (GWAS) data to identify shared genetic factors (pleiotropy) between MS and CVD risk factors. METHODS Using summary statistics from a large, recent GWAS (total n > 250,000 individuals), we investigated overlap in single nucleotide polymorphisms (SNPs) associated with MS and a number of CVD risk factors including triglycerides (TG), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, body mass index, waist-to-hip ratio, type 2 diabetes, systolic blood pressure, and C-reactive protein level. RESULTS AND CONCLUSION Using conditional enrichment plots, we found 30-fold enrichment of MS SNPs for different levels of association with LDL and TG SNPs, with a corresponding reduction in conditional false discovery rate (FDR). We identified 133 pleiotropic loci outside the extended major histocompatibility complex with conditional FDR < 0.01, of which 65 are novel. These pleiotropic loci were located on 21 different chromosomes. Our findings point to overlapping pathobiology between clinically diagnosed MS and cardiovascular risk factors and identify novel common variants associated with increased MS risk.
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Affiliation(s)
- 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
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Steffan D. Bos
- Department of Neurology, Oslo University Hospital, Ullevål, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Hanne F. Harbo
- Department of Neurology, Oslo University Hospital, Ullevål, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Andrew J. Schork
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA
- Cognitive Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
- Center for Human Development, University of California at San Diego, La Jolla, CA, USA
| | - 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
| | - 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
| | - Benedicte A. Lie
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Wen Li
- 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
| | - Linda K. McEvoy
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Srdjan Djurovic
- 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
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Rahul S. Desikan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Anders M. Dale
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, 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, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
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Can Psychological, Social and Demographical Factors Predict Clinical Characteristics Symptomatology of Bipolar Affective Disorder and Schizophrenia? Psychiatr Q 2016; 87:501-13. [PMID: 26646576 PMCID: PMC4945684 DOI: 10.1007/s11126-015-9405-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Schizophrenia (SCH) is a complex, psychiatric disorder affecting 1 % of population. Its clinical phenotype is heterogeneous with delusions, hallucinations, depression, disorganized behaviour and negative symptoms. Bipolar affective disorder (BD) refers to periodic changes in mood and activity from depression to mania. It affects 0.5-1.5 % of population. Two types of disorder (type I and type II) are distinguished by severity of mania episodes. In our analysis, we aimed to check if clinical and demographical characteristics of the sample are predictors of symptom dimensions occurrence in BD and SCH cases. We included total sample of 443 bipolar and 439 schizophrenia patients. Diagnosis was based on DSM-IV criteria using Structured Clinical Interview for DSM-IV. We applied regression models to analyse associations between clinical and demographical traits from OPCRIT and symptom dimensions. We used previously computed dimensions of schizophrenia and bipolar affective disorder as quantitative traits for regression models. Male gender seemed protective factor for depression dimension in schizophrenia and bipolar disorder sample. Presence of definite psychosocial stressor prior disease seemed risk factor for depressive and suicidal domain in BD and SCH. OPCRIT items describing premorbid functioning seemed related with depression, positive and disorganised dimensions in schizophrenia and psychotic in BD. We proved clinical and demographical characteristics of the sample are predictors of symptom dimensions of schizophrenia and bipolar disorder. We also saw relation between clinical dimensions and course of disorder and impairment during disorder.
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56
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Srinivasan S, Bettella F, Mattingsdal M, Wang Y, Witoelar A, Schork AJ, Thompson WK, Zuber V, Winsvold BS, Zwart JA, Collier DA, Desikan RS, Melle I, Werge T, Dale AM, Djurovic S, Andreassen OA. Genetic Markers of Human Evolution Are Enriched in Schizophrenia. Biol Psychiatry 2016; 80:284-292. [PMID: 26681495 PMCID: PMC5397584 DOI: 10.1016/j.biopsych.2015.10.009] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Revised: 09/30/2015] [Accepted: 10/05/2015] [Indexed: 12/13/2022]
Abstract
BACKGROUND Why schizophrenia has accompanied humans throughout our history despite its negative effect on fitness remains an evolutionary enigma. It is proposed that schizophrenia is a by-product of the complex evolution of the human brain and a compromise for humans' language, creative thinking, and cognitive abilities. METHODS We analyzed recent large genome-wide association studies of schizophrenia and a range of other human phenotypes (anthropometric measures, cardiovascular disease risk factors, immune-mediated diseases) using a statistical framework that draws on polygenic architecture and ancillary information on genetic variants. We used information from the evolutionary proxy measure called the Neanderthal selective sweep (NSS) score. RESULTS Gene loci associated with schizophrenia are significantly (p = 7.30 × 10(-9)) more prevalent in genomic regions that are likely to have undergone recent positive selection in humans (i.e., with a low NSS score). Variants in brain-related genes with a low NSS score confer significantly higher susceptibility than variants in other brain-related genes. The enrichment is strongest for schizophrenia, but we cannot rule out enrichment for other phenotypes. The false discovery rate conditional on the evolutionary proxy points to 27 candidate schizophrenia susceptibility loci, 12 of which are associated with schizophrenia and other psychiatric disorders or linked to brain development. CONCLUSIONS Our results suggest that there is a polygenic overlap between schizophrenia and NSS score, a marker of human evolution, which is in line with the hypothesis that the persistence of schizophrenia is related to the evolutionary process of becoming human.
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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
| | - Morten Mattingsdal
- 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
| | - 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,Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA
| | - 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
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA,Cognitive Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA,Center for Human Development, University of California at San Diego, La Jolla, CA, USA
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Verena Zuber
- 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,Centre for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, Oslo, Norway
| | | | | | - Bendik S. Winsvold
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Neurology and FORMI, Oslo University Hospital, Ullevål, Oslo, Norway
| | - John-Anker Zwart
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Neurology and FORMI, Oslo University Hospital, Ullevål, Oslo, Norway
| | | | - Rahul S. Desikan
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA,Neuroradiology Section, Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, USA
| | - 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
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center St. Hans, Mental Health Services Copenhagen, Roskilde, Denmark. Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
| | - Anders M. Dale
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, CA, USA,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Lilly UK, Erl Wood Manor, Windlesham, Surrey, UK,Department of Neuroscience, University of California at San Diego, La Jolla, CA, USA
| | - Srdjan Djurovic
- 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,Department of Medical Genetics, 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,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Corresponding author: , NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital - Ullevål, Kirkeveien 166, PO Box 4956 Nydalen, 0424 Oslo, Norway; Tel.: +47- 22 11 98 90, Fax: +47- 22 11 98 99
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Abstract
PURPOSE OF REVIEW The following review provides some description of the movement in cross-disorder psychiatric genomics toward addressing both comorbidity and polygenicity. RECENT FINDINGS We attempt to show how dimensional approaches to the phenotype have led to further addressing the problem of comorbidity of psychiatric diagnoses. And we also attempt to show how a dimensional approach to the genome, with different statistical methods from traditional genome-wide association analyses, has begun to resolve the problem of massive polygenicity. SUMMARY Cross-disorder research, of any area in psychiatry, arguably has the most potential to inform clinical diagnosis, early detection and prevention strategies, and pharmacological treatment research. Future research might leverage what we now know to inform developmental studies of risk and resilience.
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Affiliation(s)
- Anna R Docherty
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Arden A Moscati
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Ayman H Fanous
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA; Washington Veterans Affairs Healthcare System, Washington D.C., USA; Georgetown University School of Medicine, Washington D.C., USA
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Goff DC, Romero K, Paul J, Mercedes Perez-Rodriguez M, Crandall D, Potkin SG. Biomarkers for drug development in early psychosis: Current issues and promising directions. Eur Neuropsychopharmacol 2016; 26:923-37. [PMID: 27005595 DOI: 10.1016/j.euroneuro.2016.01.009] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 01/20/2016] [Accepted: 01/23/2016] [Indexed: 12/14/2022]
Abstract
A major goal of current research in schizophrenia is to understand the biology underlying onset and early progression and to develop interventions that modify these processes. Biomarkers can play a critical role in identifying disease state, factors contributing to underlying progression, as well as predicting and monitoring response to treatment. Once biomarker-based therapeutics are established, biomarkers can guide treatment selection. It is increasingly clear that a wide range of potential biomarkers should be examined in schizophrenia, given the large number of genetic and environmental factors that have been identified as risk factors. New models for analysis of biomarkers are needed that represent the central nervous system as a highly complex, dynamic, and interactive system. Many tools are available with which to study relevant brain chemistry, but most are indirect measures and represent only a small fraction of the potential etiologic factors contributing to the molecular, structural and functional components of schizophrenia. This review represents the work of the International Society for CNS Clinical Trials and Methodology (ISCTM) Biomarkers Working Group. It discusses advantages and disadvantages of different categories of biomarkers and provides a summary of evidence that biomarkers representing inflammation, oxidative stress, endocannabinoids, glucocorticoid, and biogenic amines systems are dysregulated and potentially interactive in early phase schizophrenia. As has been recently demonstrated in several neurodevelopmental and neurodegenerative disorders, a multi-modal, longitudinal strategy involving a diverse array of biomarkers and new approaches to statistical modeling are needed to improve early interventions based on the fuller understanding.
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Affiliation(s)
| | | | - Jeffrey Paul
- Astellas Pharma Global Development, Northbrook, IL, USA
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Genetic Relationship between Schizophrenia and Nicotine Dependence. Sci Rep 2016; 6:25671. [PMID: 27164557 PMCID: PMC4862382 DOI: 10.1038/srep25671] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 04/20/2016] [Indexed: 12/11/2022] Open
Abstract
It is well known that most schizophrenia patients smoke cigarettes. There are different hypotheses postulating the underlying mechanisms of this comorbidity. We used summary statistics from large meta-analyses of plasma cotinine concentration (COT), Fagerström test for nicotine dependence (FTND) and schizophrenia to examine the genetic relationship between these traits. We found that schizophrenia risk scores calculated at P-value thresholds of 5 × 10−3 and larger predicted FTND and cigarettes smoked per day (CPD), suggesting that genes most significantly associated with schizophrenia were not associated with FTND/CPD, consistent with the self-medication hypothesis. The COT risk scores predicted schizophrenia diagnosis at P-values of 5 × 10−3 and smaller, implying that genes most significantly associated with COT were associated with schizophrenia. These results implicated that schizophrenia and FTND/CPD/COT shared some genetic liability. Based on this shared liability, we identified multiple long non-coding RNAs and RNA binding protein genes (DA376252, BX089737, LOC101927273, LINC01029, LOC101928622, HY157071, DA902558, RBFOX1 and TINCR), protein modification genes (MANBA, UBE2D3, and RANGAP1) and energy production genes (XYLB, MTRF1 and ENOX1) that were associated with both conditions. Further analyses revealed that these shared genes were enriched in calcium signaling, long-term potentiation and neuroactive ligand-receptor interaction pathways that played a critical role in cognitive functions and neuronal plasticity.
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Fryland T, Christensen JH, Pallesen J, Mattheisen M, Palmfeldt J, Bak M, Grove J, Demontis D, Blechingberg J, Ooi HS, Nyegaard M, Hauberg ME, Tommerup N, Gregersen N, Mors O, Corydon TJ, Nielsen AL, Børglum AD. Identification of the BRD1 interaction network and its impact on mental disorder risk. Genome Med 2016; 8:53. [PMID: 27142060 PMCID: PMC4855718 DOI: 10.1186/s13073-016-0308-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2015] [Accepted: 04/15/2016] [Indexed: 01/23/2023] Open
Abstract
Background The bromodomain containing 1 (BRD1) gene has been implicated with transcriptional regulation, brain development, and susceptibility to schizophrenia and bipolar disorder. To advance the understanding of BRD1 and its role in mental disorders, we characterized the protein and chromatin interactions of the BRD1 isoforms, BRD1-S and BRD1-L. Methods Stable human cell lines expressing epitope tagged BRD1-S and BRD1-L were generated and used as discovery systems for identifying protein and chromatin interactions. Protein-protein interactions were identified using co-immunoprecipitation followed by mass spectrometry and chromatin interactions were identified using chromatin immunoprecipitation followed by next generation sequencing. Gene expression profiles and differentially expressed genes were identified after upregulating and downregulating BRD1 expression using microarrays. The presented functional molecular data were integrated with human genomic and transcriptomic data using available GWAS, exome-sequencing datasets as well as spatiotemporal transcriptomic datasets from the human brain. Results We present several novel protein interactions of BRD1, including isoform-specific interactions as well as proteins previously implicated with mental disorders. By BRD1-S and BRD1-L chromatin immunoprecipitation followed by next generation sequencing we identified binding to promoter regions of 1540 and 823 genes, respectively, and showed correlation between BRD1-S and BRD1-L binding and regulation of gene expression. The identified BRD1 interaction network was found to be predominantly co-expressed with BRD1 mRNA in the human brain and enriched for pathways involved in gene expression and brain function. By interrogation of large datasets from genome-wide association studies, we further demonstrate that the BRD1 interaction network is enriched for schizophrenia risk. Conclusion Our results show that BRD1 interacts with chromatin remodeling proteins, e.g. PBRM1, as well as histone modifiers, e.g. MYST2 and SUV420H1. We find that BRD1 primarily binds in close proximity to transcription start sites and regulates expression of numerous genes, many of which are involved with brain development and susceptibility to mental disorders. Our findings indicate that BRD1 acts as a regulatory hub in a comprehensive schizophrenia risk network which plays a role in many brain regions throughout life, implicating e.g. striatum, hippocampus, and amygdala at mid-fetal stages. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0308-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tue Fryland
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Jane H Christensen
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Jonatan Pallesen
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Manuel Mattheisen
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Johan Palmfeldt
- Research Unit for Molecular Medicine, Aarhus University Hospital, 8200, Skejby, Denmark
| | - Mads Bak
- Wilhelm Johannsen Centre for Functional Genome Research, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200, Copenhagen N, Denmark
| | - Jakob Grove
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark.,Bioinformatics Research Centre (BiRC, Aarhus University, 8000, Aarhus C, Denmark
| | - Ditte Demontis
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Jenny Blechingberg
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark
| | - Hong Sain Ooi
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Mette Nyegaard
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Mads E Hauberg
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Niels Tommerup
- Wilhelm Johannsen Centre for Functional Genome Research, Department of Cellular and Molecular Medicine, University of Copenhagen, 2200, Copenhagen N, Denmark
| | - Niels Gregersen
- Research Unit for Molecular Medicine, Aarhus University Hospital, 8200, Skejby, Denmark
| | - Ole Mors
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark.,Research Department P, Aarhus University Hospital, 8240, Risskov, Denmark
| | - Thomas J Corydon
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Anders L Nielsen
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark.,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Building 1242, Bartholins Allé 6, 8000, Aarhus C, Denmark. .,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000 Aarhus C, Denmark. .,iSEQ, Centre for Integrative Sequencing, Aarhus University, 8000, Aarhus C, Denmark. .,Research Department P, Aarhus University Hospital, 8240, Risskov, Denmark.
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Schork AJ, Wang Y, Thompson WK, Dale AM, Andreassen OA. New statistical approaches exploit the polygenic architecture of schizophrenia--implications for the underlying neurobiology. Curr Opin Neurobiol 2016; 36:89-98. [PMID: 26555806 PMCID: PMC5380793 DOI: 10.1016/j.conb.2015.10.008] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Revised: 10/07/2015] [Accepted: 10/12/2015] [Indexed: 01/08/2023]
Abstract
Schizophrenia is a complex disorder with high heritability. Recent findings from several large genetic studies suggest a large number of risk variants are involved (i.e. schizophrenia is a polygenic disorder) and analytic approaches could be tailored for this scenario. Novel statistical approaches for analyzing GWAS data have recently been developed to be more sensitive to polygenic traits. These approaches have provided intriguing new insights into neurobiological pathways and support for the involvement of regulatory mechanisms, neurotransmission (glutamate, dopamine, GABA), and immune and neurodevelopmental pathways. Integrating the emerging statistical genetics evidence with sound neurobiological experiments will be a crucial, and challenging, next step in deciphering the specific disease mechanisms of schizophrenia.
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Affiliation(s)
- Andrew J Schork
- Multimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; Center for Human Development, UC San Diego, La Jolla, CA, USA; Kavli Institute for Brain and Mind, UC San Diego, La Jolla, CA, USA; Department of Cognitive Science, UC San Diego, La Jolla, CA, USA
| | - Yunpeng Wang
- Multimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; 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; Department of Neuroscience, UC San Diego, La Jolla, CA, USA
| | - Wesley K Thompson
- Multimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; Department of Psychiatry, UC San Diego, La Jolla, CA, USA
| | - Anders M Dale
- Multimodal Imaging Laboratory, UC San Diego, La Jolla, CA, USA; Department of Neuroscience, UC San Diego, La Jolla, CA, USA; Department of Psychiatry, UC San Diego, La Jolla, CA, USA; Department of Radiology, UC San Diego, La Jolla, CA, USA.
| | - 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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Wang Y, Thompson WK, Schork AJ, Holland D, Chen CH, Bettella F, Desikan RS, Li W, Witoelar A, Zuber V, Devor A, Nöthen MM, Rietschel M, Chen Q, Werge T, Cichon S, Weinberger DR, Djurovic S, O’Donovan M, Visscher PM, Andreassen OA, Dale AM. Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS. PLoS Genet 2016; 12:e1005803. [PMID: 26808560 PMCID: PMC4726519 DOI: 10.1371/journal.pgen.1005803] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Accepted: 12/21/2015] [Indexed: 02/05/2023] Open
Abstract
Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3. Genome-wide association studies (GWAS) have thus far identified only a small fraction of the heritability of common complex disorders, such as schizophrenia. Here, we demonstrate that by using auxiliary information we can improve estimates of replication probabilities from GWAS summary statistics. The proposed Covariate-Modulated Mixture Model (CM3) incorporates auxiliary information to construct an “enrichment score” for each single nucleotide polymorphism (SNP). We show that a scale mixture of two Gaussians provides a good fit to the observed effect size distribution stratified by the predicted enrichment score when applied the method to a recent genome-wide association study (GWAS) of SCZ (n = 82,315). Compared to estimates performed not using auxiliary information, the CM3 more accurately models the observed replication rates by stratifying on covariate-modulated enrichment scores. We observed that SNPs with low enrichment scores replicate with a lower probability compared to SNPs with high enrichment scores, even when both are genome-wide significant (p < 5x10-8). At model-based replication rates ≥80% and ≥90% there were 693 and 219 independent loci, respectively. Increased out-of-sample yield for SNPs ranked according to CM3 demonstrate the utility of incorporating auxiliary information via CM3.
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Affiliation(s)
- 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
- Department of Neurosciences, University of California, San Diego, La Jolla, California, United States of America
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, California, United States of America
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, California, United States of America
| | - Andrew J. Schork
- Department of Cognitive Sciences, University of California at San Diego, La Jolla, California, United States of America
| | - Dominic Holland
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, California, United States of America
| | - Chi-Hua Chen
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, California, United States of America
- Department of Radiology, University of California, San Diego, La Jolla, California, United States of America
| | - 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
| | - Rahul S. Desikan
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, California, United States of America
- Department of Radiology, University of California, San Diego, La Jolla, California, United States of America
| | - Wen Li
- 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
| | - Verena Zuber
- 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
| | - Anna Devor
- Department of Neurosciences, University of California, San Diego, La Jolla, California, United States of America
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, California, United States of America
| | | | | | | | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim, Germany
| | - Qiang Chen
- Lieber Institute for Brain Development, Baltimore, Maryland, United States of America
| | - Thomas Werge
- Institute of Biological Psychiatry, MHC, Sct. Hans Hospital and University of Copenhagen, Copenhagen, Denmark
| | - Sven Cichon
- Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Daniel R. Weinberger
- Lieber Institute for Brain Development, Baltimore, Maryland, United States of America
| | - Srdjan Djurovic
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Michael O’Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Heath Park, Cardiff, United Kingdom
| | - Peter M. Visscher
- The Queensland Brain Institute, The University of Queensland, Brisbane, Australia
- University of Queensland Diamantina Institute, University of Queensland, Translational Research Institute (TRI), Brisbane, Australia
| | - 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
- * E-mail: (AMD); (OAA)
| | - Anders M. Dale
- Department of Neurosciences, University of California, San Diego, La Jolla, California, United States of America
- Multimodal Imaging Laboratory, University of California at San Diego, La Jolla, California, United States of America
- Department of Psychiatry, University of California, San Diego, La Jolla, California, United States of America
- Department of Radiology, University of California, San Diego, La Jolla, California, United States of America
- * E-mail: (AMD); (OAA)
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Nestler EJ, Peña CJ, Kundakovic M, Mitchell A, Akbarian S. Epigenetic Basis of Mental Illness. Neuroscientist 2015; 22:447-63. [PMID: 26450593 DOI: 10.1177/1073858415608147] [Citation(s) in RCA: 199] [Impact Index Per Article: 22.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Psychiatric disorders are complex multifactorial illnesses involving chronic alterations in neural circuit structure and function as well as likely abnormalities in glial cells. While genetic factors are important in the etiology of most mental disorders, the relatively high rates of discordance among identical twins, particularly for depression and other stress-related syndromes, clearly indicate the importance of additional mechanisms. Environmental factors such as stress are known to play a role in the onset of these illnesses. Exposure to such environmental insults induces stable changes in gene expression, neural circuit function, and ultimately behavior, and these maladaptations appear distinct between developmental versus adult exposures. Increasing evidence indicates that these sustained abnormalities are maintained by epigenetic modifications in specific brain regions. Indeed, transcriptional dysregulation and the aberrant epigenetic regulation that underlies this dysregulation is a unifying theme in psychiatric disorders. Here, we provide a progress report of epigenetic studies of the three major psychiatric syndromes, depression, schizophrenia, and bipolar disorder. We review the literature derived from animal models of these disorders as well as from studies of postmortem brain tissue from human patients. While epigenetic studies of mental illness remain at early stages, understanding how environmental factors recruit the epigenetic machinery within specific brain regions to cause lasting changes in disease susceptibility and pathophysiology is revealing new insight into the etiology and treatment of these conditions.
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Affiliation(s)
- Eric J Nestler
- Departments of Neuroscience and Psychiatry, The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Catherine J Peña
- Departments of Neuroscience and Psychiatry, The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marija Kundakovic
- Departments of Neuroscience and Psychiatry, The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amanda Mitchell
- Departments of Neuroscience and Psychiatry, The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Schahram Akbarian
- Departments of Neuroscience and Psychiatry, The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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64
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Transcriptional regulation of GAD1 GABA synthesis gene in the prefrontal cortex of subjects with schizophrenia. Schizophr Res 2015; 167:28-34. [PMID: 25458568 PMCID: PMC4417100 DOI: 10.1016/j.schres.2014.10.020] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2014] [Revised: 10/08/2014] [Accepted: 10/13/2014] [Indexed: 12/20/2022]
Abstract
Expression of GAD1 GABA synthesis enzyme is highly regulated by neuronal activity and reaches mature levels in the prefrontal cortex not before adolescence. A significant portion of cases diagnosed with schizophrenia show deficits in GAD1 RNA and protein levels in multiple areas of adult cerebral cortex, possibly reflecting molecular or cellular defects in subtypes of GABAergic interneurons essential for network synchronization and cognition. Here, we review 20years of progress towards a better understanding of disease-related regulation of GAD1 gene expression. For example, deficits in cortical GAD1 RNA in some cases of schizophrenia are associated with changes in the epigenetic architecture of the promoter, affecting DNA methylation patterns and nucleosomal histone modifications. These localized chromatin defects at the 5' end of GAD1 are superimposed by disordered locus-specific chromosomal conformations, including weakening of long-range promoter-enhancer loopings and physical disconnection of GAD1 core promoter sequences from cis-regulatory elements positioned 50 kilobases further upstream. Studies on the 3-dimensional architecture of the GAD1 locus in neurons, including developmentally regulated higher order chromatin compromised by the disease process, together with exploration of locus-specific epigenetic interventions in animal models, could pave the way for future treatments of psychosis and schizophrenia.
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65
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Cohen SM, Tsien RW, Goff DC, Halassa MM. The impact of NMDA receptor hypofunction on GABAergic neurons in the pathophysiology of schizophrenia. Schizophr Res 2015; 167:98-107. [PMID: 25583246 PMCID: PMC4724170 DOI: 10.1016/j.schres.2014.12.026] [Citation(s) in RCA: 165] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Revised: 11/25/2014] [Accepted: 12/18/2014] [Indexed: 02/07/2023]
Abstract
While the dopamine hypothesis has dominated schizophrenia research for several decades, more recent studies have highlighted the role of fast synaptic transmitters and their receptors in schizophrenia etiology. Here we review evidence that schizophrenia is associated with a reduction in N-methyl-d-aspartate receptor (NMDAR) function. By highlighting postmortem, neuroimaging and electrophysiological studies, we provide evidence for preferential disruption of GABAergic circuits in the context of NMDAR hypo-activity states. The functional relationship between NMDARs and GABAergic neurons is realized at the molecular, cellular, microcircuit and systems levels. A synthesis of findings across these levels explains how NMDA-mediated inhibitory dysfunction may lead to aberrant interactions among brain regions, accounting for key clinical features of schizophrenia. This synthesis of schizophrenia unifies observations from diverse fields and may help chart pathways for developing novel diagnostics and therapeutics.
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Affiliation(s)
- Samuel M. Cohen
- NYU Neuroscience Institute and Department of Neuroscience and Physiology, NYU Langone Medical Center, New York, NY 10016, USA
| | - Richard W. Tsien
- NYU Neuroscience Institute and Department of Neuroscience and Physiology, NYU Langone Medical Center, New York, NY 10016, USA
| | - Donald C. Goff
- Department of Psychiatry, NYU Langone Medical Center, 550 First Avenue, New York City, NY 10016, USA
,Nathan Kline Institute for Psychiatric Research, 140 Old Orangeburg Road, Orangeburg, NY 10962, USA
| | - Michael M. Halassa
- NYU Neuroscience Institute and Department of Neuroscience and Physiology, NYU Langone Medical Center, New York, NY 10016, USA
,Department of Psychiatry, NYU Langone Medical Center, 550 First Avenue, New York City, NY 10016, USA
,To whom correspondence should be addressed:
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Altered Brain Activation during Emotional Face Processing in Relation to Both Diagnosis and Polygenic Risk of Bipolar Disorder. PLoS One 2015. [PMID: 26222050 PMCID: PMC4519303 DOI: 10.1371/journal.pone.0134202] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Objectives Bipolar disorder (BD) is a highly heritable disorder with polygenic inheritance. Among the most consistent findings from functional magnetic imaging (fMRI) studies are limbic hyperactivation and dorsal hypoactivation. However, the relation between reported brain functional abnormalities and underlying genetic risk remains elusive. This is the first cross-sectional study applying a whole-brain explorative approach to investigate potential influence of BD case-control status and polygenic risk on brain activation. Methods A BD polygenic risk score (PGRS) was estimated from the Psychiatric Genomics Consortium BD case-control study, and assigned to each individual in our independent sample (N=85 BD cases and 121 healthy controls (HC)), all of whom participated in an fMRI emotional faces matching paradigm. Potential differences in BOLD response across diagnostic groups were explored at whole-brain level in addition to amygdala as a region of interest. Putative effects of BD PGRS on brain activation were also investigated. Results At whole-brain level, BD cases presented with significantly lower cuneus/precuneus activation than HC during negative face processing (Z-threshold=2.3 as cluster-level correction). The PGRS was associated positively with increased right inferior frontal gyrus (rIFG) activation during negative face processing. For amygdala activation, there were no correlations with diagnostic status or PGRS. Conclusions These findings are in line with previous reports of reduced precuneus and altered rIFG activation in BD. While these results demonstrate the ability of PGRS to reveal underlying genetic risk of altered brain activation in BD, the lack of convergence of effects at diagnostic and PGRS level suggests that this relation is a complex one.
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Abstract
Schizophrenia is a major psychiatric disorder that lacks a unifying neuropathology, while currently available pharmacological treatments provide only limited benefits to many patients. This review will discuss how the field of neuroepigenetics could contribute to advancements of the existing knowledge on the neurobiology and treatment of psychosis. Genome-scale mapping of DMA methylation, histone modifications and variants, and chromosomal loopings for promoter-enhancer interactions and other epigenetic determinants of genome organization and function are likely to provide important clues about mechanisms contributing to dysregulated expression of synaptic and metabolic genes in schizophrenia brain, including the potential links to the underlying genetic risk architecture and environmental exposures. In addition, studies in animal models are providing a rapidly increasing list of chromatin-regulatory mechanisms with significant effects on cognition and complex behaviors, thereby pointing to the therapeutic potential of epigenetic drug targets in the nervous system.
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Affiliation(s)
- Schahram Akbarian
- Department of Psychiatry, Friedman Brain Institute Icahn School of Medicine at Mount Sinai, New York, USA
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68
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Kauppi K, Westlye LT, Tesli M, Bettella F, Brandt CL, Mattingsdal M, Ueland T, Espeseth T, Agartz I, Melle I, Djurovic S, Andreassen OA. Polygenic risk for schizophrenia associated with working memory-related prefrontal brain activation in patients with schizophrenia and healthy controls. Schizophr Bull 2015; 41:736-43. [PMID: 25392519 PMCID: PMC4393689 DOI: 10.1093/schbul/sbu152] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Schizophrenia is a highly heritable and polygenic disease, and identified common genetic variants have shown weak individual effects. Many studies have reported altered working memory (WM)-related brain activation in schizophrenia, preferentially in the frontal lobe. Such differences in brain activations could reflect inherited alterations possibly involved in the disease etiology, or rather secondary disease-related mechanisms. The use of polygenic risk scores (PGRS) based on a large number of risk polymorphisms with small effects is a valuable approach to examine the effect of cumulative genetic risk on brain functioning. This study examined the impact of cumulative genetic risk for schizophrenia on WM-related brain activations, assessed with functional magnetic resonance imaging. For each participant (63 schizophrenia patients and 118 healthy controls), we calculated a PGRS for schizophrenia based on 18 862 single-nucleotide polymorphism in a large multicenter genome-wide association study including 9146 schizophrenia patients and 12 111 controls, performed by the Psychiatric Genomics Consortium. As expected, the PGRS was significantly higher in patients compared with healthy controls. Further, the PGRS was related to differences in frontal lobe brain activation between high and low WM demand. Specifically, even in absence of main effects of diagnosis, increased PGRS was associated with decreased activation difference in the right middle-superior prefrontal cortex (BA 10/11) and the right inferior frontal gyrus (BA 45). This effect was seen in both cases and controls, and was not influenced by sex, age, or task performance. The findings support the notion of dysregulation of frontal lobe functioning as an inherited vulnerability factor in schizophrenia.
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Affiliation(s)
- Karolina Kauppi
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway;
| | - Lars T. Westlye
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway; ,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,Department of Psychology, University of Oslo, Oslo, Norway
| | | | - Francesco Bettella
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway; ,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Morten Mattingsdal
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway; ,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torill Ueland
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway; ,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,Department of Psychology, University of Oslo, Oslo, Norway
| | - Thomas Espeseth
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway; ,Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway;,Department of Psychology, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Center for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Oslo, Norway; ,Institute of Clinical Medicine, University of Oslo, Oslo, Norway;,Diakonhjemmet Hospital, Oslo, Norway
| | | | - Srdjan Djurovic
- Division of Medical Genetics, Oslo University Hospital, Oslo, Norway
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Andreassen OA, Desikan RS, Wang Y, Thompson WK, Schork AJ, Zuber V, Doncheva NT, Ellinghaus E, Albrecht M, Mattingsdal M, Franke A, Lie BA, Mills I, Aukrust P, McEvoy LK, Djurovic S, Karlsen TH, Dale AM. Abundant genetic overlap between blood lipids and immune-mediated diseases indicates shared molecular genetic mechanisms. PLoS One 2015; 10:e0123057. [PMID: 25853426 PMCID: PMC4390360 DOI: 10.1371/journal.pone.0123057] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 01/16/2015] [Indexed: 12/29/2022] Open
Abstract
Epidemiological studies suggest a relationship between blood lipids and immune-mediated diseases, but the nature of these associations is not well understood. We used genome-wide association studies (GWAS) to investigate shared single nucleotide polymorphisms (SNPs) between blood lipids and immune-mediated diseases. We analyzed data from GWAS (n~200,000 individuals), applying new False Discovery Rate (FDR) methods, to investigate genetic overlap between blood lipid levels [triglycerides (TG), low density lipoproteins (LDL), high density lipoproteins (HDL)] and a selection of archetypal immune-mediated diseases (Crohn’s disease, ulcerative colitis, rheumatoid arthritis, type 1 diabetes, celiac disease, psoriasis and sarcoidosis). We found significant polygenic pleiotropy between the blood lipids and all the investigated immune-mediated diseases. We discovered several shared risk loci between the immune-mediated diseases and TG (n = 88), LDL (n = 87) and HDL (n = 52). Three-way analyses differentiated the pattern of pleiotropy among the immune-mediated diseases. The new pleiotropic loci increased the number of functional gene network nodes representing blood lipid loci by 40%. Pathway analyses implicated several novel shared mechanisms for immune pathogenesis and lipid biology, including glycosphingolipid synthesis (e.g. FUT2) and intestinal host-microbe interactions (e.g. ATG16L1). We demonstrate a shared genetic basis for blood lipids and immune-mediated diseases independent of environmental factors. Our findings provide novel mechanistic insights into dyslipidemia and immune-mediated diseases and may have implications for therapeutic trials involving lipid-lowering and anti-inflammatory agents.
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Affiliation(s)
- 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
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, United States of America
- * E-mail: (AMD); (OAA)
| | - Rahul S. Desikan
- Multimodal Imaging Laboratory, 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
| | - 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
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA 92093, United States of America
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, United States of America
| | - Wesley K. Thompson
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, United States of America
| | - Andrew J. Schork
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA 92093, United States of America
- Cognitive Sciences Graduate Program, University of California San Diego, La Jolla, CA 92093, United States of America
- Center for Human Development, University of California San Diego, La Jolla, CA 92093, United States of America
| | - Verena Zuber
- 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
- Centre for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, 0407 Oslo, Norway
| | | | - Eva Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, 24118 Kiel, Germany
| | - Mario Albrecht
- Max Planck Institute for Informatics, 66123 Saarbrücken, Germany
- Department of Bioinformatics, Institute of Biometrics and Medical Informatics, University Medicine Greifswald, 17475 Greifswald, Germany
- Institute for Knowledge Discovery, Graz University of Technology, 8010 Graz, Austria
- BioTechMed-Graz, 8010 Graz, Austria
| | - Morten Mattingsdal
- 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
- Sørlandet Hospital, 3000 Kristiansand, Norway
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, 24118 Kiel, Germany
| | | | - Ian Mills
- Centre for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, 0407 Oslo, Norway
- Department of Cancer Prevention, Institute of Cancer Research and Department of Urology, Oslo University Hospital, 0407 Oslo, Norway
| | - Pål Aukrust
- Department of Medical Genetics, University of Oslo and Oslo University Hospital, 0407 Oslo, Norway
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital, 0407 Oslo Norway
| | - Linda K. McEvoy
- Multimodal Imaging Laboratory, 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
| | - Srdjan Djurovic
- 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 Medical Genetics, University of Oslo and Oslo University Hospital, 0407 Oslo, Norway
| | - Tom H. Karlsen
- K.G.Jebsen Inflammation Research Centre, Research Institute of Internal Medicine, Division of Cancer Medicine, Surgery and Transplantation, Oslo University Hospital Rikshospitalet, 0407 Oslo, Norway
- Division of Gastroenterology, Institute of Medicine, University of Bergen, 5000 Bergen, Norway
- Norwegian PSC Research Center, Department of Transplantation Medicine, Division of Cancer Medicine, Surgery and Transplantation, Oslo University Hospital Rikshospitalet, 0407 Oslo, Norway
| | - Anders M. Dale
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, United States of America
- Multimodal Imaging Laboratory, 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 Neurosciences, University of California San Diego, La Jolla, CA 92093, United States of America
- * E-mail: (AMD); (OAA)
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Morishita H, Kundakovic M, Bicks L, Mitchell A, Akbarian S. Interneuron epigenomes during the critical period of cortical plasticity: Implications for schizophrenia. Neurobiol Learn Mem 2015; 124:104-10. [PMID: 25849095 DOI: 10.1016/j.nlm.2015.03.005] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2015] [Revised: 03/23/2015] [Accepted: 03/25/2015] [Indexed: 10/23/2022]
Abstract
Schizophrenia, a major psychiatric disorder defined by delusions and hallucinations, among other symptoms, often with onset in early adulthood, is potentially associated with molecular and cellular alterations in parvalbumin-expressing fast spiking interneurons and other constituents of the cortical inhibitory GABAergic circuitry. The underlying mechanisms, including the role of disease-associated risk factors operating in adolescence such as drug abuse and social stressors, remain incompletely understood. Here, we summarize emerging findings from animal models, highlighting the ability of parvalbuminergic interneurons (PVI) to induce, during the juvenile period, long-term plastic changes in prefrontal and visual cortex, thereby altering perception, cognition and behavior in the adult. Of note, molecular alterations in PVI from subjects with schizophrenia, including downregulated expression of a subset of GABAergic genes, have also been found in juvenile stress models of the disorder. Some of the transcriptional alterations observed in schizophrenia postmortem brain could be linked to changes in the epigenetic architecture of GABAergic gene promoters, including dysregulated DNA methylation, histone modification patterns and disruption of promoter-enhancer interactions at site of chromosomal loop formations. Therefore, we predict that, in the not-to-distant future, PVI- and other cell-type specific epigenomic mappings in the animal model and human brain will provide novel insights into the pathophysiology of schizophrenia and related psychotic diseases, including the role of cortical GABAergic circuitry in shaping long-term plasticity and cognitive function of the cerebral cortex.
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Affiliation(s)
- Hirofumi Morishita
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, United States; Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, United States; Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, United States; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, United States.
| | - Marija Kundakovic
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, United States; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, United States
| | - Lucy Bicks
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, United States; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, United States
| | - Amanda Mitchell
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, United States; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, United States
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, United States; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, United States.
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71
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All the world's a (clinical) stage: rethinking bipolar disorder from a longitudinal perspective. Mol Psychiatry 2015; 20:23-31. [PMID: 25048003 PMCID: PMC4303542 DOI: 10.1038/mp.2014.71] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Revised: 05/13/2014] [Accepted: 06/06/2014] [Indexed: 12/11/2022]
Abstract
Psychiatric disorders have traditionally been classified using a static, categorical approach. However, this approach falls short in facilitating understanding of the development, common comorbid diagnoses, prognosis and treatment of these disorders. We propose a 'staging' model of bipolar disorder that integrates genetic and neural information with mood and activity symptoms to describe how the disease progresses over time. From an early, asymptomatic, but 'at-risk' stage to severe, chronic illness, each stage is described with associated neuroimaging findings as well as strategies for mapping genetic risk factors. Integrating more biologic information relating to cardiovascular and endocrine systems, refining methodology for modeling dimensional approaches to disease and developing outcome measures will all be crucial in examining the validity of this model. Ultimately, this approach should aid in developing targeted interventions for each group that will reduce the significant morbidity and mortality associated with bipolar disorder.
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Emul M, Kalelioglu T. Etiology of cardiovascular disease in patients with schizophrenia: current perspectives. Neuropsychiatr Dis Treat 2015; 11:2493-503. [PMID: 26491327 PMCID: PMC4599145 DOI: 10.2147/ndt.s50006] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Cardiovascular morbidity and mortality are important problems among patients with schizophrenia. A wide spectrum of reasons, ranging from genes to the environment, are held responsible for causing the cardiovascular risk factors that may lead to shortening the life expectancy of patients with schizophrenia. Here, we have summarized the etiologic issues related with the cardiovascular risk factors in schizophrenia. First, we focused on heritable factors associated with cardiovascular disease and schizophrenia by mentioning studies about genetics-epigenetics, in the first-episode or drug-naïve patients. In this context, the association and candidate gene studies about metabolic disturbances in schizophrenia are reviewed, and the lack of the effects of epigenetic/posttranscriptional factors such as microRNAs is mentioned. Increased rates of type 2 diabetes mellitus and disrupted metabolic parameters in schizophrenia are forcing clinicians to struggle with metabolic syndrome parameters and related issues, which are also the underlying causes for the risk of having cardiometabolic and cardiovascular etiology. Second, we summarized the findings of metabolic syndrome-related entities and discussed the influence of the illness itself, antipsychotic drug treatment, and the possible disadvantageous lifestyle on the occurrence of metabolic syndrome (MetS) or diabetes mellitus. Third, we emphasized on the risk factors of sudden cardiac death in patients with schizophrenia. We reviewed the findings on the arrhythmias such as QT prolongation, which is a risk factor for Torsade de Pointes and sudden cardiac death or P-wave prolongation that is a risk factor for atrial fibrillation. For example, the use of antipsychotics is an important reason for the prolongation of QT and some other cardiac autonomic dysfunctions. Additionally, we discussed relatively rare issues such as myocarditis and cardiomyopathy, which are important for prognosis in schizophrenia that may have originated from the use of antipsychotic medication. In conclusion, we considered that the studies and awareness about physical needs of patients with schizophrenia are increasing. It seems logical to increase cooperation and shared care between the different health care professionals to screen and treat cardiovascular disease (CVD)-risk factors, MetS, and diabetes in patients with psychiatric disorders, because some risk factors of MetS or CVD are avoidable or at least modifiable to decrease high mortality in schizophrenia. We suggested that future research should focus on conducting an integrated system of studies based on a holistic biopsychosocial evaluation.
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Affiliation(s)
- Murat Emul
- Department of Psychiatry, Medical School of Cerrahpasa, Istanbul University, Istanbul, Turkey
| | - Tevfik Kalelioglu
- Department of Psychiatry, Bakırkoy Mental Health Research and Training Hospital, Istanbul, Turkey
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73
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Potkin SG, Macciardi F, van Erp TGM. Imaging genetics approaches to identify mechanisms in severe mental illness. Biol Psychiatry 2014; 76:436-7. [PMID: 25149350 DOI: 10.1016/j.biopsych.2014.07.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Revised: 07/18/2014] [Accepted: 07/21/2014] [Indexed: 10/24/2022]
Affiliation(s)
- Steven G Potkin
- Transdisciplinary Imaging Genetics Center, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California.
| | - Fabio Macciardi
- Transdisciplinary Imaging Genetics Center, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
| | - Theo G M van Erp
- Transdisciplinary Imaging Genetics Center, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
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74
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Cardno AG, Owen MJ. Genetic relationships between schizophrenia, bipolar disorder, and schizoaffective disorder. Schizophr Bull 2014; 40:504-15. [PMID: 24567502 PMCID: PMC3984527 DOI: 10.1093/schbul/sbu016] [Citation(s) in RCA: 173] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
There is substantial evidence for partial overlap of genetic influences on schizophrenia and bipolar disorder, with family, twin, and adoption studies showing a genetic correlation between the disorders of around 0.6. Results of genome-wide association studies are consistent with commonly occurring genetic risk variants, contributing to both the shared and nonshared aspects, while studies of large, rare chromosomal structural variants, particularly copy number variants, show a stronger influence on schizophrenia than bipolar disorder to date. Schizoaffective disorder has been less investigated but shows substantial familial overlap with both schizophrenia and bipolar disorder. A twin analysis is consistent with genetic influences on schizoaffective episodes being entirely shared with genetic influences on schizophrenic and manic episodes, while association studies suggest the possibility of some relatively specific genetic influences on broadly defined schizoaffective disorder, bipolar subtype. Further insights into genetic relationships between these disorders are expected as studies continue to increase in sample size and in technical and analytical sophistication, information on phenotypes beyond clinical diagnoses are increasingly incorporated, and approaches such as next-generation sequencing identify additional types of genetic risk variant.
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Affiliation(s)
- Alastair G. Cardno
- Academic Unit of Psychiatry and Behavioural Sciences, University of Leeds, Leeds, UK;,*To whom correspondence should be addressed; Academic Unit of Psychiatry and Behavioural Sciences, Leeds Institute of Health Sciences, University of Leeds, Charles Thackrah Building, 101 Clarendon Road, Leeds LS2 9LJ, UK; tel: +44 113 3437260, fax: +44 113 3436997, e-mail:
| | - Michael J. Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
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Andreassen OA, McEvoy LK, Thompson WK, Wang Y, Reppe S, Schork AJ, Zuber V, Barrett-Connor E, Gautvik K, Aukrust P, Karlsen TH, Djurovic S, Desikan RS, Dale AM. Identifying common genetic variants in blood pressure due to polygenic pleiotropy with associated phenotypes. Hypertension 2014; 63:819-26. [PMID: 24396023 DOI: 10.1161/hypertensionaha.113.02077] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Blood pressure is a critical determinant of cardiovascular morbidity and mortality. It is affected by environmental factors, but has a strong heritable component. Despite recent large genome-wide association studies, few genetic risk factors for blood pressure have been identified. Epidemiological studies suggest associations between blood pressure and several diseases and traits, which may partly arise from a shared genetic basis (genetic pleiotropy). Using genome-wide association studies summary statistics and a genetic pleiotropy-informed conditional false discovery rate method, we systematically investigated genetic overlap between systolic blood pressure (SBP) and 12 comorbid traits and diseases. We found significant enrichment of single nucleotide polymorphisms associated with SBP as a function of their association with body mass index, low-density lipoprotein, waist/hip ratio, schizophrenia, bone mineral density, type 1 diabetes mellitus, and celiac disease. In contrast, the magnitude of enrichment due to shared polygenic effects was smaller with the other phenotypes (triglycerides, high-density lipoproteins, type 2 diabetes mellitus, rheumatoid arthritis, and height). Applying the conditional false discovery rate method to the enriched phenotypes, we identified 62 loci associated with SBP (false discovery rate <0.01), including 42 novel loci. The observed polygenic overlap between SBP and several related disorders indicates that the epidemiological associations are not mediated solely via lifestyle factors but also reflect an etiologic relation that warrants further investigation. The new gene loci identified implicate novel genetic mechanisms related to lipid biology and the immune system in SBP.
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Affiliation(s)
- Ole A Andreassen
- Department of Radiology, University of California, San Diego, 8950 Villa La Jolla Dr, Suite C101, La Jolla, CA 92037-0841. ; and Ole A. Andreassen, NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Ullevål, PO Box 4956 Nydalen, 0424 Oslo, Norway. Email
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