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Lu Y, Cui Y, Cao L, Dong Z, Cheng L, Wu W, Wang C, Liu X, Liu Y, Zhang B, Li D, Zhao B, Wang H, Li K, Ma L, Shi W, Li W, Ma Y, Du Z, Zhang J, Xiong H, Luo N, Liu Y, Hou X, Han J, Sun H, Cai T, Peng Q, Feng L, Wang J, Paxinos G, Yang Z, Fan L, Jiang T. Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology. Sci Bull (Beijing) 2024; 69:2241-2259. [PMID: 38580551 DOI: 10.1016/j.scib.2024.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/18/2024] [Accepted: 03/11/2024] [Indexed: 04/07/2024]
Abstract
The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.
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Affiliation(s)
- Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Long Cao
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China; Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Zhenwei Dong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luqi Cheng
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Wen Wu
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Changshuo Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Xinyi Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Youtong Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Baogui Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Deying Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bokai Zhao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Kaixin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China
| | - Liang Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiyang Shi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wen Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yawei Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Zongchang Du
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiaqi Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Xiong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Na Luo
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yanyan Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiaoxiao Hou
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jinglu Han
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Hongji Sun
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Tao Cai
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Qiang Peng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Linqing Feng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - George Paxinos
- Neuroscience Research Australia and The University of New South Wales, Sydney NSW 2031, Australia
| | - Zhengyi Yang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
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Mitteroecker P, Merola GP. The cliff edge model of the evolution of schizophrenia: Mathematical, epidemiological, and genetic evidence. Neurosci Biobehav Rev 2024; 160:105636. [PMID: 38522813 DOI: 10.1016/j.neubiorev.2024.105636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/27/2024] [Accepted: 03/16/2024] [Indexed: 03/26/2024]
Abstract
How has schizophrenia, a condition that significantly reduces an individual's evolutionary fitness, remained common across generations and cultures? Numerous theories about the evolution of schizophrenia have been proposed, most of which are not consistent with modern epidemiological and genetic evidence. Here, we briefly review this evidence and explore the cliff edge model of schizophrenia. It suggests that schizophrenia is the extreme manifestation of a polygenic trait or a combination of traits that, within a normal range of variation, confer cognitive, linguistic, and/or social advantages. Only beyond a certain threshold, these traits precipitate the onset of schizophrenia and reduce fitness. We provide the first mathematical model of this qualitative concept and show that it requires only very weak positive selection of the underlying trait(s) to explain today's schizophrenia prevalence. This prediction, along with expectations about the effect size of schizophrenia risk alleles, are surprisingly well matched by empirical evidence. The cliff edge model predicts a dynamic change of selection of risk alleles, which explains the contradictory findings of evolutionary genetic studies.
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Affiliation(s)
- Philipp Mitteroecker
- Unit for Theoretical Biology, Department of Evolutionary Biology, University of Vienna, Djerassiplatz 1, Vienna, Austria; Konrad Lorenz Institute for Evolution and Cognition Research, Martinstrasse 12, Klosterneuburg, Vienna, Austria.
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Safiri S, Noori M, Nejadghaderi SA, Shamekh A, Sullman MJM, Collins GS, Kolahi AA. The burden of schizophrenia in the Middle East and North Africa region, 1990-2019. Sci Rep 2024; 14:9720. [PMID: 38678101 PMCID: PMC11055947 DOI: 10.1038/s41598-024-59905-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 04/16/2024] [Indexed: 04/29/2024] Open
Abstract
Schizophrenia ranks as the third-most common cause of disability among mental disorders globally. This study presents findings on the prevalence, incidence and years lived with disability (YLDs) as a result of schizophrenia in the Middle East and North Africa (MENA), stratified by age, sex and sociodemographic index (SDI). We collected publicly accessible data from the Global Burden of Disease (GBD) study 2019. This study reports the burden of schizophrenia, from 1990 to 2019, for the 21 countries that comprise MENA. In 2019, MENA exhibited an age-standardised point prevalence of 248.2, an incidence rate of 14.7 and an YLD rate of 158.7 per 100,000, which have not changed substantially between 1990 and 2019. In 2019, the age-standardised YLD rate was highest in Qatar and lowest in Afghanistan. No MENA countries demonstrated noteworthy changes in the burden of schizophrenia from 1990 to 2019. Furthermore, in 2019, the highest number of prevalent cases and the point prevalence were observed among those aged 35-39, with a higher prevalence among males in almost all age categories. Additionally, in 2019, the age-standardised YLD rates in MENA were below the worldwide average. Finally, there was a positive correlation between the burden of schizophrenia and the SDI from 1990 to 2019. The disease burden of schizophrenia has remained relatively stable over the past thirty years. Nevertheless, as the regional life-expectancy continues to increase, the burden of schizophrenia is also expected to rise. Therefore, early planning for the increase in the burden of the disease is urgently needed in the region.
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Affiliation(s)
- Saeid Safiri
- Neurosciences Research Center, Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran.
- Clinical Research Development Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Sciences, Tabriz, Iran.
| | - Maryam Noori
- Student Research Committee, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Seyed Aria Nejadghaderi
- HIV/STI Surveillance Research Center, WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
- Systematic Review and Meta-analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Ali Shamekh
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mark J M Sullman
- Department of Life and Health Sciences, University of Nicosia, Nicosia, Cyprus
- Department of Social Sciences, University of Nicosia, Nicosia, Cyprus
| | - Gary S Collins
- Centre for Statistics in Medicine, NDORMS, Botnar Research Centre, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Ali-Asghar Kolahi
- Social Determinants of Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Rantala MJ, Luoto S, Borráz-León JI, Krams I. Schizophrenia: the new etiological synthesis. Neurosci Biobehav Rev 2022; 142:104894. [PMID: 36181926 DOI: 10.1016/j.neubiorev.2022.104894] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 08/25/2022] [Accepted: 09/25/2022] [Indexed: 10/31/2022]
Abstract
Schizophrenia has been an evolutionary paradox: it has high heritability, but it is associated with decreased reproductive success. The causal genetic variants underlying schizophrenia are thought to be under weak negative selection. To unravel this paradox, many evolutionary explanations have been suggested for schizophrenia. We critically discuss the constellation of evolutionary hypotheses for schizophrenia, highlighting the lack of empirical support for most existing evolutionary hypotheses-with the exception of the relatively well supported evolutionary mismatch hypothesis. It posits that evolutionarily novel features of contemporary environments, such as chronic stress, low-grade systemic inflammation, and gut dysbiosis, increase susceptibility to schizophrenia. Environmental factors such as microbial infections (e.g., Toxoplasma gondii) can better predict the onset of schizophrenia than polygenic risk scores. However, researchers have not been able to explain why only a small minority of infected people develop schizophrenia. The new etiological synthesis of schizophrenia indicates that an interaction between host genotype, microbe infection, and chronic stress causes schizophrenia, with neuroinflammation and gut dysbiosis mediating this etiological pathway. Instead of just alleviating symptoms with drugs, the parasite x genotype x stress model emphasizes that schizophrenia treatment should focus on detecting and treating possible underlying microbial infection(s), neuroinflammation, gut dysbiosis, and chronic stress.
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Affiliation(s)
- Markus J Rantala
- Department of Biology, University of Turku, FIN-20014 Turku, Finland.
| | - Severi Luoto
- School of Population Health, University of Auckland, 1023 Auckland, New Zealand
| | | | - Indrikis Krams
- Institute of Ecology and Earth Sciences, University of Tartu, 51014 Tartu, Estonia; Department of Zoology and Animal Ecology, Faculty of Biology, University of Latvia, 1004, Rīga, Latvia
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Banerjee N, Polushina T, Bettella F, Steen VM, Andreassen OA, Le Hellard S. Analysis of differentially methylated regions in great apes and extinct hominids provides support for the evolutionary hypothesis of schizophrenia. Schizophr Res 2019; 206:209-216. [PMID: 30545758 DOI: 10.1016/j.schres.2018.11.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 10/12/2018] [Accepted: 11/22/2018] [Indexed: 12/12/2022]
Abstract
INTRODUCTION The persistence of schizophrenia in human populations separated by geography and time led to the evolutionary hypothesis that proposes schizophrenia as a by-product of the higher cognitive abilities of modern humans. To explore this hypothesis, we used here an evolutionary epigenetics approach building on differentially methylated regions (DMRs) of the genome. METHODS We implemented a polygenic enrichment testing pipeline using the summary statistics of genome-wide association studies (GWAS) of schizophrenia and 12 other phenotypes. We investigated the enrichment of association of these traits across genomic regions with variable methylation between modern humans and great apes (orangutans, chimpanzees and gorillas; great ape DMRs) and between modern humans and recently extinct hominids (Neanderthals and Denisovans; hominid DMRs). RESULTS Regions that are hypo-methylated in humans compared to great apes show enrichment of association with schizophrenia only if the major histocompatibility complex (MHC) region is included. With the MHC region removed from the analysis, only a modest enrichment for SNPs of low effect persists. The INRICH pipeline confirms this finding after rigorous permutation and bootstrapping procedures. CONCLUSION The analyses of regions with differential methylation changes in humans and great apes do not provide compelling evidence of enrichment of association with schizophrenia, in contrast to our previous findings on more recent methylation differences between modern humans, Neanderthals and Denisovans. Our results further support the evolutionary hypothesis of schizophrenia and indicate that the origin of some of the genetic susceptibility factors of schizophrenia may lie in recent human evolution.
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Affiliation(s)
- Niladri Banerjee
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
| | - Tatiana Polushina
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
| | - Francesco Bettella
- NORMENT - K.G. Jebsen Center for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; NORMENT - K.G. Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
| | - Vidar M Steen
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
| | - Ole A Andreassen
- NORMENT - K.G. Jebsen Center for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; NORMENT - K.G. Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
| | - Stephanie Le Hellard
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
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Cosgrave J, Haines R, Golodetz S, Claridge G, Wulff K, van Heugten-van der Kloet D. Schizotypy and Performance on an Insight Problem-Solving Task: The Contribution of Persecutory Ideation. Front Psychol 2018; 9:708. [PMID: 29867673 PMCID: PMC5964745 DOI: 10.3389/fpsyg.2018.00708] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 04/23/2018] [Indexed: 11/22/2022] Open
Abstract
Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01–1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving.
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Affiliation(s)
- Jan Cosgrave
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, Medical Sciences Division, The Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Ross Haines
- Department of Statistics, Mathematical, Physical, and Life Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Stuart Golodetz
- Oxford Smart Specs Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Gordon Claridge
- Department of Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Katharina Wulff
- Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, Medical Sciences Division, The Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Dalena van Heugten-van der Kloet
- Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, Medical Sciences Division, The Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom.,Social Work and Public Health, Department of Psychology, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, United Kingdom
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Banerjee N, Polushina T, Bettella F, Giddaluru S, Steen VM, Andreassen OA, Le Hellard S. Recently evolved human-specific methylated regions are enriched in schizophrenia signals. BMC Evol Biol 2018; 18:63. [PMID: 29747567 PMCID: PMC5946405 DOI: 10.1186/s12862-018-1177-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Accepted: 04/11/2018] [Indexed: 01/10/2023] Open
Abstract
Background One explanation for the persistence of schizophrenia despite the reduced fertility of patients is that it is a by-product of recent human evolution. This hypothesis is supported by evidence suggesting that recently-evolved genomic regions in humans are involved in the genetic risk for schizophrenia. Using summary statistics from genome-wide association studies (GWAS) of schizophrenia and 11 other phenotypes, we tested for enrichment of association with GWAS traits in regions that have undergone methylation changes in the human lineage compared to Neanderthals and Denisovans, i.e. human-specific differentially methylated regions (DMRs). We used analytical tools that evaluate polygenic enrichment of a subset of genomic variants against all variants. Results Schizophrenia was the only trait in which DMR SNPs showed clear enrichment of association that passed the genome-wide significance threshold. The enrichment was not observed for Neanderthal or Denisovan DMRs. The enrichment seen in human DMRs is comparable to that for genomic regions tagged by Neanderthal Selective Sweep markers, and stronger than that for Human Accelerated Regions. The enrichment survives multiple testing performed through permutation (n = 10,000) and bootstrapping (n = 5000) in INRICH (p < 0.01). Some enrichment of association with height was observed at the gene level. Conclusions Regions where DNA methylation modifications have changed during recent human evolution show enrichment of association with schizophrenia and possibly with height. Our study further supports the hypothesis that genetic variants conferring risk of schizophrenia co-occur in genomic regions that have changed as the human species evolved. Since methylation is an epigenetic mark, potentially mediated by environmental changes, our results also suggest that interaction with the environment might have contributed to that association. Electronic supplementary material The online version of this article (10.1186/s12862-018-1177-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Niladri Banerjee
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Tatiana Polushina
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Francesco Bettella
- NORMENT - K.G. Jebsen Center for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,NORMENT - K.G. Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Sudheer Giddaluru
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Vidar M Steen
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Ole A Andreassen
- NORMENT - K.G. Jebsen Center for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,NORMENT - K.G. Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Stephanie Le Hellard
- NORMENT - K.G. Jebsen Center for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway. .,Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway. .,Department of Clinical Medicine, Laboratory Building, Haukeland University Hospital, N-5021, Bergen, Norway.
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Thys E, Sabbe B, De Hert M. Creativity and psychiatric illness: the search for a missing link--an historical context for current research. Psychopathology 2013; 46:136-44. [PMID: 22987048 DOI: 10.1159/000339458] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2011] [Accepted: 05/01/2012] [Indexed: 11/19/2022]
Abstract
Creativity is an important human quality upon which many achievements of humankind are based. Defined as the ability to produce something that is novel and useful or meaningful, it is difficult to operationalize for research. This text provides an overview of the historical and cultural context of this research. The assumption that creativity is related to psychiatric vulnerability dates back to antiquity. The modern interest in the subject stems from the romantic era and gained a scientific aura in the 19th century. In the 20th century, a further entanglement of creativity and psychopathology came about through the influence of patient artists on regular art. Psychometric, psychodiagnostic and genetic research supports a connection between creativity and psychiatric illness within the bipolar-psychotic continuum, with schizotypy/thymotypy as prototypes of creativity-related disorders. Evolutionary hypotheses link the schizophrenia paradox to a survival advantage through enhanced creative ability. The relevance of scientific research in this complex and heterogeneous area can be increased if creativity and psychopathology are further operationalized and if underlying art concepts are made explicit and placed in a broader cultural context. There is a continuing need for meaningful definitions and measures, as well as a multidisciplinary collaboration.
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Affiliation(s)
- E Thys
- University Psychiatric Centre KU Leuven, Campus Kortenberg, Kortenberg, Belgium.
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Kyaga S, Lichtenstein P, Boman M, Hultman C, Långström N, Landén M. Creativity and mental disorder: family study of 300,000 people with severe mental disorder. Br J Psychiatry 2011; 199:373-9. [PMID: 21653945 DOI: 10.1192/bjp.bp.110.085316] [Citation(s) in RCA: 133] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
BACKGROUND There is a long-standing belief that creativity is coupled with psychopathology. AIMS To test this alleged association and to investigate whether any such association is the result of environmental or genetic factors. METHOD We performed a nested case-control study based on Swedish registries. The likelihood of holding a creative occupation in individuals who had received in-patient treatment for schizophrenia, bipolar disorder or unipolar depression between 1973 and 2003 and their relatives without such a diagnosis was compared with that of controls. RESULTS Individuals with bipolar disorder and healthy siblings of people with schizophrenia or bipolar disorder were overrepresented in creative professions. People with schizophrenia had no increased rate of overall creative professions compared with controls, but an increased rate in the subgroup of artistic occupations. Neither individuals with unipolar depression nor their siblings differed from controls regarding creative professions. CONCLUSIONS A familial cosegregation of both schizophrenia and bipolar disorder with creativity is suggested.
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Affiliation(s)
- Simon Kyaga
- Department of Epidemiology and Biostatistics, Karolinska Institutet, POB 281, SE 171 77 Stockholm, Sweden.
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Belief in conspiracy theories. The role of paranormal belief, paranoid ideation and schizotypy. PERSONALITY AND INDIVIDUAL DIFFERENCES 2011. [DOI: 10.1016/j.paid.2011.02.027] [Citation(s) in RCA: 188] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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