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      Pathological oligodendrocyte precursor cells revealed in human schizophrenic brains and trigger schizophrenia-like behaviors and synaptic defects in genetic animal model

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          Abstract

          Although the link of white matter to pathophysiology of schizophrenia is documented, loss of myelin is not detected in patients at the early stages of the disease, suggesting that pathological evolution of schizophrenia may occur before significant myelin loss. Disrupted-in-schizophrenia-1 (DISC1) protein is highly expressed in oligodendrocyte precursor cells (OPCs) and regulates their maturation. Recently, DISC1-Δ3, a major DISC1 variant that lacks exon 3, has been identified in schizophrenia patients, although its pathological significance remains unknown. In this study, we detected in schizophrenia patients a previously unidentified pathological phenotype of OPCs exhibiting excessive branching. We replicated this phenotype by generating a mouse strain expressing DISC1-Δ3 gene in OPCs. We further demonstrated that pathological OPCs, rather than myelin defects, drive the onset of schizophrenic phenotype by hyperactivating OPCs’ Wnt/β-catenin pathway, which consequently upregulates Wnt Inhibitory Factor 1 (Wif1), leading to the aberrant synaptic formation and neuronal activity. Suppressing Wif1 in OPCs rescues synaptic loss and behavioral disorders in DISC1-Δ3 mice. Our findings reveal the pathogenetic role of OPC-specific DISC1-Δ3 variant in the onset of schizophrenia and highlight the therapeutic potential of Wif1 as an alternative target for the treatment of this disease.

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          Most cited references77

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          Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

          Summary Background As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016. Methods We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes, we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval [UI] 40·8–75·9 million [7·2%, 6·0–8·3]), 45·1 million (29·0–62·8 million [5·6%, 4·0–7·2]), 36·3 million (25·3–50·9 million [4·5%, 3·8–5·3]), 34·7 million (23·0–49·6 million [4·3%, 3·5–5·2]), and 34·1 million (23·5–46·0 million [4·2%, 3·2–5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined decreased between 1990 and 2016 by 2·7% (95% UI 2·3–3·1). Despite mostly stagnant age-standardised rates, the absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined were 10·4% (95% UI 9·0–11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer’s disease and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate (China, 9201 YLDs per 100 000, 95% UI 6862–11943) and highest rate (Yemen, 14 774 YLDs per 100 000, 11 018–19 228). Interpretation The decrease in death rates since 1990 for most causes has not been matched by a similar decline in age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases steeply with age, health systems will face increasing demand for services that are generally costlier than the interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-to-date information about the trends of disease and how this varies between countries is essential to plan for an adequate health-system response.
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            An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex.

            The major cell classes of the brain differ in their developmental processes, metabolism, signaling, and function. To better understand the functions and interactions of the cell types that comprise these classes, we acutely purified representative populations of neurons, astrocytes, oligodendrocyte precursor cells, newly formed oligodendrocytes, myelinating oligodendrocytes, microglia, endothelial cells, and pericytes from mouse cerebral cortex. We generated a transcriptome database for these eight cell types by RNA sequencing and used a sensitive algorithm to detect alternative splicing events in each cell type. Bioinformatic analyses identified thousands of new cell type-enriched genes and splicing isoforms that will provide novel markers for cell identification, tools for genetic manipulation, and insights into the biology of the brain. For example, our data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycolytic enzyme pyruvate kinase. This dataset will provide a powerful new resource for understanding the development and function of the brain. To ensure the widespread distribution of these datasets, we have created a user-friendly website (http://web.stanford.edu/group/barres_lab/brain_rnaseq.html) that provides a platform for analyzing and comparing transciption and alternative splicing profiles for various cell classes in the brain. Copyright © 2014 the authors 0270-6474/14/3411929-19$15.00/0.
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              Inhibition of glycogen synthase kinase-3 by insulin mediated by protein kinase B.

              Glycogen synthase kinase-3 (GSK3) is implicated in the regulation of several physiological processes, including the control of glycogen and protein synthesis by insulin, modulation of the transcription factors AP-1 and CREB, the specification of cell fate in Drosophila and dorsoventral patterning in Xenopus embryos. GSK3 is inhibited by serine phosphorylation in response to insulin or growth factors and in vitro by either MAP kinase-activated protein (MAPKAP) kinase-1 (also known as p90rsk) or p70 ribosomal S6 kinase (p70S6k). Here we show, however, that agents which prevent the activation of both MAPKAP kinase-1 and p70S6k by insulin in vivo do not block the phosphorylation and inhibition of GSK3. Another insulin-stimulated protein kinase inactivates GSK3 under these conditions, and we demonstrate that it is the product of the proto-oncogene protein kinase B (PKB, also known as Akt/RAC). Like the inhibition of GSK3 (refs 10, 14), the activation of PKB is prevented by inhibitors of phosphatidylinositol (PI) 3-kinase.

                Author and article information

                Contributors
                Alexej.Verkhratsky@manchester.ac.uk
                xiaolan35@tmmu.edu.cn
                jianqinniu@tmmu.edu.cn
                Journal
                Mol Psychiatry
                Mol Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                21 September 2022
                21 September 2022
                2022
                : 27
                : 12
                : 5154-5166
                Affiliations
                [1 ]GRID grid.410570.7, ISNI 0000 0004 1760 6682, Department of Histology and Embryology, Chongqing Key Laboratory of Neurobiology, Brain and Intelligence Research Key Laboratory of Chongqing Education Commission, , Third Military Medical University, ; Chongqing, China
                [2 ]GRID grid.511083.e, ISNI 0000 0004 7671 2506, Research Centre, , The Seventh Affiliated Hospital of Sun Yat-sen University, ; Shenzhen, China
                [3 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Department of Neurobiology, and Department of Neurology of Sir Run Run Shaw Hospital, , Zhejiang University School of Medicine, ; Hangzhou, China
                [4 ]GRID grid.417298.1, ISNI 0000 0004 1762 4928, Department of Neurosurgery, , The Second Affiliated Hospital of Third Military Medical University, ; Chongqing, China
                [5 ]GRID grid.117476.2, ISNI 0000 0004 1936 7611, School of Life Sciences, Faculty of Science, , University of Technology Sydney, ; Sydney, Australia
                [6 ]GRID grid.203458.8, ISNI 0000 0000 8653 0555, Department of Physiology, College of Basic Medical Science, , Chongqing Medical University, ; Chongqing, China
                [7 ]GRID grid.5379.8, ISNI 0000000121662407, Faculty of Biology, Medicine and Health, , The University of Manchester, ; Manchester, UK
                [8 ]GRID grid.424810.b, ISNI 0000 0004 0467 2314, Achucarro Center for Neuroscience, IKERBASQUE, ; 48011 Bilbao, Spain
                Author information
                http://orcid.org/0000-0002-7362-6237
                http://orcid.org/0000-0003-2592-9898
                http://orcid.org/0000-0002-0391-6909
                http://orcid.org/0000-0003-0642-7542
                Article
                1777
                10.1038/s41380-022-01777-3
                9763102
                36131044
                83ef0d47-4bc8-4009-af8f-1eaf4d85b5b7
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 April 2022
                : 30 August 2022
                : 2 September 2022
                Funding
                Funded by: National Nature Science Foundation of China (NSFC 32070964 and 31871045). National Key Research and Development Program of China (2021ZD0201703).
                Funded by: National Nature Science Foundation of China (NSFC 81971309 and 32170980). Guangdong Basic and Applied Basic Research Foundation (2019A1515011333). Shenzhen Fundamental Research Program (JCYJ20190809161405495, JCYJ20210324123212035 and RCYX20200714114644167).
                Funded by: Zhejiang Provincial Natural Science Foundation of China (LR19C090001).
                Funded by: National Nature Science Foundation of China (NSFC 31970921 and 31921003). National Key Research and Development Program of China (2021ZD0201703).
                Categories
                Article
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                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                Molecular medicine
                schizophrenia,neuroscience,cell biology
                Molecular medicine
                schizophrenia, neuroscience, cell biology

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