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      A transcriptome-wide association study implicates specific pre- and post-synaptic abnormalities in schizophrenia

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          Abstract

          Schizophrenia is a complex highly heritable disorder. Genome-wide association studies (GWAS) have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. We identify a significant correlation between schizophrenia risk and expression at 89 genes in the dorsolateral prefrontal cortex ( P ≤ 9.43 × 10 −6), including 20 novel genes. Genes whose expression correlate with schizophrenia were enriched for those involved in abnormal CNS synaptic transmission ( P FDR = 0.02) and antigen processing and presentation of peptide antigen via MHC class I ( P FDR = 0.02). Within the CNS synaptic transmission set, we identify individual significant candidate genes to which we assign direction of expression changes in schizophrenia. The findings provide strong candidates for experimentally probing the molecular basis of synaptic pathology in schizophrenia.

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          Most cited references31

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          Cortical inhibitory neurons and schizophrenia.

          Impairments in certain cognitive functions, such as working memory, are core features of schizophrenia. Convergent findings indicate that a deficiency in signalling through the TrkB neurotrophin receptor leads to reduced GABA (gamma-aminobutyric acid) synthesis in the parvalbumin-containing subpopulation of inhibitory GABA neurons in the dorsolateral prefrontal cortex of individuals with schizophrenia. Despite both pre- and postsynaptic compensatory responses, the resulting alteration in perisomatic inhibition of pyramidal neurons contributes to a diminished capacity for the gamma-frequency synchronized neuronal activity that is required for working memory function. These findings reveal specific targets for therapeutic interventions to improve cognitive function in individuals with schizophrenia.
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            Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder

            Most genetic risk for psychiatric disease lies in regulatory regions, implicating pathogenic dysregulation of gene expression and splicing. However, comprehensive assessments of transcriptomic organization in diseased brains are limited. In this work, we integrated genotypes and RNA sequencing in brain samples from 1695 individuals with autism spectrum disorder (ASD), schizophrenia, and bipolar disorder, as well as controls. More than 25% of the transcriptome exhibits differential splicing or expression, with isoform-level changes capturing the largest disease effects and genetic enrichments. Coexpression networks isolate disease-specific neuronal alterations, as well as microglial, astrocyte, and interferon-response modules defining previously unidentified neural-immune mechanisms. We integrated genetic and genomic data to perform a transcriptome-wide association study, prioritizing disease loci likely mediated by cis effects on brain expression. This transcriptome-wide characterization of the molecular pathology across three major psychiatric disorders provides a comprehensive resource for mechanistic insight and therapeutic development.
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              Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

              Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.
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                Author and article information

                Journal
                Hum Mol Genet
                Hum. Mol. Genet
                hmg
                Human Molecular Genetics
                Oxford University Press
                0964-6906
                1460-2083
                01 January 2020
                06 November 2019
                06 November 2019
                : 29
                : 1
                : 159-167
                Affiliations
                [1 ] MRC Centre for Neuropsychiatric Genetics and Genomics , Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff CF24 4HQ, UK
                [2 ] Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London , London SE5 8AF, UK
                Author notes
                To whom correspondence should be addressed at: MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Cardiff CF24 4HQ, UK. Tel: +44 (0)29 2068 8320; Email: owenmj@ 123456cardiff.ac.uk
                Article
                ddz253
                10.1093/hmg/ddz253
                7416679
                31691811
                6df0f7d2-2430-4156-9de2-fbbff9fcde5b
                © The Author(s) 2019. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 7 May 2019
                : 31 August 2019
                : 2 September 2019
                Page count
                Pages: 9
                Funding
                Funded by: Medical Research Council 10.13039/501100000265
                Award ID: MR/L010305/1
                Award ID: G0800509
                Award ID: MR/L011794/1
                Award ID: MR/L010674/2
                Funded by: National Institute of Mental Health 10.13039/100000025
                Funded by: Psychiatric Genomics Consortium
                Award ID: 5U01MH109514-02
                Categories
                Association Studies Article

                Genetics
                Genetics

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