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      De novo mutations identified by exome sequencing implicate rare missense variants in SLC6A1 in schizophrenia

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          Abstract

          Schizophrenia is a highly polygenic disorder with important contributions from both common and rare risk alleles. We analysed exome-sequencing data for de novo variants (DNVs) in a new sample of 613 schizophrenia trios, and combined this with published data for a total of 3,444 trios. In our new data, loss-of-function (LoF) DNVs were significantly enriched among 3,471 LoF intolerant genes, supporting previous findings. In the full dataset, genes associated with neurodevelopmental disorders (n=159) were significantly enriched for LoF DNVs. Within these neurodevelopmental disorder genes, SLC6A1, encoding a gamma-aminobutyric acid transporter, was associated with missense-damaging DNVs. In 1,122 trios for which we had genome-wide common variant data, schizophrenia and bipolar disorder polygenic risk were significantly over-transmitted to probands. Probands carrying LoF or deletion DNVs in LoF intolerant or neurodevelopmental disorder genes had significantly less over-transmission of schizophrenia polygenic risk than non-carriers, providing robust support for these DNVs increasing liability to schizophrenia.

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          Common genetic variants contribute to risk of rare severe neurodevelopmental disorders

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            A polygenic theory of schizophrenia.

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              Is Open Access

              Genotype harmonizer: automatic strand alignment and format conversion for genotype data integration

              Background To gain statistical power or to allow fine mapping, researchers typically want to pool data before meta-analyses or genotype imputation. However, the necessary harmonization of genetic datasets is currently error-prone because of many different file formats and lack of clarity about which genomic strand is used as reference. Findings Genotype Harmonizer (GH) is a command-line tool to harmonize genetic datasets by automatically solving issues concerning genomic strand and file format. GH solves the unknown strand issue by aligning ambiguous A/T and G/C SNPs to a specified reference, using linkage disequilibrium patterns without prior knowledge of the used strands. GH supports many common GWAS/NGS genotype formats including PLINK, binary PLINK, VCF, SHAPEIT2 & Oxford GEN. GH is implemented in Java and a large part of the functionality can also be used as Java ‘Genotype-IO’ API. All software is open source under license LGPLv3 and available from http://www.molgenis.org/systemsgenetics. Conclusions GH can be used to harmonize genetic datasets across different file formats and can be easily integrated as a step in routine meta-analysis and imputation pipelines.
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                Author and article information

                Journal
                9809671
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                23 November 2019
                13 January 2020
                February 2020
                13 July 2020
                : 23
                : 2
                : 179-184
                Affiliations
                [1 ]MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
                [2 ]Department of Psychiatry and Psychotherapy, University of Würzburg, Germany
                [3 ]Clinical Genetics Laboratory, Mental Health Research Centre, Moscow, Russia
                [4 ]Child and Adolescent Psychiatry Department, Hospital General Universitario Gregorio Marañón, IisGM, School of Medicine, Universidad Complutense, CIBERSAM, Madrid, Spain
                Author notes
                [* ] Corresponding authors: Professor Michael J Owen, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, Wales, UK. CF24 4HQ. owenmj@ 123456cardiff.ac.uk , Phone: +44 (0) 29 2068 8320; Professor Michael C O’Donovan, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, Wales, UK. CF24 4HQ. odonovanmc@ 123456cardiff.ac.uk , Phone: +44 (0)29 2068 8320
                [5]

                A full list of authors can be found at the end of the article.

                Article
                EMS85023
                10.1038/s41593-019-0565-2
                7007300
                31932766
                df283da0-f2a6-4181-b2c9-3a3c85ae9cba

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                Neurosciences
                Neurosciences

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