62
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found

      Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia

      research-article
      1 , 2 , 3 , 4 , 5 , 6 , 2 , Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Cross-Disorder Working Group of the Psychiatric Genomics Consortium, 7 , 8 , 9 , 9 , 10 , 11 ,   12 , 10 , 13 , 12 , 14 , 15 , 16 , 9 , 17 , 18 ,   9 , 19 , 1 , 4 , 20
      Molecular psychiatry

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Bipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but diagnostic and molecular distinctions still remain. Here, we perform a combined GWAS of 19,779 BP and SCZ cases versus 19,423 controls, in addition to a direct comparison GWAS of 7,129 SCZ cases versus 9,252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance ( CACNA1C, IFI44L, MHC, TRANK1, MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.

          Related collections

          Most cited references52

          • Record: found
          • Abstract: found
          • Article: not found

          PLINK: a tool set for whole-genome association and population-based linkage analyses.

          Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The positive and negative syndrome scale (PANSS) for schizophrenia.

            The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10.

              The Mini-International Neuropsychiatric Interview (M.I.N.I.) is a short structured diagnostic interview, developed jointly by psychiatrists and clinicians in the United States and Europe, for DSM-IV and ICD-10 psychiatric disorders. With an administration time of approximately 15 minutes, it was designed to meet the need for a short but accurate structured psychiatric interview for multicenter clinical trials and epidemiology studies and to be used as a first step in outcome tracking in nonresearch clinical settings. The authors describe the development of the M.I.N.I. and its family of interviews: the M.I.N.I.-Screen, the M.I.N.I.-Plus, and the M.I.N.I.-Kid. They report on validation of the M.I.N.I. in relation to the Structured Clinical Interview for DSM-III-R, Patient Version, the Composite International Diagnostic Interview, and expert professional opinion, and they comment on potential applications for this interview.
                Bookmark

                Author and article information

                Journal
                9607835
                20545
                Mol Psychiatry
                Mol. Psychiatry
                Molecular psychiatry
                1359-4184
                1476-5578
                15 November 2013
                26 November 2013
                September 2014
                01 March 2015
                : 19
                : 9
                : 1017-1024
                Affiliations
                [1 ]Division of Psychiatric Genomics, Department of Psychiatry, Mount Sinai School of Medicine, New York, New York, USA
                [2 ]Washington DC VA Medical Center, Washington DC, USA
                [3 ]Department of Psychiatry, Georgetown University School of Medicine, Washington, DC, USA
                [4 ]Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA
                [5 ]Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
                [6 ]Molecular Psychiatry Laboratory, Research Department of Mental Health Sciences, University College London Medical School, Windeyer Institute of Medical Sciences, London, England, UK
                [7 ]Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem and University of Chicago, Evanston, Illinois, USA
                [8 ]MRC Centre for Neuropsychiatric Genetics and Genomics, Department of Psychological Medicine and Neurology, School of Medicine, Cardiff University, Cardiff, Wales, UK
                [9 ]KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
                [10 ]Department of Medical Epidemiology and Biostatistics; Karolinska Institutet; Stockholm; Sweden
                [11 ]Department of Psychiatry, University of California San Diego, La Jolla, California, USA; Department of Psychiatry, Special Treatment and Evaluation Program (STEP), Veterans Affairs San Diego Healthcare System, San Diego, California, USA
                [12 ]INSERM, U955, Psychiatrie Géné que; Université Paris Est, Faculté de Médecine, Assistance Publique–Hôpitaux de Paris (AP -HP); Hôpital H. Mondor–A. Chenevier, Département de Psychiatrie; ENBREC group; Fondation Fondamental, Créteil; France
                [13 ]Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
                [14 ]Department of Psychiatry, WPIC, University of Pittsburgh School of Medicine. Pittsburgh, Pennsylvania, USA
                [15 ]Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
                [16 ]Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital; Stanley Center for Psychiatric Research, Broad Institute, Boston, MA, USA
                [17 ]Neuropsychiatric Genetics Research Group, Department of Psychiatry and Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland
                [18 ]Department of Genetics, University of North Carolina at Chapel Hill, USA
                [19 ]Biostatistics and Bioinformatics Unit, Cardiff University School of Medicine, Cardiff, UK
                [20 ]Virginia Institute for Psychiatric and Behavioral Genetics; Department of Human and Molecular Genetics, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA
                Author notes
                Corresponding authors: Kenneth S. Kendler and Pamela Sklar
                [+]

                Individual members are listed in the supplementary material

                Article
                NIHMS523069
                10.1038/mp.2013.138
                4033708
                24280982
                d881499a-8abf-4607-882c-b55cce9aff3b

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Categories
                Article

                Molecular medicine
                Molecular medicine

                Comments

                Comment on this article