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Mol Psychiatry. 2014 Sep;19(9):1017-1024. doi: 10.1038/mp.2013.138. Epub 2013 Nov 26.

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

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Division of Psychiatric Genomics, Department of Psychiatry, Mount Sinai School of Medicine, New York, New York, USA.
Washington DC VA Medical Center, Washington DC, USA.
Department of Psychiatry, Georgetown University School of Medicine, Washington, DC, USA.
Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA.
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.
Molecular Psychiatry Laboratory, Research Department of Mental Health Sciences, University College London Medical School, Windeyer Institute of Medical Sciences, London, England, UK.
Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem and University of Chicago, Evanston, Illinois, USA.
MRC Centre for Neuropsychiatric Genetics and Genomics, Department of Psychological Medicine and Neurology, School of Medicine, Cardiff University, Cardiff, Wales, UK.
KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Department of Medical Epidemiology and Biostatistics; Karolinska Institutet; Stockholm; Sweden.
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.
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.
Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden.
Department of Psychiatry, WPIC, University of Pittsburgh School of Medicine. Pittsburgh, Pennsylvania, USA.
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital; Stanley Center for Psychiatric Research, Broad Institute, Boston, MA, USA.
Neuropsychiatric Genetics Research Group, Department of Psychiatry and Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland.
Department of Genetics, University of North Carolina at Chapel Hill, USA.
Biostatistics and Bioinformatics Unit, Cardiff University School of Medicine, Cardiff, UK.
Virginia Institute for Psychiatric and Behavioral Genetics; Department of Human and Molecular Genetics, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA.
Contributed equally


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 genome-wide association study (GWAS) of 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and 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.

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