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      A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia

      1 , 1 , 2 , 1 , 3 , 1 , 1 , 1 , 4 , 5 , 6 , 7 , 5 , 8 , 9 , 10 , 11 , 11 , 4 , 12 , 13 , 13 , 14 , 15 , 16 , 16 , 17 , 16 , 18 , 19 , 19 , 13 , 9 , 1 , *

      PLoS Genetics

      Public Library of Science

          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.


          We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater “load” of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.

          Author Summary

          Schizophrenia is a highly heritable disease. While the drugs commonly used to treat schizophrenia offer important relief from some symptoms, other symptoms are not well treated, and the drugs cause serious adverse effects in many individuals. This has fueled intense interest over the years in identifying genetic contributors to schizophrenia. In this paper, we first show that common genetic variants, the focus of most research until recently, do not seem to have a major impact on schizophrenia predisposition. We then provide further evidence that very rare, large DNA deletions and duplications contribute to or explain a minority of schizophrenia cases. Although the small number of events identified here do not restrict focus to a finite set of molecular pathways, we do show one event that deletes a gene known to interact with DISC1, a gene known to cause psychiatric problems in one family. Such convergent findings have potential implications for the development of new therapies and patient subclassifications. We conclude that schizophrenia genetics research must turn sharply toward the identification of rare genetic contributors and that the most important tool in this effort will be complete whole-genome sequencing of patients whose clinical characteristics have been very thoroughly assessed.

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          Most cited references 47

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          Genome-wide association studies for complex traits: consensus, uncertainty and challenges.

          The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
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            A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer.

            We conducted a genome-wide association study (GWAS) of breast cancer by genotyping 528,173 SNPs in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls. We identified four SNPs in intron 2 of FGFR2 (which encodes a receptor tyrosine kinase and is amplified or overexpressed in some breast cancers) that were highly associated with breast cancer and confirmed this association in 1,776 affected individuals and 2,072 controls from three additional studies. Across the four studies, the association with all four SNPs was highly statistically significant (P(trend) for the most strongly associated SNP (rs1219648) = 1.1 x 10(-10); population attributable risk = 16%). Four SNPs at other loci most strongly associated with breast cancer in the initial GWAS were not associated in the replication studies. Our summary results from the GWAS are available online in a form that should speed the identification of additional risk loci.
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              Association between microdeletion and microduplication at 16p11.2 and autism.

              Autism spectrum disorder is a heritable developmental disorder in which chromosomal abnormalities are thought to play a role. As a first component of a genomewide association study of families from the Autism Genetic Resource Exchange (AGRE), we used two novel algorithms to search for recurrent copy-number variations in genotype data from 751 multiplex families with autism. Specific recurrent de novo events were further evaluated in clinical-testing data from Children's Hospital Boston and in a large population study in Iceland. Among the AGRE families, we observed five instances of a de novo deletion of 593 kb on chromosome 16p11.2. Using comparative genomic hybridization, we observed the identical deletion in 5 of 512 children referred to Children's Hospital Boston for developmental delay, mental retardation, or suspected autism spectrum disorder, as well as in 3 of 299 persons with autism in an Icelandic population; the deletion was also carried by 2 of 18,834 unscreened Icelandic control subjects. The reciprocal duplication of this region occurred in 7 affected persons in AGRE families and 4 of the 512 children from Children's Hospital Boston. The duplication also appeared to be a high-penetrance risk factor. We have identified a novel, recurrent microdeletion and a reciprocal microduplication that carry substantial susceptibility to autism and appear to account for approximately 1% of cases. We did not identify other regions with similar aggregations of large de novo mutations. Copyright 2008 Massachusetts Medical Society.

                Author and article information

                Role: Editor
                PLoS Genet
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                February 2009
                February 2009
                6 February 2009
                : 5
                : 2
                [1 ]Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, United States of America
                [2 ]Department of Medical and Molecular Genetics, King's College London, Guy's Hospital, London, United Kingdom
                [3 ]Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, United States of America
                [4 ]Institute of Neurology, University College London, London, United Kingdom
                [5 ]Genetic Unit, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
                [6 ]Department of Biomedical Science and Biotech, University of Brescia, Brescia, Italy
                [7 ]Division of Neurology, Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America
                [8 ]Psychiatric Unit, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
                [9 ]Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
                [10 ]University Hospitals Case Medical Center, Cleveland, Ohio, United States of America
                [11 ]Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, North Carolina, United States of America
                [12 ]Genetics Division, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America
                [13 ]Division of Molecular and Clinical Neurobiology, Department of Psychiatry, Ludwig-Maximilians-University, Munich, Germany
                [14 ]Department of Psychiatry, Ludwig-Maximilians-University, Munich, Germany
                [15 ]Genetics Research Centre GmbH (GRC), Munich, Germany
                [16 ]Department of Mental Health, University of Aberdeen, Aberdeen, United Kingdom
                [17 ]Division of Neuroscience and Mental Health, Neuroscience Laboratories, Burlington Danes, Hammersmith Hospital, London, United Kingdom
                [18 ]Deane Drug Discovery Institute, Duke University Medical Center, Durham, North Carolina, United States of America
                [19 ]Medical Genetics, GlaxoSmithKline R&D, Verona, Italy
                Oxford Centre for Diabetes, Endocrinology, and Metabolism and Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom
                Author notes

                Conceived and designed the experiments: ACN DG DBG. Performed the experiments: ACN DG ELH KVS WY DK. Analyzed the data: ACN DG MEW SF. Contributed reagents/materials/analysis tools: DG JM SF MG WJS CB GR KJ PAC JPM RSEK EMCF PLSJ IG AMH HJM AR GF CC LTM DSC ADR PM CF DR HYM. Wrote the paper: ACN DG MEW HYM DBG.

                Need et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 19
                Research Article
                Genetics and Genomics/Complex Traits
                Genetics and Genomics/Genetics of Disease
                Genetics and Genomics/Medical Genetics



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