Common variants on chromosome 6p22.1 are associated with schizophrenia

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Abstract

Schizophrenia, a devastating psychiatric disorder, has a prevalence of 0.5–1%, with high heritability (80–85%) and complex transmission. 1 Recent studies implicate rare, large, high-penetrance copy number variants (CNVs) in some cases 2, but it is not known what genes or biological mechanisms underlie susceptibility. Here we show that schizophrenia is significantly associated with single nucleotide polymorphisms (SNPs) in the extended Major Histocompatibility Complex (MHC) region on chromosome 6. We carried out a genome-wide association study (GWAS) of common SNPs in the Molecular Genetics of Schizophrenia (MGS) case-control sample, and then a meta-analysis of data from the MGS, International Schizophrenia Consortium (ISC) and SGENE datasets. No MGS finding achieved genome-wide statistical significance. In the meta-analysis of European-ancestry subjects (8,008 cases, 19,077 controls), significant association with schizophrenia was observed in a region of linkage disequilibrium on chromosome 6p22.1 ( P = 9.54 × 10 ⁻⁹). This region includes a histone gene cluster and several immunity-related genes, possibly implicating etiologic mechanisms involving chromatin modification, transcriptional regulation, auto-immunity and/or infection. These results demonstrate that common schizophrenia susceptibility alleles can be detected. The characterization of these signals will suggest important directions for research on susceptibility mechanisms.

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Most cited references 9

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Copy-number variations associated with neuropsychiatric conditions.

Edwin H Cook, Stephen W Scherer (2008)

Neuropsychiatric conditions such as autism and schizophrenia have long been attributed to genetic alterations, but identifying the genes responsible has proved challenging. Microarray experiments have now revealed abundant copy-number variation--a type of variation in which stretches of DNA are duplicated, deleted and sometimes rearranged--in the human population. Genes affected by copy-number variation are good candidates for research into disease susceptibility. The complexity of neuropsychiatric genetics, however, dictates that assessment of the biomedical relevance of copy-number variants and the genes that they affect needs to be considered in an integrated context.

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Genotype-imputation accuracy across worldwide human populations.

Lucy Huang, Yun Li, Andrew B. Singleton … (2009)

A current approach to mapping complex-disease-susceptibility loci in genome-wide association (GWA) studies involves leveraging the information in a reference database of dense genotype data. By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed and tested for disease association. This imputation strategy has been successful for GWA studies in populations well represented by existing reference panels. We used genotypes at 513,008 autosomal single-nucleotide polymorphism (SNP) loci in 443 unrelated individuals from 29 worldwide populations to evaluate the "portability" of the HapMap reference panels for imputation in studies of diverse populations. When a single HapMap panel was leveraged for imputation of randomly masked genotypes, European populations had the highest imputation accuracy, followed by populations from East Asia, Central and South Asia, the Americas, Oceania, the Middle East, and Africa. For each population, we identified "optimal" mixtures of reference panels that maximized imputation accuracy, and we found that in most populations, mixtures including individuals from at least two HapMap panels produced the highest imputation accuracy. From a separate survey of additional SNPs typed in the same samples, we evaluated imputation accuracy in the scenario in which all genotypes at a given SNP position were unobserved and were imputed on the basis of data from a commercial "SNP chip," again finding that most populations benefited from the use of combinations of two or more HapMap reference panels. Our results can serve as a guide for selecting appropriate reference panels for imputation-based GWA analysis in diverse populations.

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The genetics of multiple sclerosis: SNPs to pathways to pathogenesis.

Stephen L. Hauser, Stephen J Sawcer, Jorge Oksenberg … (2008)

Multiple sclerosis (MS) is an autoimmune demyelinating disease and a common cause of neurological disability in young adults. The modest heritability of MS reflects complex genetic effects and multifaceted gene-environment interactions. The human leukocyte antigen (HLA) region is the strongest susceptibility locus for MS, but a genome-wide association study recently identified new susceptibility genes. Progress in high-throughput genotyping and sequencing technologies and a better understanding of the structural organization of the human genome, together with powerful brain-imaging techniques that refine the phenotype, suggest that the tools could finally exist to identify the full set of genes influencing the pathogenesis of MS.

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Author and article information

Journal

Journal ID (nlm-journal-id): 0410462

Journal ID (pubmed-jr-id): 6011

Journal ID (nlm-ta): Nature

Title: Nature

ISSN (Print): 0028-0836

ISSN (Electronic): 1476-4687

Publication date Nihms-submitted: 9 July 2009

Publication date (Electronic): 1 July 2009

Publication date (Print): 6 August 2009

Publication date PMC-release: 7 February 2010

Volume: 460

Issue: 7256

Pages: 753-757

Affiliations

[1 ]Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94304, USA

[2 ]Center for Psychiatric Genetics, NorthShore University HealthSystem Research Institute, Evanston, Illinois 60201, USA

[3 ]Department of Computer Science, Columbia University, New York, New York 10027, USA

[4 ]Medical Research Council-Biostatistics Unit, Institute of Public Health, Cambridge CB2 2SR, UK

[5 ]Biostatistics and Bioinformatics Unit, Cardiff University, Cardiff CF14 4NX, UK

[6 ]Department of Health Research and Policy, Stanford University, Stanford, California 94304, USA

[7 ]Queensland Centre for Mental Health Research, and Queensland Institute for Medical Research, Brisbane, Queensland 4072, Australia

[8 ]Department of Psychiatry, University of Colorado Denver, Aurora, Colorado 80045, USA

[9 ]Department of Psychiatry and Behavioral Sciences, Atlanta Veterans Affairs Medical Center, and Emory University, Atlanta, Georgia 30322, USA

[10 ]Department of Psychiatry, Washington University, St. Louis, Missouri 63110, USA

[11 ]Department of Psychiatry, Mount Sinai School of Medicine, New York, New York 10029, USA

[12 ]School of Nursing, Louisiana State University Health Sciences Center, New Orleans, Louisiana 70112, USA

[13 ]Departments of Psychiatry, and Neurology, University of California at San Francisco, San Francisco, California 94143, USA

[14 ]Mental Health Clinical Research Center, and Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa 52242, USA

[15 ]Department of Neurology, School of Medicine, University of California at San Francisco, 513 Parnassus Avenue, San Francisco, California 94143, USA

[16 ]Center for Genotyping and Analysis, Broad Institute of Massachusetts Institute of Technology & Harvard University, Cambridge, Massachusetts 02142, USA

[17 ]Departments of Psychiatry, and Human Genetics, Virginia Commonwealth University, Richmond, Virginia 23298, USA

Author notes

Correspondence and requests for materials should be addressed to P.V.G. ( pgejman@ 123456mac.com )

Article

Manuscript ID: nihpa123666

DOI: 10.1038/nature08192

PMC ID: 2775422

PubMed ID: 19571809

SO-VID: 163e3938-9935-468a-bb6e-5d925b291be4