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Genome-wide association study identifies five new schizophrenia loci

Stephan Ripke, +210 more
- 01 Oct 2011 - 
- Vol. 43, Iss: 10, pp 969-976
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TLDR
The authors examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects.
Abstract
We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 x 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 x 10(-9)), ANK3 (rs10994359, P = 2.5 x 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 x 10(-9)).

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Genome-wide DNA methylation analysis of heavy cannabis exposure in a New Zealand longitudinal cohort.

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TL;DR: This work uses schizophrenia, a disorder characterized by dysconnectivity, to demonstrate how the brainnetome concept can be applied to the study of psychiatric disorders, and reviews studies of abnormal brain networks in schizophrenia that are based on single regions of interest.
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An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies.

TL;DR: A scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics is proposed and concludes that, despite having very similar estimates of variance explained by genotyped SNPs, CD and SZ have a broadly dissimilar genetic architecture, due to differing mean effect size and proportion of non-null loci.
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Preliminary evidence for association of genetic variants in pri-miR-34b/c and abnormal miR-34c expression with attention deficit and hyperactivity disorder.

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Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Shaun Purcell, +81 more
- 06 Aug 2009 - 
TL;DR: The extent to which common genetic variation underlies the risk of schizophrenia is shown, using two analytic approaches, and the major histocompatibility complex is implicate, which is shown to involve thousands of common alleles of very small effect.
Journal ArticleDOI

Common SNPs explain a large proportion of the heritability for human height

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