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Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis
in
Collaboration
/ Consortia
/ Gene frequency
/ Genome-wide association studies
/ Genomes
/ Heritability
/ Meta-analysis
/ Neuroses
/ Obsessive compulsive disorder
/ Polymorphism
/ Single-nucleotide polymorphism
/ Systematic review
2018
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Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis
by
in
Collaboration
/ Consortia
/ Gene frequency
/ Genome-wide association studies
/ Genomes
/ Heritability
/ Meta-analysis
/ Neuroses
/ Obsessive compulsive disorder
/ Polymorphism
/ Single-nucleotide polymorphism
/ Systematic review
2018
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Do you wish to request the book?
Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis
in
Collaboration
/ Consortia
/ Gene frequency
/ Genome-wide association studies
/ Genomes
/ Heritability
/ Meta-analysis
/ Neuroses
/ Obsessive compulsive disorder
/ Polymorphism
/ Single-nucleotide polymorphism
/ Systematic review
2018
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Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis
Journal Article
Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis
2018
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Overview
Two obsessive-compulsive disorder (OCD) genome-wide association studies (GWASs) have been published by independent OCD consortia, the International Obsessive-Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) and the OCD Collaborative Genetics Association Study (OCGAS), but many of the top-ranked signals were supported in only one study. We therefore conducted a meta-analysis from the two consortia, investigating a total of 2688 individuals of European ancestry with OCD and 7037 genomically matched controls. No single-nucleotide polymorphisms (SNPs) reached genome-wide significance. However, in comparison with the two individual GWASs, the distribution of P-values shifted toward significance. The top haplotypic blocks were tagged with rs4733767 (P=7.1 × 10-7 ; odds ratio (OR)=1.21; confidence interval (CI): 1.12-1.31, CASC8/CASC11), rs1030757 (P=1.1 × 10-6 ; OR=1.18; CI: 1.10-1.26, GRID2) and rs12504244 (P=1.6 × 10-6 ; OR=1.18; CI: 1.11-1.27, KIT). Variants located in or near the genes ASB13, RSPO4, DLGAP1, PTPRD, GRIK2, FAIM2 and CDH20, identified in linkage peaks and the original GWASs, were among the top signals. Polygenic risk scores for each individual study predicted case-control status in the other by explaining 0.9% (P=0.003) and 0.3% (P=0.0009) of the phenotypic variance in OCGAS and the European IOCDF-GC target samples, respectively. The common SNP heritability in the combined OCGAS and IOCDF-GC sample was estimated to be 0.28 (s.e.=0.04). Strikingly, ∼65% of the SNP-based heritability in the OCGAS sample was accounted for by SNPs with minor allele frequencies of [egs]40%. This joint analysis constituting the largest single OCD genome-wide study to date represents a major integrative step in elucidating the genetic causes of OCD.
Publisher
Nature Publishing Group
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