Expressive

rs11170820 - FLJ12825, FAM242C

Magnitude 2.2 · 4 studies on file

Reported associations

  • Identification of 64 Novel Genetic Loci Provides an Expanded View on the Genetic Architecture of Coronary Artery Disease - Unknown journal (n.d.) · Unknown authors · PubMed 29212778

    ABSTRACT: Supplemental Digital Content is available in the text. Rationale: Coronary artery disease (CAD) is a complex phenotype driven by genetic and environmental factors. Ninety-seven genetic risk loci have been identified to date, but the identification of additional susceptibility loci might be important to enhance our understanding of the genetic architecture of CAD. Objective: To expand the number of genome-wide significant loci, catalog functional insights, and enhance our understanding of the genetic architecture of CAD. Methods and Results: We performed a genome-wide association study in 34 541 CAD cases and 261 984 controls of UK Biobank resource followed by replication in 88 192 cases and 162 544 controls from CARDIoGRAMplusC4D. We identified 75 loci that replicated and

  • Multi‐phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations - Unknown journal (n.d.) · Unknown authors · PubMed 35285134

    ABSTRACT: Abstract Background Multi‐phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods Summary statistics from genome wide‐association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI

  • Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants - Unknown journal (n.d.) · Unknown authors · PubMed 36474045

    ABSTRACT: The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We priorit

  • Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies - Unknown journal (n.d.) · Unknown authors · PubMed 30104761

    ABSTRACT: In genome-wide association studies (GWAS) for thousands of phenotypes in large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, linear mixed model and the recently proposed logistic mixed model, perform poorly - producing large type I error rates - in the analysis of unbalanced case-control phenotypes. Here we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation to calibrate the distribution of score test statistics. This method, SAIGE, provides accurate p-values even when case-control ratios are extremely unbalanced. It utilizes state-of-art optimization strategies to reduce computational cost, and hence is applicable to GWAS for thousands of phenotypes by la

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