Expressive

rs11079419 - BCAS3

Magnitude 2.2 · 2 studies on file

Reported associations

  • Genome-wide association analysis of 95 549 individuals identifies novel loci and genes influencing optic disc morphology. - Human molecular genetics (2020) · Han X, Qassim A, An J, Marshall H, Zhou T, Ong JS, Hassall MM, Hysi PG, Foster PJ, Khaw PT, Mackey DA, Gharahkhani P, Khawaja AP, Hewitt AW, Craig JE, MacGregor S · PubMed 31809533

    Optic nerve head morphology is affected by several retinal diseases. We measured the vertical optic disc diameter (DD) of the UK Biobank (UKBB) cohort (N = 67 040) and performed the largest genome-wide association study (GWAS) of DD to date. We identified 81 loci (66 novel) for vertical DD. We then replicated the novel loci in International Glaucoma Genetic Consortium (IGGC, N = 22 504) and European Prospective Investigation into Cancer-Norfolk (N = 6005); in general the concordance in effect sizes was very high (correlation in effect size estimates 0.90): 44 of the 66 novel loci were significant at P < 0.05, with 19 remaining significant after Bonferroni correction. We identified another 26 novel loci in the meta-analysis of UKBB and IGGC data. Gene-based analyses iden

  • A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286

    ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

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