rs10417548 - HAS1 - FPR1

Magnitude 2.2 · 2 studies on file

Reported associations

• 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%

• Genomic and transcriptomic analyses of aortic stenosis enhance therapeutic target discovery and disease prediction - Unknown journal (n.d.) · Unknown authors · PubMed 41419686

  ABSTRACT: Aortic stenosis (AS) is a common valvular heart disease and has no pharmacological therapies. We performed a multi-ancestry genome-wide association meta-analysis of 86,864 AS cases among 2,853,408 individuals, discovering 241 autosomal independent risk loci and 3 X chromosome risk loci. We additionally performed sex-stratified and ancestry-stratified genome-wide association studies (GWASs), identifying an additional 5 sex-specific risk loci, 11 risk loci in European ancestry individuals and 1 risk locus in African ancestry individuals. We also performed a transcriptome-wide association study using expression quantitative trait loci from human aortic valves, discovering 54 new genes for which genetically predicted expression influences the risk of AS. We then generated a new polyg

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