Expressive

rs10960276 - LINC03131 - JKAMPP1

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%

  • Use of genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomisation study - Unknown journal (n.d.) · Unknown authors · PubMed 32376654

    ABSTRACT: Abstract Objective To evaluate whether body size in early life has an independent effect on risk of disease in later life or whether its influence is mediated by body size in adulthood. Design Two sample univariable and multivariable mendelian randomisation. Setting The UK Biobank prospective cohort study and four large scale genome-wide association studies (GWAS) consortiums. Participants 453 169 participants enrolled in UK Biobank and a combined total of more than 700 000 people from different GWAS consortiums. Exposures Measured body mass index during adulthood (mean age 56.5) and self-reported perceived body size at age 10. Main outcome measures Coronary artery disease, type 2 diabetes, breast cancer, and prostate cancer. Results Having a larger genetically predicted body

Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.