rs117098605 - PRND - PRNT

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%

• Genome-wide associations of human gut microbiome variation and implications for causal inference analyses - Unknown journal (n.d.) · Unknown authors · PubMed 32572223

  ABSTRACT: Recent population-based and clinical studies have identified a range of factors associated with human gut microbiome variation. Murine quantitative trait loci, human twin studies and microbiome genome-wide association studies (mGWAS) have provided evidence for genetic contributions to microbiome composition. Despite this, there is still poor overlap in genetic association across human studies. Using appropriate taxon-specific models along with support from independent cohorts, we show association between human host genotype and gut microbiome variation. We also suggest that interpretation of applied analyses using genetic associations is complicated by the likely overlap between genetic contributions and heritable components of host environment. Using fecal derived 16S rRNA gene

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