Expressive

rs11160190 - SERPINA12 - SERPINA4

Magnitude 2.2 · 2 studies on file

Reported associations

  • Genetic variation in the vaspin gene affects circulating serum vaspin concentrations. - International journal of obesity (2005) (2014) · Breitfeld J, Tönjes A, Böttcher Y, Schleinitz D, Wiele N, Marzi C, Brockhaus C, Rathmann W, Huth C, Grallert H, Illig T, Blüher M, Kovacs P, Stumvoll M · PubMed 22907691

    Visceral adipose tissue-derived serine protease inhibitor (vaspin) is an adipokine potentially linking obesity, insulin resistance and type 2 diabetes. Here, we searched for genetic determinants that could explain the variability in serum vaspin concentrations. First, we conducted a genome-wide association study (GWAS) for serum vaspin in the Sorbs cohort (N=826). Subsequently, 26 single-nucleotide polymorphisms (SNPs) covering genetic variation in the vaspin locus were genotyped in the Sorbs. In addition, we measured serum vaspin concentrations in 1806 samples from Augsburg/the Cooperative Health Research in the Region of Augsburg (KORA) for replication of the association signals. Finally, we conducted association analyses of vaspin SNPs with metabolic traits in the Sorbs (N=1013), KORA (

  • 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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