rs10181342 - GCKR - SPATA31H1

Magnitude 2.2 · 4 studies on file

Reported associations

• Genetic Determinants of Clustering of Cardiometabolic Risk Factors in U.K. Biobank. - Metabolic syndrome and related disorders (2021) · Lind L · PubMed 31928498

  The metabolic syndrome (MetS) is a description of a clustering of cardiometabolic risk factors in the same individual. This study searched for genetic loci associated with all five prespecified components of MetS to find a common pathophysiological link for this risk factor clustering. Using data from 291,107 individuals in the U.K. biobank, a genome-wide association study (GWAS) was performed versus each of the five components of the syndrome as continuous variables (glucose, systolic blood pressure, triglycerides, waist circumference, and high-density lipoprotein-cholesterol). Using false discovery rate <0.05, three loci were related to all five MetS components (rs7575523; nearest gene , rs3936511; intron of , and rs111970447; intron of ). Of those, seems the most interesting candidate f

• 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%

• Genomics and phenomics of body mass index reveals a complex disease network - Unknown journal (n.d.) · Unknown authors · PubMed 36581621

  ABSTRACT: Elevated body mass index (BMI) is heritable and associated with many health conditions that impact morbidity and mortality. The study of the genetic association of BMI across a broad range of common disease conditions offers the opportunity to extend current knowledge regarding the breadth and depth of adiposity-related diseases. We identify 906 (364 novel) and 41 (6 novel) genome-wide significant loci for BMI among participants of European (N~1.1 million) and African (N~100,000) ancestry, respectively. Using a BMI genetic risk score including 2446 variants, 316 diagnoses are associated in the Million Veteran Program, with 96.5% showing increased risk. A co-morbidity network analysis reveals seven disease communities containing multiple interconnected diseases associated with BMI

• GWAS and multi-omics integrative analysis reveal novel loci and their molecular mechanisms for circulating fatty acids - Unknown journal (n.d.) · Unknown authors · PubMed 40545721

  ABSTRACT: Summary Previous genome-wide association studies (GWAS) have identified genetic loci associated with the circulating levels of fatty acids (FAs), but the biological mechanisms of these genetic associations remain largely unexplored. Here, we conducted GWAS to identify additional genetic loci for 19 circulating FA traits in UK Biobank participants of European ancestry (n = 239,268) and five other ancestries (n = 508-4,663). We leveraged the GWAS findings to characterize genetic correlations and colocalized regions among FAs, explore sex differences, examine FA loci influenced by lipoprotein metabolism, and apply statistical fine-mapping to pinpoint putative causal variants. We integrated GWAS signals with multi-omics quantitative trait loci (QTL) to reveal intermediate molecular

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