rs11725517 - NR3C2

Magnitude 2.2 · 3 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 pleiotropy analysis identifies novel blood pressure variants and improves its polygenic risk scores - Unknown journal (n.d.) · Unknown authors · PubMed 34989438

    ABSTRACT: Abstract Systolic and diastolic blood pressure (S/DBP) are highly correlated modifiable risk factors for cardiovascular disease (CVD). We report here a bidirectional Mendelian Randomization (MR) and horizontal pleiotropy analysis of S/DBP summary statistics from the UK Biobank (UKB)‐International Consortium for Blood Pressure (ICBP) (UKB‐ICBP) BP genome‐wide association study and construct a composite genetic risk score (GRS) by including pleiotropic variants. The composite GRS captures greater (1.11-3.26 fold) heritability for BP traits and increases (1.09‐ and 2.01‐fold) Nagelkerke's R 2 for hypertension and CVD. We replicated 118 novel BP horizontal pleiotropic variants including 18 novel BP loci using summary statistics from the Million Veteran Program (MVP) study

  • Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation - Unknown journal (n.d.) · Unknown authors · PubMed 40645996

    ABSTRACT: Atrial fibrillation (AF) is a common cardiac arrhythmia with strong genetic components, yet its underlying molecular mechanisms and potential therapeutic targets remain incompletely understood. We conducted a cross-population genome-wide meta-analysis of 252,438 AF cases and identified 525 loci that met genome-wide significance. Two loci of PITX2 and ZFHX3 genes were identified as shared across populations of different ancestries. Comprehensive gene prioritization approaches reinforced the role of muscle development and heart contraction while also uncovering additional pathways, including cellular response to transforming growth factor-beta. Population-specific genetic correlations uncovered common and unique circulatory comorbidities between Europeans and Africans. Mendelian ra


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

Lifestyle context

Concrete actions anchored to the cited research. We do not prescribe, we describe.

Screening

  • Atrial fibrillation screening Moderate

    Mineralocorticoid receptor variant associated with increased atrial fibrillation risk via aldosterone-mediated electrolyte and blood pressure effects

  • Blood pressure monitoring Moderate

    Mineralocorticoid receptor regulates aldosterone-mediated sodium reabsorption and potassium excretion affecting systemic blood pressure