Expressive

rs11741656 - NR3C1 - RNU7-156P

Magnitude 2.2 · 2 studies on file

Reported associations

  • Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program - Unknown journal (n.d.) · Unknown authors · PubMed 39024449

    ABSTRACT: INTRODUCTION: Findings from genome-wide association studies (GWASs) have provided foundational knowledge of the genetic basis of disease, facilitating precision approaches for prevention and treatment. Current GWAS results are limited by underrepresentation of individuals from diverse populations, leading to concerns with generalizability regarding our knowledge of the relationships between genes, traits, and disease. The Department of Veterans Affairs (VA) Million Veteran Program (MVP), one of the largest US-based biobanks, addresses this need; 29% of MVP comprises individuals genetically similar to African (AFR), Admixed American (AMR), and East Asian (EAS) reference populations. With over 635,000 participants and more than 44.3M genotyped variants linked with detailed phenotyp

  • 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.