rs11042717 - SBF2

Magnitude 2.2 · 4 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%

• Investigating the shared genetic architecture between adiposity measures and obesity-related cancers - Unknown journal (n.d.) · Unknown authors · PubMed 40874817

  ABSTRACT: Abstract Fat distribution patterns are increasingly linked to obesity-related cancers; however, their shared genetic determinants remain unclear. To identify shared genetic architecture between adiposity measures and obesity-related cancers. Utilizing large-scale summary statistics from genome-wide association study, we conducted genome-wide cross trait analyses of nine adiposity measures [body mass index (BMI), waist-to-hip (WTH) ratio, waist-to-hip ratio adjusted for BMI, arm fat ratio, trunk fat ratio, leg fat ratio, abdominal subcutaneous adipose tissue, gluteofemoral adipose tissue, and visceral adipose tissue] in five obesity-related cancers (colorectal cancer, esophageal adenocarcinoma, breast cancer, endometrial cancer, and ovarian cancer) to characterize their shared gen

• Modeling the genomic architecture of adiposity and anthropometrics across the lifespan - Unknown journal (n.d.) · Unknown authors · PubMed 40796553

  ABSTRACT: Obesity-related conditions are among the leading causes of preventable death and are increasing in prevalence worldwide. Body size and composition are complex traits that are challenging to characterize due to environmental and genetic influences, longitudinal variation, heterogeneity between sexes, and differing health risks based on adipose distribution. Here, we construct a 4-factor genomic structural equation model using 18 measures, unveiling shared and distinct genetic architectures underlying birth size, abdominal size, adipose distribution, and adiposity. Multivariate genome-wide associations reveal the adiposity factor is enriched specifically in neural tissues and pathways, while adipose distribution is enriched more broadly across physiological systems. In addition, po

• The genetic architecture of appendicular lean mass characterized by association analysis in the UK Biobank study - Unknown journal (n.d.) · Unknown authors · PubMed 33097823

  ABSTRACT: Appendicular lean mass (ALM) is a heritable trait associated with loss of lean muscle mass and strength, or sarcopenia, but its genetic determinants are largely unknown. Here we conducted a genome-wide association study (GWAS) with 450,243 UK Biobank participants to uncover its genetic architecture. A total of 1059 conditionally independent variants from 799 loci were identified at the genome-wide significance level (p < 5 × 10−9), all of which were also significant at p < 5 × 10-5 in both sexes. These variants explained ~15.5% of the phenotypic variance, accounting for more than one quarter of the total ~50% GWAS-attributable heritability. There was no difference in genetic effect between sexes or among different age strata. Heritability was enriched in cer

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