Expressive

rs111640872 - C19orf12 - CCNE1

Magnitude 2.2 · 3 studies on file

Reported associations

  • Body surface area is a potential obesity index: Its genetic determination and its causality for later-life diseases. - Obesity (Silver Spring, Md.) (2022) · Yu XH, Cao RR, Yang YQ, Deng FY, Bo L, Lei SF · PubMed 36502284

    This study aimed to identify novel genetic factors that contribute to body surface area (BSA) and explore its relationship with complex traits and diseases. Based on more than 330,000 European individuals in the UK Biobank, the first large-scale genome-wide association study for BSA was performed. Comprehensive genetic analysis and enrichment analysis were then performed to explore the biological function of the identified loci. The genetic correlations and causal associations between BSA and other anthropometry parameters, early growth indices, and later-life diseases, respectively, were assessed by complex genetic approaches. Genome-wide association study analysis identified a total of 456 conditionally independent single-nucleotide polymorphism mapping genes with known functions in the

  • 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%

  • Multi-trait GWAS for diverse ancestries: mapping the knowledge gap - Unknown journal (n.d.) · Unknown authors · PubMed 38627641

    ABSTRACT: Background Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores. Methods Here, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits acro

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