Expressive

rs113086489 - Y_RNA - SLC2A4

Magnitude 2.2 · 4 studies on file

Reported associations

  • A cross-population atlas of genetic associations for 220 human phenotypes. - Nature genetics (2021) · Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, Narita A, Konuma T, Yamamoto K, Akiyama M, Ishigaki K, Suzuki A, Suzuki K, Obara W, Yamaji K, Takahashi K, Asai S, Takahashi Y, Suzuki T, Shinozaki N, Yamaguchi H, Minami S, Murayama S, Yoshimori K, Nagayama S, Obata D, Higashiyama M, Masumoto A, Koretsune Y, Ito K, Terao C, Yamauchi T, Komuro I, Kadowaki T, Tamiya G, Yamamoto M, Nakamura Y, Kubo M, Murakami Y, Yamamoto K, Kamatani Y, Palotie A, Rivas MA, Daly MJ, Matsuda K, Okada Y · PubMed 34594039

    Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wid

  • 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 associations for birth weight and correlations with adult disease - Unknown journal (n.d.) · Unknown authors · PubMed 27680694

    ABSTRACT: Birth weight (BW) is influenced by both foetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These lifecourse associations have often been attributed to the impact of an adverse early life environment. We performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where foetal genotype was associated with BW (P <5x10-8). Overall, ˜15% of variance in BW could be captured by assays of foetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (rg=-0.22, P =5.5x10-13), T2D (rg=-0.27, P =1.1x10-6) an

  • Multi-trait association analysis reveals shared genetic loci between Alzheimer's disease and cardiovascular traits - Unknown journal (n.d.) · Unknown authors · PubMed 39537608

    ABSTRACT: Several cardiovascular traits and diseases co-occur with Alzheimer's disease. We mapped their shared genetic architecture using multi-trait genome-wide association studies. Subsequent fine-mapping and colocalisation highlighted 16 genetic loci associated with both Alzheimer's and cardiovascular diseases. We prioritised rs11786896, which colocalised with Alzheimer's disease, atrial fibrillation and expression of PLEC in the heart left ventricle, and rs7529220, which colocalised with Alzheimer's disease, atrial fibrillation and expression of C1Q family genes. Single-cell RNA-sequencing data, co-expression network and protein-protein interaction analyses provided evidence for different mechanisms of PLEC, which is upregulated in left ventricular endothelium and cardiomyocyte

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