Expressive

rs11153653 - RNA5SP214 - VGLL2

Magnitude 2.2 · 3 studies on file

Reported associations

  • Meta-analysis of genome-wide associations and polygenic risk prediction for atrial fibrillation in more than 180,000 cases. - Nature genetics (2025) · Roselli C, Surakka I, Olesen MS, Sveinbjornsson G, Marston NA, Choi SH, Holm H, Chaffin M, Gudbjartsson D, Hill MC, Aegisdottir H, Albert CM, Alonso A, Anderson CD, Arking DE, Arnar DO, Barnard J, Benjamin EJ, Braunwald E, Brumpton B, Campbell A, Chami N, Chasman DI, Cho K, Choi EK, Christophersen IE, Chung MK, Conen D, Crijns HJ, Cutler MJ, Czuba T, Damrauer SM, Dichgans M, Dörr M, Dudink E, Duong T, Erikstrup C, Esko T, Fatkin D, Faul JD, Ferreira M, Freitag DF, Ganesh SK, Gaziano JM, Geelhoed B, Ghouse J, Gieger C, Giulianini F, Graham SE, Gudnason V, Guo X, Haggerty C, Hayward C, Heckbert SR, Hveem K, Ito K, Johnson R, Jukema JW, Jurgens SJ, Kääb S, Kane JP, Kany S, Kardia SLR, Kavousi M, Khurshid S, Kamanu FK, Kirchhof P, Kleber ME, Knight S, Komuro I, Krieger JE, Launer LJ, Li D, Lin H, Lin HJ, Loos RJF, Lotta L, Lubitz SA, Lunetta KL, Macfarlane PW, Magnusson PKE, Malik R, Mantineo H, Marcus GM, März W, McManus DD, Melander O, Melloni GEM, Meyre PB, Miyazawa K, Mohanty S, Monfort LM, Müller-Nurasyid M, Nafissi NA, Natale A, Nazarian S, Ostrowski SR, Pak HN, Pang S, Pedersen OB, Pedersen NL, Pereira AC, Pirruccello JP, Preuss M, Psaty BM, Pullinger CR, Rader DJ, Rämö JT, Ridker PM, Rienstra M, Risch L, Roden DM, Rotter JI, Sabatine MS, Schunkert H, Shah SH, Shim J, Shoemaker MB, Simonson B, Sinner MF, Smit RAJ, Smith JA, Smith NL, Smith JG, Soliman EZ, Sørensen E, Sotoodehnia N, Strbian D, Stricker BH, Teder-Laving M, Sun YV, Thériault S, Thorolfsdottir RB, Thorsteinsdottir U, Tveit A, van der Harst P, van Meurs J, Wang B, Weiss S, Wells QS, Weng LC, Wilson PW, Xiao L, Yang PS, Yao J, Yoneda ZT, Zeller T, Zeng L, Zhao W, Zhou X, Zöllner S, Ruff CT, Bundgaard H, Willer C, Stefansson K, Ellinor PT · PubMed 40050429

    Atrial fibrillation (AF) is the most common heart rhythm abnormality and is a leading cause of heart failure and stroke. This large-scale meta-analysis of genome-wide association studies increased the power to detect single-nucleotide variant associations and found more than 350 AF-associated genetic loci. We identified candidate genes related to muscle contractility, cardiac muscle development and cell-cell communication at 139 loci. Furthermore, we assayed chromatin accessibility using assay for transposase-accessible chromatin with sequencing and histone H3 lysine 4 trimethylation in stem cell-derived atrial cardiomyocytes. We observed a marked increase in chromatin accessibility for our sentinel variants and prioritized genes in atrial cardiomyocytes. Finally, a polygenic risk score (P

  • 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

  • Genetic analyses across cardiovascular traits: leveraging genetic correlations to empower locus discovery and prediction in common cardiovascular diseases - Unknown journal (n.d.) · Unknown authors · PubMed 41022758

    ABSTRACT: Common genetic variation detected by genome-wide association studies (GWAS) partially explains variability in the spectrum of cardiac phenotypes. In this work, we explore genetic correlations among 58 cardiac-related traits/diseases, detecting novel ones. We subsequently employ multi-trait analysis of GWAS (MTAG), which meta-analyzes genetically correlated traits, to improve genomic loci discovery and prediction in atrial fibrillation (AF), coronary artery disease (CAD), and heart failure (HF). We identify 19 novel loci specific for AF, 131 for CAD, and 141 for HF. Polygenic scores (PGS) in 15,177 Canadian individuals show similar results when PGS are derived from conventional GWAS versus MTAG summary statistics, although MTAG-PGS improve prediction and discrimination of CAD in f

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