Expressive

rs10262140 - HOTTIP - EVX1-AS

Magnitude 2.2 · 4 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

  • 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

  • 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

  • Genome-wide variance quantitative trait locus analysis suggests small interaction effects in blood pressure traits - Unknown journal (n.d.) · Unknown authors · PubMed 35879408

    ABSTRACT: Genome-wide variance quantitative trait loci (vQTL) analysis complements genome-wide association study (GWAS) and has the potential to identify novel variants associated with the trait, explain additional trait variance and lead to the identification of factors that modulate the genetic effects. I conducted genome-wide analysis of the UK Biobank data and identified 27 vQTLs associated with systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse pressure (PP). The top single-nucleotide polymorphisms (SNPs) are enriched for expression QTLs (eQTLs) or splicing QTLs (sQTLs) annotated by GTEx, suggesting their regulatory roles in mediating the associations with blood pressure (BP). Of the 27 vQTLs, 14 are known BP-associated QTLs discovered by GWASs. The heteroscedasti

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