Expressive

rs11001667 - LRMDA

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 Polygenic Risk Score Based on a Cardioembolic Stroke Multitrait Analysis Improves a Clinical Prediction Model for This Stroke Subtype - Unknown journal (n.d.) · Unknown authors · PubMed 35872910

    ABSTRACT: Background Occult atrial fibrillation (AF) is one of the major causes of embolic stroke of undetermined source (ESUS). Knowing the underlying etiology of an ESUS will reduce stroke recurrence and/or unnecessary use of anticoagulants. Understanding cardioembolic strokes (CES), whose main cause is AF, will provide tools to select patients who would benefit from anticoagulants among those with ESUS or AF. We aimed to discover novel loci associated with CES and create a polygenetic risk score (PRS) for a more efficient CES risk stratification. Methods Multitrait analysis of GWAS (MTAG) was performed with MEGASTROKE-CES cohort (n = 362,661) and AF cohort (n = 1,030,836). We considered significant variants and replicated those variants with MTAG p-value < 5 × 10−8 influencing both t

  • Multi-Ethnic Genome-wide Association Study for Atrial Fibrillation - Unknown journal (n.d.) · Unknown authors · PubMed 29892015

    ABSTRACT: Atrial fibrillation (AF) affects over 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies for AF to date, consisting of over half a million individuals including 65,446 with AF. In total, we identified 97 loci significantly associated with AF including 67 of which were novel in a combined-ancestry analysis, and 3 in a European specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait loci (eQTL) analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate

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