rs12154315 - DGKB
Magnitude 2.2 · 5 studies on file
Reported associations
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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
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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
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Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction - Unknown journal (n.d.) · Unknown authors · PubMed 36653681
ABSTRACT: Atrial fibrillation (AF) is a common cardiac arrhythmia resulting in increased risk of stroke. Despite highly heritable etiology, our understanding of the genetic architecture of AF remains incomplete. Here we performed a genome-wide association study in the Japanese population comprising 9,826 cases among 150,272 individuals and identified East Asian-specific rare variants associated with AF. A cross-ancestry meta-analysis of >1 million individuals, including 77,690 cases, identified 35 new susceptibility loci. Transcriptome-wide association analysis identified IL6R as a putative causal gene, suggesting the involvement of immune responses. Integrative analysis with ChIP-seq data and functional assessment using human induced pluripotent stem cell-derived cardiomyocytes demonstrat
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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
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Multitrait analyses identify genetic variants associated with aortic valve function and aortic stenosis risk - Unknown journal (n.d.) · Unknown authors · PubMed 41419685
ABSTRACT: The genetic influences on normal aortic valve function and their impact on aortic stenosis risk are of substantial interest. We used deep learning to measure peak velocity, mean gradient and aortic valve area from magnetic resonance imaging and conducted genome-wide association studies (GWAS) in 59,571 participants in the UK Biobank. Incorporating the aortic valve measurement GWAS with aortic stenosis GWAS using multitrait analysis of GWAS (MTAG), we identified 166 distinct loci (134 with aortic valve traits, 134 with aortic stenosis and 166 unique loci across all GWAS), including PCSK9 and LDLR. The MTAG aortic stenosis PGS was associated with aortic stenosis in All of Us (hazard ratio (HR) = 3.32 for top 5% versus all others, P = 8.8 × 10−22) and Mass General Bri
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