rs11545169 - PSMD2

Magnitude 2.0 · 8 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

• Leveraging Polygenic Functional Enrichment to Improve GWAS Power. - American journal of human genetics (2019) · Kichaev G, Bhatia G, Loh PR, Gazal S, Burch K, Freund MK, Schoech A, Pasaniuc B, Price AL · PubMed 30595370

  Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attaine

• The genetic architecture of appendicular lean mass characterized by association analysis in the UK Biobank study - Unknown journal (n.d.) · Unknown authors · PubMed 33097823

  ABSTRACT: Appendicular lean mass (ALM) is a heritable trait associated with loss of lean muscle mass and strength, or sarcopenia, but its genetic determinants are largely unknown. Here we conducted a genome-wide association study (GWAS) with 450,243 UK Biobank participants to uncover its genetic architecture. A total of 1059 conditionally independent variants from 799 loci were identified at the genome-wide significance level (p < 5 × 10−9), all of which were also significant at p < 5 × 10-5 in both sexes. These variants explained ~15.5% of the phenotypic variance, accounting for more than one quarter of the total ~50% GWAS-attributable heritability. There was no difference in genetic effect between sexes or among different age strata. Heritability was enriched in cer

• Combining cross-sectional and longitudinal genomic approaches to identify determinants of cognitive and physical decline - Unknown journal (n.d.) · Unknown authors · PubMed 40374629

  ABSTRACT: Large-scale genomic studies focusing on the genetic contribution to human aging have mostly relied on cross-sectional data. With the release of longitudinally curated aging phenotypes by the UK Biobank (UKBB), it is now possible to study aging over time at genome-wide scale. In this work, we evaluated the suitability of competing models of change in realistic simulation settings, performed genome-wide association scans on simulation-validated measures of age-related deweekcline, and followed up with LD-score regression and Mendelian Randomization (MR) analyses. Focusing on global cognitive and physical function, we observed marked differences between baseline function (θ) and accelerated decline (Δ). Both outcomes showed distinct heritability levels (e.g., 31.38% versus 3.15%

• Genetic analysis of elevated levels of creatinine and cystatin C biomarkers reveals novel genetic loci associated with kidney function - Unknown journal (n.d.) · Unknown authors · PubMed 39927731

  ABSTRACT: Abstract The rising prevalence of chronic kidney disease (CKD), affecting an estimated 37 million adults in the United States, presents a significant global health challenge. CKD is typically assessed using estimated Glomerular Filtration Rate (eGFR), which incorporates serum levels of biomarkers such as creatinine and cystatin C. However, these biomarkers do not directly measure kidney function; their elevation in CKD results from diminished glomerular filtration. Genome-wide association studies (GWAS) based on eGFR formulas using creatinine (eGFRcre) or cystatin C (eGFRcys) have identified distinct non-overlapping loci, raising questions about whether these loci govern kidney function or biomarker metabolism. In this study, we show that GWAS on creatinine and cystatin C levels

• 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%

• A saturated map of common genetic variants associated with human height - Unknown journal (n.d.) · Unknown authors · PubMed 36224396

  ABSTRACT: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation

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