rs112370447 - COG5

Magnitude 2.2 · 2 studies on file

Reported associations

• Association analyses based on false discovery rate implicate new loci for coronary artery disease. - Nature genetics (2017) · Nelson CP, Goel A, Butterworth AS, Kanoni S, Webb TR, Marouli E, Zeng L, Ntalla I, Lai FY, Hopewell JC, Giannakopoulou O, Jiang T, Hamby SE, Di Angelantonio E, Assimes TL, Bottinger EP, Chambers JC, Clarke R, Palmer CNA, Cubbon RM, Ellinor P, Ermel R, Evangelou E, Franks PW, Grace C, Gu D, Hingorani AD, Howson JMM, Ingelsson E, Kastrati A, Kessler T, Kyriakou T, Lehtimäki T, Lu X, Lu Y, März W, McPherson R, Metspalu A, Pujades-Rodriguez M, Ruusalepp A, Schadt EE, Schmidt AF, Sweeting MJ, Zalloua PA, AlGhalayini K, Keavney BD, Kooner JS, Loos RJF, Patel RS, Rutter MK, Tomaszewski M, Tzoulaki I, Zeggini E, Erdmann J, Dedoussis G, Björkegren JLM, Schunkert H, Farrall M, Danesh J, Samani NJ, Watkins H, Deloukas P · PubMed 28714975

  Genome-wide association studies (GWAS) in coronary artery disease (CAD) had identified 66 loci at 'genome-wide significance' (P < 5 × 10 ) at the time of this analysis, but a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs. 1,2,3,4). Here we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; n = 10,801) as well as a stricter definition without angina (HARD; n = 6,482) and selected cases with the former phenotype to conduct a meta-analysis using the two most recent CAD GWAS. This approach identified 13 new loci at genome-wide significance, 12 of which were on our previous list of loci meeting the 5% FDR threshold, thus providing strong support that the remai

• 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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