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Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits

van Setten, J; Verweij, N; Mbarek, H; Niemeijer, MN; Trompet, S; Arking, DE; Brody, JA; ... Isaacs, A; + view all (2019) Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits. European Journal of Human Genetics 10.1038/s41431-018-0295-z. (In press). Green open access

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Abstract

Genome-wide association studies (GWAS) of quantitative electrocardiographic (ECG) traits in large consortia have identified more than 130 loci associated with QT interval, QRS duration, PR interval, and heart rate (RR interval). In the current study, we meta-analyzed genome-wide association results from 30,000 mostly Dutch samples on four ECG traits: PR interval, QRS duration, QT interval, and RR interval. SNP genotype data was imputed using the Genome of the Netherlands reference panel encompassing 19 million SNPs, including millions of rare SNPs (minor allele frequency < 5%). In addition to many known loci, we identified seven novel locus-trait associations: KCND3, NR3C1, and PLN for PR interval, KCNE1, SGIP1, and NFKB1 for QT interval, and ATP2A2 for QRS duration, of which six were successfully replicated. At these seven loci, we performed conditional analyses and annotated significant SNPs (in exons and regulatory regions), demonstrating involvement of cardiac-related pathways and regulation of nearby genes.

Type: Article
Title: Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41431-018-0295-z
Publisher version: http://doi.org/10.1038/s41431-018-0295-z
Language: English
Additional information: © The Author(s) 2019. This article is published with open access. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
Keywords: Genome-wide association studies, Quantitative trait
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Health Informatics
URI: http://discovery.ucl.ac.uk/id/eprint/10067495
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