Analysing electrocardiographic traits and predicting cardiac risk in UK biobank. (June 2021)

• Record Type: Journal Article
• Authors: Ramírez, Julia; Duijvenboden, Stefan van; Young, William J; Orini, Michele; Jones, Aled R; Lambiase, Pier D; Munroe, Patricia B; Tinker, Andrew
• Is Part Of: JRSM cardiovascular disease. Volume 10(2021)
• Publication Date: 2021-06
• Subjects: Arrhythmias -- clinical electrophysiology -- drugs -- genomics -- ion channels -- membrane transport; Cardiovascular system -- Diseases -- Periodicals; 616.1005
• DOI: 10.1177/20480040211023664
• Languages: English
• ISSNs: 2048-0040

Abstract

The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.