Analysing electrocardiographic traits and predicting cardiac risk in UK biobank

Julia Ramírez; Stefan van Duijvenboden; William J Young; Michele Orini; Aled R Jones; Pier D Lambiase; Patricia B Munroe; Andrew Tinker

doi:10.1177/20480040211023664

Analysing electrocardiographic traits and predicting cardiac risk in UK biobank

JRSM Cardiovasc Dis. 2021 Jun 12:10:20480040211023664. doi: 10.1177/20480040211023664. eCollection 2021 Jan-Dec.

Authors

Julia Ramírez^{1

2}, Stefan van Duijvenboden^{1

2}, William J Young^{1

3}, Michele Orini^{1

2

3}, Aled R Jones¹, Pier D Lambiase^{2

3}, Patricia B Munroe^{1

4}, Andrew Tinker^{1

4}

Affiliations

¹ Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
² Institute of Cardiovascular Science, University College London, London, UK.
³ Barts Heart Centre, St Bartholomew's Hospital, London, UK.
⁴ NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

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.

Keywords: Arrhythmias; clinical electrophysiology; drugs; genomics; ion channels; membrane transport.

Publication types

Review

Abstract

Publication types

Grants and funding