| Title: | Understanding genetic influences in the response of the cardiac electrical system to exercise |
| Lead Institution: | Queen Mary University of London |
| Principal investigator: | Professor Andrew Tinker |
Application 8256
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About
Abnormalities in the normal electrical activity of the heart are an important cause of disease and at their most traumatic can result in sudden unexpected death. Such events can occur under stressful conditions such as exercise. We propose to study the response of a range of parameters measured from the surface electrical activity of the heart and link these with potential new genes by integrating this with the genomic information obtained in UK Biobank. Our hope is to understand the (patho)physiological response of the cardiac electrical system to exercise by combining the physiological analysis with the genomic studies. UK Biobank aims to improve the prevention, diagnosis and treatment of a wide range of serious and life-threatening illnesses. Abnormalities of heart rhythm are a substantial health burden with stroke as a result of atrial fibrillation and sudden cardiac death in the setting of acute coronary syndromes and ischaemic heart disease being particularly common. Our study may reveal unique precipitating factors and suggest new targets for therapeutic innovation by integrating the physiological measurements with the large scale genomic characterisation. Potentially this might identify new molecular players in these responses. We would like to study the subgroup of individuals undergoing the core cardioassessment (exercise testing). Volunteers are exercised on a standing bicycle whilst a measurement is made of surface cardiac electrical activity (electrocardiogram, ECG). We would use automated computer analysis of the digitised ECGs to study how the cardiac electrical system responds to exercise. We propose a two phase study first on analysing a small number of 100 ECGs and then a much larger analysis after developing an automated algorithm. Subsequently, we will need access to data obtained in these individuals from the bespoke genotyping chip developed for UK Biobank. 100K Full cohort. Our workstream will be in two phases though (see above and below)2 Returns
| Return ID | App ID | Description | Archive Date |
|---|---|---|---|
| 1502 | 8256 | Long-term intra-individual reproducibility of heart rate dynamics during exercise and recovery in the UK Biobank cohort | 1 Aug 2018 |
| 2367 | 8256 | Thirty loci identified for heart rate response to exercise and recovery implicate autonomic nervous system | 25 Aug 2020 |
12 Publications
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