Heart failure and cardiac arrhythmias are major contributors to mortality, morbidity, and healthcare costs worldwide. Despite advances in treatment, early detection and prevention strategies remain limited. This project aims to leverage the extensive UK Biobank dataset to identify predictors and determinants of heart failure and arrhythmias, with the goal of improving risk stratification, disease prevention, and mechanistic understanding.
We will utilise the UK Biobank’s multimodal datasets, including imaging, functional, physical, environmental, genetic, and proteomic data alongside linked health records and outcome data to address the following key research objectives:
Identify prognostic signatures for arrhythmic and heart failure events, enabling earlier detection of high-risk individuals.
Characterise how individual-level variables (e.g. imaging or genetic profiles) interact with lifestyle and environmental factors to influence disease onset and progression.
Investigate novel mechanistic pathways and potential therapeutic targets by integrating genetic and biomarker data with clinical outcomes.
This research will contribute to improved clinical risk models, support personalised prevention strategies, and generate insights into the underlying biology of heart failure and arrhythmias. Ultimately, it will inform future interventional studies and precision medicine approaches.