Causes and consequences of valvular heart disease: analyses of large-scale datasets

Valvular heart disease (VHD) refers to a group of conditions which affect an increasing number of adults worldwide. Despite this, our knowledge of its burden, underlying causes and consequences is limited. Indeed, a large proportion of VHD is still considered to be ’degenerative’ with no clear understanding of its causes and no established preventative strategies. Most previous research in this field has been based on small-scale mechanistic studies or cross-sectional studies with their inherent limitations.

Recent accumulation of Big Data from routine health records (such as the UK Clinical Practice Research Datalink [CPRD]), registries and large-scale cohorts (such as the UK Biobank) provides an unprecedented opportunity to investigate the burden and determinants of VHD and help identify potentially modifiable risk factors. Early analyses from our group have shown highly promising results. The more recent imaging substudy of the UK Biobank, which will involve cardiac MRI and echo studies from up to 100,000 participants, will enable more in-depth analyses of the causes and consequences of VHD.

For this DPhil project, the student will use very large datasets from different to investigate the epidemiology of VHD with cross-validation in different cohorts. The specific focus of the studies to be undertaken will depend the student’s skills and interests. As a member of the team, the student will become involved in the design, conduct and interpretation of related Big Data projects.