Approved Research

Leveraging UK biobank data and its genetic communities to inform on common and rare variant risk for common conditions including neurological, renal and pulmonary disease.

Lay summary

This project aims to understand how variation in our genetic code can influence a number of health conditions such as epilepsy, autism, kidney disease and transplantation, and progressive lung disease. In addition, this project aims to identify and study the genetics of population communities of ancestries beyond Britain and Ireland. What other global communities have been sampled through the biobank, and how can we leverage the genetic makeup of these diverse communities to better understand how our genes influence our health?

Scientific rationale: In genetic forms of kidney and lung disease, people with the exact same genetic cause can experience quite different severities of disease. Within renal transplantation, genetic factors influencing long-term transplant outcome are poorly understood. We also appreciate that communities of individuals of shared genetic identity exist across Britain, Ireland and of course beyond. People in such communities share a similar recent ancestry. But we have a limited understanding of the extent to which rare genetic variants (i.e. changes in DNA code) are shared within and across such communities, despite rare variation being more likely to influence health-related traits, including disease.

We propose a project duration of 36 months. The distinct aims of this project are questions forming part of several PhD thesis projects.

Public health impact: We expect this work to improve our ability to identify people at particular risk of specific conditions (e.g. kidney disease) that would in theory allow targeted interventions to reduce risk in such individuals (e.g. approaches to control blood pressure). Further, by studying diverse ancestries in UKBiobank this project will contribute to making the impact of genetic studies more equitable across populations, by for example and improved understanding of how specific genetic factors confer disease risk across populations.