Using health and genomic data to understand and predict respiratory disease

About the Project

This project is an example of the type of approaches used by academics in the Genetic Epidemiology group, which can be applied to a wide range of health conditions. Conditions studied include asthma, chronic cough, COPD, interstitial lung disease, thyroid disease, as well as associated traits such as lung function and thyroid hormone levels. We also have a focus on multiple long-term conditions and cardiorespiratory comorbidity, as well as expertise in a range of statistical genetics methods including Mendelian randomisation. We are happy to discuss opportunities with potential candidates.

Spontaneous pneumothorax (SP) is a condition where air leaks into the space around the lungs, causing the lung to collapse. It can happen suddenly, often without warning, causing pain and difficulty breathing. It affects around 10,000 people a year in England, many of them young and otherwise healthy. While doctors can manage the immediate problem, up to four in ten people will experience a further episode. It is currently not possible to predict who will experience recurrence, meaning decisions about long-term management are more difficult.

Emerging evidence suggests a genetic contribution to SP, including both monogenic and polygenic influences, but there have been no studies that are both sufficiently focused and sufficiently large to investigate the polygenic contribution. This PhD project aims to elucidate the genetic architecture of SP and develop predictive models for recurrence risk.

With training and support, you will access large-scale biobanks such as UK Biobank and All Of Us. You will utilise electronic health records (EHR) to identify people who have experienced SP, and undertake genetic association studies using genome-wide genotyping and whole genome sequencing data, meta-analysing these across biobanks. You will perform fine-mapping to identify the causal variant, and will use a range of in silico methods and data including expression, protein and other functional data to identify the most likely causal gene. You will use phenome-wide association studies to gain insight into the wider effects of SP-associated variants. This could be extended to more in-depth functional study, depending on the interests of the student.

You will construct polygenic scores for SP, and evaluate their predictive performance in different clinical scenarios, comparing with standard risk factors such as age and sex.

Training and Environment

You will be based in the world-leading Genetic Epidemiology research group. The group currently hosts 17 PhD students and has an exceptional track record in developing talented postgraduate researchers who go on to successful postdoctoral careers in academia and in industry. You will have access to the NIHR Biomedical Research Centre, high-performance computing facilities, and expert supervision in statistical genetics, genetic epidemiology, and bioinformatics. Our strong collaborations with clinical and functional genomics experts will provide you with opportunities to gain further insights into translation. You will be encouraged to take up opportunities for experience of public outreach and engagement.

Expected Outcomes

The project will identify novel genetic variants and biological pathways associated with SP, improve understanding of disease mechanisms, and develop tools for personalised risk prediction. These findings will provide a foundational understanding for future personalised medicine, enabling patients and clinicians to make better decisions about their care. You will present your emerging findings to academics and clinicians at relevant conferences, and will be encouraged to contribute to publications.