MRC DTP in Precision Medicine

Precision Risk Prediction of Tuberculosis (TB) in Individuals with Multimorbidity: Integrating Clinical, Demographic and Biological Data

Supervisors

Prof Peter MacPherson, School of Health and Wellbeing, University of Glasgow
Dr Heather Waddell, School of Health and Wellbeing, University of Glasgow
Prof Judith Bruchfeld, Karolinska Institutet
Prof Lina Davies Forsman, Karolinska Institutet

Summary

Tuberculosis (TB) remains a major global health challenge, and the growing prevalence of chronic non-communicable diseases (NCDs) means that many people living with TB experience multimorbidity, which can influence disease progression and treatment outcomes. Despite its importance, the interactions between TB and multimorbidity are poorly understood, particularly when considering individual-level clinical, demographic, and biological variation.

This PhD project will develop risk prediction models using existing datasets such as UK Biobank and Public Health Scotland Enhanced TB Notification records to understand how multimorbidity is associated with TB in Scotland, and how it impacts upon treatment outcomes and long-term health. Using precision medicine approaches, the student will integrate clinical, demographic, and biological data to build models that will update risk estimates over time, age-cohort effects, and will capture the evolving nature of disease progression and treatment response. The project will also explore how TB outcomes vary across patient subgroups with different multimorbidity profiles, including comparative analyses between Sweden and Scotland to understand how epidemiological context shapes these relationships. This will provide insights into which populations are at highest risk and supporting development of a personalised medicine approach.

The successful candidate will gain experience in advanced statistical and epidemiological methods, advanced statistical modelling, and data integration, while producing research that has potential applications in personalised TB management and public health policy. This project offers a unique opportunity to work at the interface of epidemiology, precision medicine, and computational modelling, equipping the student with skills relevant for both academic and an applied health research career trajectory.