Assessing the causal roles of inflammatory biomarkers in cardiometabolic diseases

Background

Cardiometabolic diseases (CMD), including IHD, stroke, and type 2 diabetes, are the leading causes of morbidity and mortality worldwide. While major risk factors such as hypertension, obesity, and dyslipidaemia are well-established, there is growing evidence to suggest the importance of chronic low-grade inflammation in CMD pathogenesis. However, the precise role of many inflammatory protein biomarkers — particularly those captured by more recent high-throughput proteomics assays — remains poorly understood. This project will investigate the relationships of inflammatory proteins with CMD, utilising available and emerging proteomics data in subsets of China Kadoorie Biobank (CKB: ~10,000 proteins) and the UK Biobank (UKB: ~3000 proteins) participants. The integrated analyses of proteomics, genetics, health outcome and other exposure (e.g. lifestyle, adiposity, gut microbiome) data in these biobanks will greatly improve understanding of the inflammatory processes underlying CMD, informing disease prevention and treatment strategies. 

research experience, research methods and skills training

The specific DPhil project will be developed according to the candidate’s interests and aptitude, and may cover some of the following objectives:

1. To examine and compare the associations of inflammatory markers with traits (e.g. adiposity, smoking) and CMD risks in CKB versus UKB and to explore factors contributing to the observed differences;
2. To explore whether sex, age and lifestyle factors (e.g. smoking, diet, physical activity) modify the associations between inflammatory protein biomarkers and cardiometabolic traits and outcomes.
3. To develop inflammation-based protein scores, using conventional and machine learning approaches, and to assess their predictive utilities for disease risks in diverse populations;
4. To clarify the causal associations of inflammatory markers with CMD risks, using Mendelian randomisation (MR) and colocalisation test;
5. To assess potential druggability of certain inflammatory markers using various downstream analyses (e.g. enrichment, KO mouse models, tissue expression, MR-PheWAS);
6. To explore, using genetic instruments, the up- and/or down-regulating roles of specific proteins (e.g. IL6, TNF) on signalling network and their likely effects on disease risks.

Advanced in-house training will be provided in statistics, statistical programming (e.g. R), genetics (e.g. MR, colocalisation analyses), and scientific writing. By the end of the DPhil, the student will be competent to plan, undertake and interpret analyses of large datasets, and to report research findings, including some peer-reviewed publications as the lead author.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

There may be opportunities to collaborate with industry partners and laboratory scientists. Attendance at seminars, workshops and courses provided by the Department and University will be encouraged. There will be opportunity to present research work at relevant international/national conferences. 

PROSPECTIVE STUDENT

The candidate should have a good first degree (first class or 2.1 grade) and MSc in epidemiology, statistics, genetics, biomedical science, or a related discipline, with a strong interest in molecular epidemiology.