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In this project the student will investigate the extent to which an inflammatory profile is associated with concurrent or subsequent disease states – e.g. colorectal, prostate cancer; cardiac or cerebrovascular outcomes, using data from 500,000 UK Biobank participants.

The degree of inflammation will be assessed through utilising plasma concentrations of blood-based biomarkers e.g. CRP, leukocytes, as measured using blood assay and NMR. Disease incidence will be identified using linked health records including hospital episode statistics (HES), mortality and cancer registry data.

The roles which certain pre-existing conditions (e.g. diabetes and obesity) play in contributing towards an adverse inflammatory metabolic profile and exacerbating disease risk will also be assessed.

Observational epidemiological methods will be used in the first instance and then genetic epidemiological methods (e.g. Mendelian randomisation) may be used to interrogate any significant associations. 

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

Observational and genetic epidemiological methods; research methods including conducting a systematic review; possible statistical methods including multivariable, logistic and Cox regression; mediation analysis; Mendelian randomisation; handling ‘big data’ e.g. electronic health records and genetic data. Skills training will be available. 

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

The successful candidate will be based at the Big Data Institute, University of Oxford. Training will be available for using the UK Biobank Research Analysis Platform (RAP) and conducting statistical analyses. 

PROSPECTIVE  STUDENT

The ideal candidate will have a Master’s degree in a relevant area (e.g. statistics/epidemiology/public health). The project can be focused towards the specific areas of interest of the student (e.g. cardiovascular disease, cancer). Depending on the scope of the project, there may be an opportunity to look at other cohorts alongside UK Biobank. 

Supervisors