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Obesity is a major cause of premature disease and mortality, is increasing worldwide, and is particularly common in Latin-America. Observational and genetic studies have also established the role of lipids, glycaemic and blood-pressure traits for the risk of cardiometabolic and other diseases in many populations. Recent studies have suggested that higher levels of lipid particle sizes or concentrations measured through Nuclear Magnetic Resonance (NMR) may explain the excess risk of cardiometabolic diseases associated with higher adiposity, in addition to that explained by diabetes, blood pressure and other metabolites. However, there is limited evidence from non-European populations. 

The MCPS is a cohort of 150,000 participants followed for two decades with high baseline prevalences of obesity and diabetes and low use of statins. All participants have detailed baseline information on socio-demographic factors, lifestyle characteristics, and physical and biological measurements (including NMR metabolomic, genetic array and exome data in the whole cohort). It is also anticipated that some proteomic data will become available during the course of this project.   

This DPhil project aims to systematically assess and compare the relevance of 150 individual circulating metabolites to various specific diseases and causes of premature death in the MCPS. The project will apply conventional and genetic epidemiological techniques to: 

  1. examine the observed and genetic associations of a wide range of novel NMR-biomarkers (e.g. lipids, including their classes and particle sizes, markers of inflammation, glucose, and liver function), to specific cardio-metabolic traits and specific non-fatal or fatal diseases in MCPS
  2. map-up overlapping and unique metabolomic traits specific to certain disease (including their comorbid conditions) or causes of death in MCPS
  3. assess potential differences in risk by ancestry admixture and other relevant characteristics.


The student will gain experience in non-communicable diseases epidemiological research and analysis of large-scale prospective data. They will develop skills in conducting systematic literature reviews, prospective study design in a general population context, statistical programming, data analysis, and presentation skills. 


The student will be supported to publish peer-reviewed papers emerging from their DPhil.

prospective student

The ideal candidate will have a Master's degree in a relevant area (e.g. statistics/genetic epidemiology/biomedical or life sciences) and proficiency with programing analyses in STATA, R or SAS packages.