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Background

Lipoprotein particles vary enormously by size, content and function. While some blood lipid particles are causally related to the risk of cardiovascular and related metabolic diseases much is unknown, in part because (until quite recently) it has only been possible to characterise lipids very crudely. NMR metabolomics resolves information on over 200 metabolomic measures related to lipoprotein subclass concentration and composition, glycerides and phospholipids, apolipoproteins, and other markers.  

The Mexico City Prospective Study (MCPS) is a blood-based prospective study of 150,000 adults who were recruited between 1998 and 2004 and have been followed for cause-specific mortality ever since. Questionnaire data and physical measurements were recorded at baseline, genome-wide genotyping and whole exome sequence data exists for all participants, and NMR metabolomics data already exists for 40,000 participants (anticipated whole cohort by October 2021). 

This project aims to leverage molecular features within MCPS to elucidate causal relationships between refined lipid signatures and mortality from specific diseases. The specific DPhil project will be subject to further discussion and personal interest, but could include the following areas of work: 

  1. Identify and fine-map genetic loci associated with NMR lipid signatures. This may involve a series of genome-wide association studies (GWAS), adjusting for sources of genetic confounding (i.e. genetic relatedness, ancestry, admixture), and subsequent conditional analyses, to map quantitative trait loci (QTLs) that influence metabolite features. 
  2. Construct and evaluate genetic instruments for NMR lipid signatures. This may involve incorporating external datasets to refine instrument variables that serve as genetic proxies for lipid “exposures”.
  3. Employ Mendelian randomisation approaches (one- and two-sample methods) to assess causal relationships between lipid signatures and disease-specific mortality from ischaemic heart disease, stroke types, renal disease, and hepatobiliary diseases.
  4. Integrate across metabolomic QTLs to construct polygenic risk scores (PRS) and assess PRS utility in patient stratification and predicting disease outcomes based on underlying genetic burden. 

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

This project will involve detailed analysis and interpretation of existing MCPS data. The student will work within a multi-disciplinary team and will gain research experience in literature review, epidemiological and statistical methodology (including genetic epidemiology techniques), programming and data analysis. Regular research meetings and workshops will be held in which the candidate will be expected to attend and to present research findings.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

The project will provide a range of training opportunities in statistical analysis and interpretation and statistical programming. By the end of the DPhil, it is expected that you will be competent to plan, undertake and interpret statistical analysis of large-scale epidemiological and genetic data, and to report your findings. The project will be based in the MRC Population Health Research Unit, Nuffield Department of Population Health, which has excellent facilities and a world-class community of statistical and clinical scientists.

prospective candidate

Candidates should have a strong background in a mathematical or biomedical discipline and postgraduate training in epidemiology, statistics or public health. The project will involve large-scale data and statistical analyses. Candidates should therefore have an interest and aptitude in extending these skills as well as a strong interest in non-communicable disease epidemiology.

Supervisors