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Genome-wide association studies (GWAS) have identified hundreds of common and low-frequency variants associated with kidney function. However, <1% of the individuals who have contributed to these discovery efforts are from Latin American or Hispanic ancestry (DOI: 10.1038/s41467-021-24491-0). Large studies of non-European populations are needed to fully assess the influence of genetics on kidney disease, as evidence suggests there is increased opportunity for discovery of trait/disease risk-increasing loci in recently admixed populations such as those from Latin America,(DOI: 10.1101/2022.06.26.495014) including kidney disease-related loci (DOI: 10.1681/ASN.2021050617). Additionally, the relevance of kidney function (measured as the estimated glomerular filtration rate) to death due to vascular (and other) causes remains largely unexplored in the Mexican population, which is characterised by extremely high levels of adiposity and diabetes.

The Mexico City Prospective Study (MCPS) is a blood-based cohort of 150,000 adults aged >35 years and recruited between 1998 and 2004 who have been followed for cause-specific mortality ever since. Questionnaire data and physical measurements were recorded at baseline, and genome-wide genotyping exists for all participants. By the time of start of this DPhil project, all participants will have NMR-measured plasma creatinine as well as dozens of other lipid and metabolic biomarkers. 

While the specifics are subject to discussion and the candidate’s interest, this DPhil project could include the following work: 

  1. Conducting a GWAS of kidney function while accounting for sources of genetic confounding within this population (i.e., genetic relatedness and admixture); assessing potential novelty of found associations; and exploring biological mechanisms for genetic risk factors
  2. Assessing the associations of kidney function with other cardio-metabolic risk factors and its relevance to cause-specific mortality, using observational and genetic epidemiology methods.


This project will involve undertaking complex analyses of large-scale genetic and epidemiological data. The student will work within a multi-disciplinary team of clinical scientists, geneticists, epidemiologists, and statisticians and will develop skills involving epidemiological, genetic, and statistical methods, bioinformatics, and programming. The student is expected to attend and present their work in regular internal research meetings and workshops. They will have opportunities to present their findings in national or international conferences and to publish in peer-reviewed journals.


There will be multiple training opportunities in statistical and genetic analyses and in programming in high-performance cluster computing. By the end of the DPhil, the student will be competent to plan, undertake, interpret, and report scientific analysis of large-scale epidemiological and genetics data. The student will be based at Oxford Population Health, which has excellent facilities and a world-class community of scientists.


Candidates should have a strong background in mathematical or biomedical discipline and postgraduate training in epidemiology, statistics, population genetics, 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 and strong interest in non-communicable diseases genetics/epidemiology.