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Background

Worldwide obesity affects about 700 million adults with the prevalence still rising steadily in most countries. Although the health effects of adiposity on cardio-metabolic diseases and many cancers are well established, substantial uncertainty remains about its relevance, including both the shape and strength of associations, for many other diseases. Moreover, the relative importance of different measures of adiposity (e.g. general vs central obesity) in predicting disease risks and biological mechanisms underpinning the associations of adiposity with different diseases has still not been properly investigated. Large prospective biobanks are well positioned to investigate these questions.

The prospective China Kadoorie Biobank (CKB) recruited >0.5 million adults from 10 diverse areas across China during 2004-08, with extensive data collection by questionnaire and physical measurements (including different measures of adiposity) (http://www.ckbiobank.org/). To date, the study has recorded >55,000 deaths and >1.2 million episodes of hospitalisation, involving >5000 different disease types. These exposure and health outcome data are being complemented by sample assays, including genetics (currently 100K genotyped and 10K sequenced), metabolomics and proteomics in a subset of participants. These data should enable comprehensive assessment of adiposity-related disease burden and the likely mechanisms underpinning the associations in Chinese adults. 

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

A range of projects are available. The specific research areas of the DPhil project will be developed in discussion with the student and, depending on their interests and aptitude, may include one or more of the following objectives:

  1. To comprehensively assess the burdens of disease mortality and morbidity attributed to adiposity;
  2. To investigate the relative importance of different measures of adiposity in predicting risks of specific diseases and associations with established and emerging biomarkers;
  3. To determine the causal relevance of adiposity for risks of specific diseases, using Mendelian randomisation approaches;
  4. To explore the mechanisms linking adiposity with development of specific diseases, utilising multi-dimensional ‘omics and genomic data;
  5. To compare the associations, both qualitatively and quantitatively, of adiposity with specific diseases and/or traits in Chinese adults with those in the UK populations

The student will work within a multi-disciplinary team, and will gain research experience in systematic literature review, study design and planning, data analysis and scientific writing. There will also be in-house training in epidemiology, statistical programing and computational genetics. By the end of the DPhil, the student will be competent to plan, undertake and interpret analyses of large and high dimensional datasets, and to report research findings, including some publications as the lead author in peer-reviewed journals and presentation at national/international conferences.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

The project will be based within the CKB research group, part of the Nuffield Department of Population Health and based in the Big Data Institute. There are excellent facilities and a world-class community of population health, data science and genomic medicine researchers. There may be opportunities to work with external partners from industry and other research institutions. 

PROSPECTIVE STUDENT

Candidates should have a 2.1 and a higher degree in epidemiology, statistics, genetics, biomedical science, or another related area, with a strong interest in population health and epidemiology. The project will involve large-scale data analyses and requires relevant previous experience.

Supervisors