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Circulating levels of sex hormones and insulin-like growth factor-I (IGF-I) are known to be associated with measures of body fatness and the subsequent risk of developing particular cancers.  However, little is known about the effect of these hormones across a wide range of health outcomes.  UK Biobank has lifestyle, physical and biomarker measurements for the full cohort (500,000 men and women), with follow-up through electronic medical records.  Such a resource provides a unique opportunity to conduct research into the association of these biomarkers across many phenotypes (commonly known as a PheWAS).  Such an approach can generate new hypotheses for further exploration and lead to new insights into disease mechanisms.


This project provides an opportunity to use a range of methods to assess the relationship between hormonal biomarkers and a unprecedented wide and diverse range of phenotypes, including traits (e.g., body composition, strength, bone mineral density) and well-characterised health outcomes (e.g., cancer, cardiovascular disease, diabetes), plus other outcomes that have been little studied  - through a systematic and unbiased analysis of hospital in-patient disease codes and NHS cancer and death registry data.  This project will enable the student to develop statistical skills required to deal with large-scale and complex data, and to develop epidemiological skills needed to interpret such data.

field work, secondments, industry placements and training

This project will provide the successful applicant with excellent training in large-scale epidemiology, the statistical analysis of cohort data and will provide opportunities to network with other investigators. He/she will receive training in conducting literature reviews and writing academic papers for peer-reviewed journals and will work closely with a strong interdisciplinary team of researchers with expertise in epidemiology, statistics, clinical medicine and biochemistry.

prospective candidate

This project will suit someone with an interest in the relationship of aetiological biomarkers (in particular hormones and growth factors) with health outcomes. This student will be looking to expand their skills  and experience in the field of large-scale prospective epidemiology, including the statistical analysis of epidemiological data, and will be interested in exploring the use of routine electronic medical records for research purposes.