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Worldwide chronic infection of pathogens is responsible for >2 million new cancer cases each year. The relevance of several pathogens such as H. pylori, HBV, HCV, and HPV for certain cancers is well established, but their roles for non-neoplastic diseases is less clear. There is evidence that other pathogens (e.g. EBV, HTLV-1) may also associate with risks of certain cancers. Furthermore, the risk of developing particular diseases and/or disease subtypes and long-term prognosis may likely be affected by host immunity, pathogen subtype, other factors and their complex interactions. Large prospective biobank studies are well positioned to assess these questions.

The prospective China Kadoorie Biobank included 0.5 million Chinese adults recruited during 2004-08 from 10 diverse areas across China, with extensive data collection by questionnaire and physical measurements, and with long-term follow-up for health outcomes through linkage to death registries and hospital records ( To date, >50,000 deaths and >1.2 million hospitalisation episodes for >5000 different disease types (including >35,000 incident cancer cases) have been recorded. These exposure and outcome data are complemented by on-going multiplex serology assays (19 pathogens in ~40,000 participants), genotyping and other omics data (e.g. inflammation) in a subset of participants. Moreover, HBV viral genomes will be sequenced in >4000 HBV-infected participants to investigate the role of host-virus interactions in development and prognosis of liver cancer and liver diseases.


The specific lines of investigation covered by this DPhil project will depend on the student’s interests and previous training, and may include the following areas of work:

  • To examine the associations of chronic infection of particular pathogens with risks of different types of cancers;
  • To explore the role of host immune system genetics (e.g. HLA) in susceptibility to specific types of chronic infection and cancer;
  • To establish the value of serological markers, in combination with other lifestyle and genetic risk factors, in predicting the risk of infection-related cancers.

There will be in-house training opportunities in epidemiology, statistics, genetics, and bioinformatics and if necessary attendance at relevant courses. By the end of the DPhil, the student will be competent to review the literature, to plan, undertake and interpret analyses of large-scale data, and to report research findings, including some publications in peer-reviewed journals and presentation at conferences.


The student will be based within the CKB research group in NDPH. There are excellent facilities and a world-class community of population health, data science and genomic medicine researchers.


The ideal candidate should have a good degree in a biomedical or quantitative science, with an interest in epidemiology and, with some experience in statistics and programming.