Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.


Large-scale population studies have identified several hundred common and low frequency genetic variants which are associated with various reproductive traits, such as pubertal timing and fertility. Most previous studies have involved Western populations with limited evidence from Chinese or other non-Western populations. Data from non-European ancestries is becoming increasingly important, not only to understand the difference between populations, but also to exploit the contrasting patterns of association for “fine mapping” of the “causal variants” that are responsible for the observed association.

China Kadoorie Biobank (CKB) is a prospective cohort of 0.5 million adults aged 30-79 years at recruitment during 2004-08 ( Questionnaire data and physical measurements were collected at baseline, and follow-up is through linkage to registry and health insurance records. Genome-wide data with imputation of 10M genetic variants is available for 100,000 participants.

This project will identify and characterise genetic variants associated with a range of reproductive traits in Chinese women, such as ages at menarche and menopause, number of children (also reported in men), age at first birth, miscarriage, and breastfeeding.


The project will include:

  1. Literature reviews and selection of reproductive traits, which may depend on the interest of the student.
  2. Genome-wide analysis of reproductive traits including data QC and association analysis; meta-analysis across datasets; fine mapping and trans-ethnic analyses.
  3. Use of bioinformatics tools to investigate the biological roles and potential functional effects of identified loci and variants.
  4. Explore shared genetic aetiology between different reproductive traits and other health outcomes e.g. cardio-metabolic risk factors.

There will be in-house training in epidemiology and in statistical and computational genetics, attendance at relevant external courses such as the Wellcome Trust course “Design and Analysis of Genetic-based Association Studies” will also be possible.


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, genetic and data scientists. There will be opportunities to participate in international collaborations and/or consortia.

prospective candidate

The candidate should have a 2.1 or higher degree in a biomedical or quantitative science, with a strong background and interest in genetics, statistics and/or reproductive health.