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Traits related to mental health and well-being, such as mood, life satisfaction and sleep, are important for quality of life and have also been shown to be associated with morbidity and mortality. They have been shown to have both genetic and environmental components, some of which are common among traits. However the genetic and environmental determinants of these traits are not yet fully understood and most evidence comes from studies in Western populations.

The aim of the project is to identify genetic variants associated with sleep characteristics, life satisfaction, mood traits and affective disorders, and to investigate the associations of these traits with subsequent development of disease, using data on over 0.5M individuals from the China Kadoorie Biobank (http://www.ckbiobank.org/).

The data available include questionnaire data (including detailed assessment of depressive symptoms, generalized anxiety disorder and major depression, self-reported life satisfaction, prior psychiatric disorders and neurasthenia), blood-based measurements at study baseline and two resurveys, and genetic data on 100,000 participants, as well as follow-up data from disease and death registries and health insurance records, including information on hospitalizations and procedures.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The project will involve a comprehensive review of the relevant literature, standardisation of outcomes, and planning and undertaking statistical analysis in order to examine the associations of interest. The project may include the following areas of work:

  • Genome-wide association analyses of various traits which may have shared genetic components, such as sleep duration, sleep disorder, depressive symptoms, screen-detected generalized anxiety disorder and major depression, life satisfaction and personality traits.
  • Bioinformatics analyses of identified variants to identify biological pathways and processes involved.
  • Investigating the associations of mental health and well-being traits with subsequent morbidity and mortality, such as cardiovascular disease (CVD), accidents and suicide.
  • Using Mendelian randomisation to assess the causality of observed associations, such as the associations of mood disorders and sleep with CVD.

The specific focus of the project can be refined to match the interests of the candidate. The student will work within a multidisciplinary team including epidemiologists, statisticians, geneticists and other scientists. He/she will gain experience in the statistical analysis and handling of large-scale data, interpretation and dissemination of results.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

There are training opportunities in statistics, genetics, epidemiology and other courses provided by the Department and the University. The student will be expected to publish 3-5 peer-reviewed papers and to present their findings at relevant meetings.

PROSPECTIVE CANDIDATE

Students should have a degree in the biomedical or life sciences, or related subject, with a strong interest, and some experience, in genetics, statistics, or epidemiology, or alternatively a degree in statistics or related subject with experience in biomedical research.

Supervisors