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Globally, about 1.3 billion people suffer from vision impairment and this number is expected to increase further with population growth and ageing. Several common eye diseases - such as cataract, glaucoma, diabetic retinopathy (DR), and age-related macular degeneration (AMD) - are the major contributors to vision impairment but their aetiology and risk factors are still poorly understood, especially in Chinese population where the burden, disease phenotypes (e.g., primary angle-closure vs primary open-angle glaucoma) and management of related conditions (e.g., diabetes) differ importantly from those typically seen in the Western populations.  

The China Kadoorie Biobank (CKB) is a large prospective cohort study of >0.5 million adults recruited from 10 diverse areas across China during 2004-08 (http://www.ckbiobank.org/). To date, nearly 15,000 cataract cases, >2000 glaucoma cases and >6000 cases of DR have been recorded among participants through electronic linkages to hospital records. Moreover, intraocular pressure (IOP) and retinal images are being collected in ~25,000 CKB participants, together with visual acuity and other detailed medical history of vision and eye diseases. This highly enriched database will provide a great opportunity for comprehensive assessment of the patterns and risk factors of cataract, glaucoma and IOP, DR, and other retinal diseases in Chinese adults.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The specific DPhil project will be developed in discussion with the student, and depending on their interests and abilities, may focus on a specific disease area, covering the following areas of work:

  1. To investigate the patterns and associations of environmental and lifestyle factors, including related biomarkers, with risks of selected eye diseases (e.g. glaucoma and levels of IOP; RD and AMD);
  2. To identify genetic risk factors for selected eye diseases using genome-wide genotyping data in CKB (and other available datasets);
  3. To assess the causality of associations in observational epidemiology using Mendelian randomisation;
  4. To explore the possibility of developing a machine learning and/or AI-based approach for diagnosing DR and other retinal diseases, and characterising macular, retinal vasculature and optic nerve abnormalities based on the retinal images captured among ~25,000 participants.

The student will work within a multi-disciplinary team, and will gain research experience in systematic literature review, study design and planning, statistical analysis and scientific writing. There will be in-house training in epidemiology, statistics, and genetics. If necessary, the student can also attend relevant external training courses e.g. genetic association studies. By the end of the DPhil, the student will be competent to plan, undertake and interpret analyses of large-scale data, 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 located 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 higher degree in epidemiology, statistics or another related area. They should also have a strong interest in vision science and epidemiology of eye diseases.

Supervisors