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Background

Globally, about 1.3 billion people live with some form of vision impairment and the number is expected to significantly increase in future decades due to population growth and aging. Even mild vision impairment can have considerable economic costs and adverse influences on quality of life. The common eye diseases that can cause vision loss or impairment include cataract, glaucoma, diabetic retinopathy, and age-related macular degeneration (AMD). Appropriate understanding of their aetiology and risk factors is essential for improvement in prevention, early diagnosis and treatment.

About one-third of individuals with diabetes are expected to develop diabetic retinopathy, and the risk is substantially higher in many low- and middle-income countries, including China, where diabetes is poorly detected and managed. Glaucoma now affects >60 million adults worldwide and can cause irreversible blindness globally. In China, about 3% of the population has glaucoma, and primary angle-closure glaucoma (PACG) is the major subtype, in contrast with Western populations where primary open-angle glaucoma (POAG) predominates. The causes of glaucoma, particularly PACG, and many other eye diseases are still not fully understood and most of the previous research has been constrained by small study size or use of retrospective study design.

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. To date, >2000 glaucoma cases and >6000 cases of diabetic retinopathy have been recorded during 10-year follow-up among participants. The exposure and outcome data are being complemented by genetic (currently 100,000 genotyped) and other omics assays. Moreover, data on intraocular pressure (IOP) and retinal images will be collected by late 2021 among ~25,000 CKB participants as part of the on-going third resurvey, together with visual acuity measurement and other information on 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 IOP and glaucoma, diabetic retinopathy, and other retinal diseases in Chinese adults. 

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The specific DPhil project will be subject to further discussion and personal interest, but may focus on a specific disease area and include the following areas of work:

  1. To examine the patterns and associations of lifestyle, environmental, and genetic risk factors with different types of eye diseases (e.g. glaucoma, diabetic retinopathy, AMD);
  2. To characterise IOP, its main correlates and associations with development of common eye diseases;
  3. To characterise macular, retinal vasculature and optic nerve abnormalities based on the retinal images captured among ~25,000 participants;
  4. To develop and enhance algorithms, using machine learning and/or AI-based approach, for early detection of diabetic retinopathy and other retinal diseases 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, epidemiological and statistical methodology, statistical programming, data analysis and scientific writing. It is anticipated that the candidate will publish their results by the end of their DPhil.   

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

The project will provide an extensive range of training opportunities through attending specific courses, meetings, workshops and seminars, along with regular supervisory meetings. There may be opportunities to work with external partners from industry and other research institutions. 

prospective candidate

Candidates should have a higher degree in imaging sciences, medicine, epidemiology, or another related area. Previous postgraduate training or experience in epidemiology or statistics is necessary. Candidates should also have a strong interest in the epidemiology of eye disease.

Supervisors