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This project will be supported with an MRC PHRU Studentship if there is a suitable candidate.

Background

About one-third of individuals with Type 2 diabetes (T2D) are expected to develop diabetic retinopathy (DR), and the risk is substantially higher in many low- and middle-income countries, including China, where diabetes is poorly detected and managed. DR and other retinal diseases, including age-related macular degeneration (AMD) and retinal vein occlusion, are major contributors to impaired vision globally. Population ageing and escalating rates of obesity and T2D are expected to contribute to increasing prevalence of these eye conditions, for which early detection is critical for the prevention of related vision loss.

The China Kadoorie Biobank (CKB) is a large prospective cohort study of >0.5 million adults who were recruited from 10 diverse areas across China during 2004-08 (http://www.ckbiobank.org/). To date, >5000 cases of DR have been recorded among participants through electronic linkages to hospital records. During 2019-20, retinal images will be collected from ~25,000 participants during the third resurvey, providing an opportunity for comprehensive assessment of the burden, detection and risk factors of DR 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 include the following areas of work:

  1. Using machine learning and/or AI-based approach to diagnose DR and other retinal diseases, and to characterise macular, retinal vasculature and optic nerve abnormalities based on the retinal images captured among ~25,000 participants;
  2. To validate the retinal image-based diagnosis of DR and other retinal diseases using the hospital diagnosis of these conditions collected through linkages to health insurance data;
  3. To investigate the patterns and associations of environmental and lifestyle factors with risks of RD and AMD, and potential mediation by other factors (e.g. smoking, BMI);
  4. To identify genetic risk factors for RD and AMD using genome-wide genotyping data generated (currently ~100K participants) or to be generated.

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, workshop and seminars, along with regular supervisory meetings. There may be opportunities to become involved in field work related to retinal photography in China and to work with external partners from industry and other research institutions. 

PROSPECTIVE CANDIDATE

A higher degree in vision 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 epidemiology of eye disease.

Supervisors