Principal Investigator: Dr Alexander Day
Department: Biomedical Research Building
Moorfields Eye Hospital NHS Foundation Trust, Biomedical Research Building, 2nd Floor RDEC Building, 162 City Road, London EC1v 2PD, United KingdomTags: 10536, Cataract, diet, genetics, lifestyle, vision
Funding body: Internally funded from existing grants
1a: The anterior segment (front) of the eye includes the lens and cornea. Diseases of these can cause significant visual problems. For example, cataract (clouding of the lens), is the leading cause of blindness in the world and cataract surgery is the most commonly performed operation in the UK. Diseases of the cornea include keratoconus, a progressive thinning and bulging, which is the most common cause of corneal transplantation in the developed world. Analyses of UKBiobank data will potentially allow identification of new risk factors and disease associations, and new treatments.
1b: This research fits entirely within the remit of the UK Biobank’s stated purpose. Namely:
-Cataract is a major disease of middle and old age, and keratoconus is a disease of early to middle adulthood.
-Data from the UKBiobank will allow investigations of the individual and combined effects of environmental, lifestyle, biometric and genetic factors on cataract and keratoconus.
-The findings of this research will potentially improve the prevention, diagnosis and treatment of diseases of anterior segment of the eye.
1c: We will identify UKBiobank participants who have the condition of interest (cases) and those without (controls). The environmental, lifestyle, biometric and genetic characteristics between the cases and controls will then be compared. For example for cataracts, we will identify people who have had cataract surgery from their health records and compare them to people who have not yet had cataract surgery. This data can then be used to infer risk factors for disease and also factors that may be preventative, thus suggesting potentially novel treatment areas. Associations with other diseases may imply common disease pathways.
1d: We will use the full dataset of approximately 500,000 people.