Retinal Vessel Biomarkers for Risk Assessment of Incident Diabetic Complications in the WESDR

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 DESCRIPTION (provided by applicant): Persons with diabetes mellitus are at high risk of developing severe complications, presenting a pressing need to prevent them from occurring. It is, therefore, the goal of this epidemiological study to determine the long term relationships of retinal vessel geometric characteristics (such as tortuosity, branching angles, junctional coefficients, fractals, length to diameter ratio) to the incidence of diabetic retinopathy and its progression to severe vision-threatening retinopathy (proliferative diabetic retinopathy and macular edema) as well as to the incidence of systemic complications including diabetic nephropathy, lower extremity amputation, myocardial infarction, and stroke, adjusting for glycemic and blood pressure control and other confounders. A second goal is to determine whether these retinal vessel geometric characteristics can be used for risk assessment for predicting the incidence of early and severe diabetic complications. This proposal builds upon the findings of the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR, funded by NEI grant R01 EY016379), a longitudinal representative cohort study of persons with type 1 and type 2 diabetes. The study includes all insulin-taking persons with type 1 diabetes (n=996) and type 2 diabetes (n=1370) who were receiving primary medical care in an 11-county area of southwestern Wisconsin in 1979-1980 and who were examined in 1980-1982. The cohort was reexamined approximately every 5 years thereafter, with persons with type 1 diabetes participating in up to 7 examinations over a 33-year period and those with type 2 diabetes participating in up to 3 visits over a 10-year period. Retinal vessel geometric characteristics wil be measured from digitized photographs taken at the examinations. The new data from this study will provide a unique opportunity to determine whether changes in these retinal vessel geometric measures can be used as biomarkers to predict the incidence of diabetic complications, and to examine their utility as biomarkers for risk assessment. These data will be important to patients and their physicians for managing their diabetes and to public health practitioners recommending approaches to assess risk and deliver preventive care based on these assessments.