Short summary

DECODE-EYE comprises substudies OP_742, OP_743, OP_744, OP_745, OP_746, OP_747 

With this project, we intend to conduct a long series of epidemiological studies, which will provide us with an important understanding of the relationship ocular and systemic disease and between different ophthalmological conditions. 

Rationale

The field of ophthalmology has primarily been examined in clinical studies that are often limited by selection bias and differences in study design and small sample sizes. To account for the shortfalls of clinical studies, register-based data at a real-life national level can contribute to better utilization of the existing data within the field of ophthalmology to explore any unseen potential association and ultimately improve patient care within this field.

Ocular manifestations of systemic disease are common and include conditions like diabetes, hypertension as well as neurological, vascular, and autoimmune diseases. The associations between ocular and systemic diseases are, however, insufficiently understood. Glaucoma, diabetic retinopathy, retinal vascular occlusion, and cataract are examples of eye diseases that can cause visual impairment. Glaucoma is a chronic progressive eye condition that can lead to damage to the optic nerve and visual impairment. Studies have suggested an association between glaucoma and neurodegenerative disorders. Diabetic retinopathy is the most common complication in diabetes and a major cause of visual impairment and blindness. In recent years, retinal neurodegeneration has been recognized as an early event in diabetic retinopathy. The interplay between retinal and systemic neurologic dysfunction is particularly important given the possibilities to monitor retinal dysfunction non-invasively (e.g., screening for diabetic retinopathy) and to support this assumption, proof-of-concept has been established to link diabetic retinopathy with neurological diseases like Alzheimer's, Parkinson's, sleep apnea, depression, and migraine. It has consistently been demonstrated that patients with diabetes have excess mortality, which is mainly explained by a higher risk of macrovascular cardiovascular and cerebrovascular disease. Given that multiple pathophysiological mechanisms are shared between microvascular and macrovascular disease in diabetes, it is possible that diabetic retinopathy, as the most prevalent microvascular complication, may serve as an important risk marker of cardiovascular disease.  Finally, retinal vascular occlusion and cataract have been proposed as markers of systemic disease and aging, and we will use DECODE-EYE to exploit these correlations.

We aim to utilize data from relevant national registers and databases to examine the relationship between ocular diseases and systemic neurological diseases as well as cardiovascular disorders. 

Description of the cohort

Health data from Danish National registers (the National Patient Register, the Civil Registration System, the National Prescription Registry, the Register of Cause of Death), socio-economic data from Statistics Denmark, data from the clinical database the Danish Registry of Diabetic Retinopathy and data from the Danish Association of the Blind will provide data for DECODE-EYE. DECODE-EYE consists of several studies, primarily, designed as matched register-based cohort studies (matched 1:5 by birth year and gender), only a few studies are designed as a population-based cohort study. 

Collaborating researchers and departments

DECODE EYE-Danish Excellence Center in Ophthalmic Epidemiology consists of an international and cross-regional epidemiological research network of leading researchers in the fields of ophthalmology and epidemiology.

The lead investigator is Professor Jakob Grauslund, Odense University Hospital (OUH) and University of Southern Denmark (SDU), and the steering committee includes Associate Professor Katrine Hass Rubin (OPEN and SDU), Professor Morten la Cour (University of Copenhagen [UCPH]), Professor Kirsten Kyvik (SDU), Associate Professor Line Kessel (UCPH), and Head of Department Gerda Nørrelykke Møller (OUH).

We will take advantage of the strong epidemiological environment of OPEN at OUH and SDU. To support the study, Katrine Hass Rubin will serve as Lead Data Manager, and we will rely on the expertise of Data Manager Lonny Stokholm (OPEN) and Biostatistician Sören Möller (OPEN).

• OPEN Odense Patient data Exploratory Network, Odense University Hospital, University of Southern Denmark
• The University of Copenhagen