diabetic macular edema exsudative macular degeneration
Conditions
Interventions
None listed
Sponsors
Academisch Medisch Centrum
Eligibility
Age
18 Years to 99 Years
Inclusion criteria
Inclusion criteria: 1. Able and willing to provide written informed consent. Alternatively, a legally authorized representative must be able to consent for the patient. 2. Participants where sampling of >90 µl of AH seems feasible and safe in the opinion of the investigator. 3. Male and female participants aged *18 years for DME participants or * 50 years for nAMD participants or aged * 45 years with age-related cataract (scheduled for cataract surgery) 4. Clear ocular media and adequate pupillary dilation to allow acquisition of good quality retinal imaging 5. DME and nAMD patients with treatment naïve, or ongoing treatment with anti-VEGF
Exclusion criteria
Exclusion criteria: 1. Ocular history of retinal (focal-, pan- or macular) laser photocoagulation within the last 3 months in study eye (in AMD: participants with a history of central macular laser photocoagulation in the study eye are not permitted) 2. History of laser iridotomy or YAG laser capsulotomy within the last month in study eye 3. History of vitreoretinal surgery/pars plana vitrectomy in study eye 4. Uncontrolled glaucoma or ocular hypertension * 25 mmHg in study eye 5. Neovascularization of the iris at screening in study eye 6. Participants affected by any systemic autoimmune disease
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| * To establish values for AH biomarker composition in participants with nAMD or DME | — |
Secondary
| Measure | Time frame |
|---|---|
| * To establish normative baseline values for AH biomarker composition from cataract participants undergoing surgery with no vision impacting retinal pathology * Establish clusters of differentially expressed (vs healthy) AH biomarkers by pathways, including but not limited to angiogenesis, inflammation, apoptosis and fibrosis * To identify and segment disease phenotypes and grade disease severity in DME / nAMD patients from their multi-modal imaging * To utilize advanced analytics to correlate AH biomarker signatures with disease morphology, disease phenotypes and severity * For treatment naïve patients: associate longitudinal AH and imaging biomarkers to model and predict treatment response * To explore correlations between disease, disease status, treatment response and disease relevant genetic polymorphisms | — |
Countries
Netherlands
Outcome results
None listed