Abstract
Purpose::
To evaluate the protein expression profiles from serum samples of persons with proliferative diabetic retinopathy, end-stage open angle glaucoma, and age-related macular degeneration as compared to individuals without ocular disease.
Methods::
Serum samples from 38 participants were selected for this study. This included 6 case-control pairs of persons with end-stage open angle glaucoma and proliferative diabetic retinopathy, and 7 case-control pairs of those with age-related macular degeneration. Controls were free from glaucoma, diabetic retinopathy, and age-related macular degeneration, and they were matched to age, gender, smoking status, history of cardiovascular disease, hypertension, and alcohol use. Controls paired to those with proliferative diabetic retinopathy were also matched to duration since diabetes diagnosis and hemoglobin A1c levels. Equalized serum sample fractions were analyzed using SELDI-TOF-MS ProteinChip Arrays with two different chromatographic surfaces (CM10 weak cation exchange and H50 hydrophobic or IMAC30 metal-affinity). The data were analyzed by univariate and multivariate statistical techniques.
Results::
Several hundred protein peaks (mass/charge ratios) were consistent across samples and chip sites. After exclusion of peaks with poor resolution and low signal-to-noise ratios, univariate analysis was performed, and 6-10 differentially expressed protein biomarkers were found between the disease versus control groups. Select candidate proteins were identified by off-line purification and tandem mass spectrometry (MSMS).
Conclusions::
The identification of serum biomarkers for ocular diseases such as proliferative diabetic retinopathy, end stage glaucoma, or age-related macular degeneration could provide insight into the pathogenesis of the diseases.
Keywords: proteomics • diabetic retinopathy • age-related macular degeneration