Diabetic retinopathy (DR) is retinal disease and a condition that develops after long lasting and poorly handled diabetes type 1 or 2. The development of treatment and medicine for reducing disease progression refers on genetics, pathophysiology and protein interactions research. Data in literature is very heterogeneous and not coherent, thus the research and understanding of the disease is challenged and time comsuming. Curated database of genes associated with DR does not yet exist, but with such we could potentially chose biomarkers, which can be used to potentially forsee the development of the disease and adjust the treatment for patient. Aims of the research were: 1. development of database of genes associated with DR, 2. determine reliable biomarkers using bioinformatics tools and 3. develop a test for genotyping of a chosen gene with KASP (KBioscience Competitive Allele-specific PCR Amplification) method. By text mining we obtained 389 articles which were manually checked and obtained data was ordered in database named DRdb. The data from genomic databases was used to unify the names of genes and polymorphisms. Then we added identification numbers (IDs) of genes, diseases, publications and taxonomic IDs of species. Final DRdb consists of 244 genes associated with DR researched in human and animal species. For identification of potential biomarkers we analysed 189 genes from DRdb associated with DR on human, performed enrichment analysis using publicly available bioinformatics tools and determined 15 critical regions in human genome where the distance between genes is less than 1 Mbp. Based on the analysis of biological pathways associated with 189 we proposed gene selectin E (SELE) as potential biomarker for DR. We developed first detailed database with an overview on genes associated with DR, which was then used for identification of potential biomarker. The research will contribute to the understanding of molecular mechanisms of DR in the future.
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