Identification of new candidate genes for retinopathy in type 2 diabetics. Valencia Study on Diabetic Retinopathy (VSDR). Report number 3. / Identificación de nuevos genes candidatos para la retinopatía en diabéticos tipo 2. Estudio Valencia sobre Retinopatía Diabética (EVRD). Informe n.° 3.

OBJECTIVE: To identify genes involved in the pathogenic mechanisms of non-proliferative diabetic retinopathy (NPDR), among which include oxidative stress, extracellular matrix changes, and/or apoptosis, in order to evaluate the risk of developing this retinal disease in a type2 diabetic (DM2) population. MATERIAL AND METHODS: A case-control study was carried out on 81 participants from the Valencia Study on Diabetic Retinopathy (VSDR) of both genders, with ages 25-85years. They were classified into: (i)DM2 group (n=49), with DR (+DR; n=14) and without DR (-DR; n=35), and (ii)control group (GC; n=32). The protocols included a personal interview, standardised ophthalmological examination, and blood collection (to analyse the DNA for determining the gene expression (TP53, MMP9, and SLC23A2) in the study groups. Statistical analyses were performed using the SPSS v22.0 program. RESULTS: The TP53 and MMP9 genes showed a higher expression in the DM2 group compared to the GC, although the difference was only significant for the MMP9 gene (TP53: 10.40±1.20 vs. 8.23±1.36, P=.084; MMP9: 1.45±0.16 vs. 0.95±0.16, P=.036), and the SLC23A2 gene showed a significant lower expression in the DM2 vs CG (5.58±0.64 vs. 11.66±1.90, P=.026). When sub-dividing the DM2 group according to the presence of retinopathy, the expression of the TP53, MMP9 and SLC23A2 genes showed significant differences between the DM2-RD, DM2+RD and GC groups (TP53: 9.95±1.47 vs. 11.52±2.05 vs. 8.23±1.36, P=.038; MMP9: 1.47±0.20 vs. 1.41±0.27 vs. 0.95±0.16, P=.021; SLC23A2: 5.61±0.77 vs. 5.51±1.21 vs. 11.66±1.90, P=.018). CONCLUSIONS: Genes involved in extracellular matrix integrity (MMP9) and/or apoptosis (TP53), could be considered potential markers of susceptibility to the development/progression of NPDR. Interestingly, the SLC232A2 gene (ascorbic acid transporter) can be considered a protector of the risk of the development/progression of the retinopathy.

[From scientific evidence to clinical practice: treatment protocols for diabetic macular edema]. / De la evidencia científica a la práctica clínica: pautas de tratamiento del edema macular diabético.

Diabetic macular edema (DME) is now considered the leading cause of moderate vision loss in type 2 diabetic patients and has a high socioeconomic burden. In recent years, the therapeutic approach to this entity has changed. The role of laser treatment, considered the gold standard in clinical practice worldwide for more than 25 years, has been redefined. To understand current treatment algorithms, the pathophysiology of diabetic macular edema and the role played by vascular endothelial growth factor must be elucidated. Many clinical trials have emerged showing that intravitreal ranibizumab provides effective therapy with an acceptable safety profile. Based in these data, the European Medicines Agency has approved ranibizumab for the treatment of diabetic macular edema. This article aims to discuss new treatment options and the recently developed evidence-based algorithms.

[Retinal image analysis to detect lesions associated with diabetic retinopathy]. / Tratamiento digital de retinografías para detectar automáticamente lesiones asociadas con la retinopatía diabética.

PURPOSE: Diabetic retinopathy is a leading cause of vision loss in developed countries. Regular diabetic retinal eye screenings are needed to detect early signs of retinopathy, so that appropriate treatments can be rendered to prevent blindness. Digital imaging is becoming available as a means of screening for diabetic retinopathy. However, with the large number of patients undergoing screenings, medical professionals require a tremendous amount of time and effort in order to analyse and diagnose the fundus photographs. Our aim is to develop an automatic algorithm using digital image analysis for detecting these early lesions from retinal images. METHODS: An automatic method to detect hard exudates, a lesion associated with diabetic retinopathy, is proposed. The algorithm is based on their colour, using a statistical classification, and their sharp edges, applying an edge detector, to localise them. RESULTS: A sensitivity of 79.62% with a mean number of 3 false positives per image is obtained in a database of 20 retinal images with variable colour, brightness and quality. It can also be seen that the number of the false negative cases increases when the hard exudates were very close to the vessel tree. CONCLUSION: The long term goal of the project is to automate the screening for diabetic retinopathy with retinal images. We have described the preliminary development of a tool to provide automatic analysis of digital fundus photographs to localise hard exudates. Future work will address the issue of improving the obtained results and also will focus on detecting other lesions.