ABSTRACT
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.
Subject(s)
Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/genetics , Diabetic Retinopathy/genetics , Genetic Association Studies , Adult , Aged , Aged, 80 and over , Case-Control Studies , Female , Humans , Male , Middle Aged , SpainABSTRACT
El edema macular diabético está considerado como la causa más frecuente de pérdida moderada de visión en los pacientes diabéticos y un problema de gran trascendencia sociosanitaria, cuyo abordaje terapéutico se ha modificado en los últimos años. El papel del láser, considerado como el "gold standard" del tratamiento desde hace más de 25 años, ha sido redefinido. Para entender los algoritmos actuales de tratamiento es necesario indagar en la fisiopatología de esta enfermedad y en el papel desempeñado por el factor de crecimiento vascular endotelial. Los ensayos clínicos llevados a cabo con ranibizumab han demostrado la capacidad de este fármaco de modificar el pronóstico funcional de esta enfermedad y sus resultados han permitido la aprobación de la indicación de edema macular diabético por la Agencia Europea del Medicamento. En este trabajo se discuten las opciones actuales de tratamiento para el edema macular diabético y los algoritmos desarrollados según la evidencia científica (AU)
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 (AU)
Subject(s)
Humans , Male , Female , Clinical Clerkship/methods , Clinical Clerkship/trends , Evidence-Based Medicine/methods , Evidence-Based Medicine/trends , Evidence-Based Practice/methods , Macular Edema/epidemiology , Macular Edema/prevention & control , Light Coagulation/trends , Light Coagulation , Clinical Clerkship/organization & administration , Clinical Clerkship/standards , Macular Edema/physiopathology , Macular Edema/therapy , Angiogenesis Inhibitors/therapeutic use , Laser TherapyABSTRACT
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.
Subject(s)
Angiogenesis Inhibitors/therapeutic use , Antibodies, Monoclonal, Humanized/therapeutic use , Diabetic Retinopathy/drug therapy , Macular Edema/drug therapy , Translational Research, Biomedical/methods , Algorithms , Angiogenesis Inhibitors/administration & dosage , Antibodies, Monoclonal, Humanized/administration & dosage , Aptamers, Nucleotide/therapeutic use , Bevacizumab , Clinical Protocols , Diabetic Retinopathy/diagnosis , Diabetic Retinopathy/pathology , Diabetic Retinopathy/surgery , Drug Approval , European Union , Fluorescein Angiography , Humans , Laser Coagulation , Macular Edema/classification , Macular Edema/diagnosis , Macular Edema/pathology , Macular Edema/surgery , Microscopy, Acoustic , Multicenter Studies as Topic , Randomized Controlled Trials as Topic , Ranibizumab , Receptors, Vascular Endothelial Growth Factor/therapeutic use , Recombinant Fusion Proteins/therapeutic use , Tomography, Optical Coherence , Triamcinolone Acetonide/therapeutic use , Vascular Endothelial Growth Factor A/antagonists & inhibitorsABSTRACT
Objetivos: La retinopatía diabética es la causa más frecuente de ceguera en la población activa de los países industrializados. Para retrasar su evolución y evitar así la pérdida de visión, el mejor método de prevención es un seguimiento regular médico. Para ello, se utilizan las imágenes de fondo de ojo o retinografías. Sin embargo, debido al gran número de pacientes, se requiere mucho esfuerzo y tiempo para revisar todas las imágenes. El objetivo de este trabajo es desarrollar un método automático que ayude a detectar los primeros síntomas de la retinopatía diabética mediante un tratamiento digital de las retinografías. Métodos: El método expuesto en este artículo se centra exclusivamente en la detección de exudados duros, uno de los primeros síntomas de la retinopatía diabética. Su localización automática se basa en su color, usando clasificación estadística, y sus bordes definidos, mediante un filtro detector de bordes. Resultados: Aplicando el algoritmo propuesto a 20 retinografías de distinta calidad, iluminación y color, obtuvimos una sensibilidad de 79,62% con una media de 3 falsos positivos por imagen. El número de falso negativos aumentaba sobre todo cuando los exudados aparecían muy cerca de los vasos sanguíneos. Conclusión: El objetivo final de este proyecto es automatizar el seguimiento médico de la retinopatía diabética mediante el tratamiento digital de las retinografias de los pacientes. En esta primera etapa, se ha desarrollado una herramienta que permite la detección automática de una lesión asociada a esta enfermedad: los exudados duros. En futuros trabajos se pretende mejorar los resultados obtenidos y continuar con la localización de otras lesiones(AU)
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(AU)
Subject(s)
Humans , Diabetic Retinopathy/diagnosis , Retinal Drusen/physiopathology , Diabetes Complications , /methods , False Negative Reactions , Mass ScreeningABSTRACT
No disponible
Subject(s)
Humans , Macular Edema , Diabetic Retinopathy , International Classification of Diseases , Severity of Illness Index , Severity of Illness IndexABSTRACT
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.
