Superoxide Dismutase1 Levels in North Indian Population with Age-Related Macular Degeneration

Aim. The aim of the study was to estimate the levels of superoxide dismutase1 (SOD1) in patients of age-related macular degeneration (AMD) and examine the role of oxidative stress, smoking, hypertension, and other factors involved in the pathogenesis of AMD. Methods. 115 AMD patients and 61 healthy...

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Bibliographic Details
Main Authors: Akshay Anand, Neel K. Sharma, Amod Gupta, Sudesh Prabhakar, Suresh K. Sharma, Ramandeep Singh
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Oxidative Medicine and Cellular Longevity
Online Access:http://dx.doi.org/10.1155/2013/365046
Description
Summary:Aim. The aim of the study was to estimate the levels of superoxide dismutase1 (SOD1) in patients of age-related macular degeneration (AMD) and examine the role of oxidative stress, smoking, hypertension, and other factors involved in the pathogenesis of AMD. Methods. 115 AMD patients and 61 healthy controls were recruited for this study. Serum SOD1 levels were determined by ELISA and were correlated to various risk factors. Logistic regression model of authenticity, by considering SOD1 as independent variable, has been developed along with ROC curve. Results. The SOD1 levels were significantly higher in AMD patients as compared to those of the controls. The difference was not significant for wet and dry AMD. However, the difference was significant between wet AMD subtypes. Nonsignificance of the Hosmer-Lemeshow goodness of fit statistic (χ2=10.516, df=8, P=0.231) indicates the appropriateness of logistic regression model to predict AMD. Conclusion. Oxidative stress in AMD patients may mount compensatory response resulting in increased levels of SOD1 in AMD patients. To predict the risk of AMD on the basis of SOD1, a logistic regression model shows authenticity of 78%, and area under the ROC curve (0.827, P=.0001) with less standard error of 0.033 coupled with 95% confidence interval of 0.762–0.891 further validates the model.
ISSN:1942-0900
1942-0994