“Discriminat Analysis Of Serum Biochemical Parameters In Dry And Wet Age Related Macular Degeneration Patients”

J.D. LUNA PINTO; GRAMAJO L; COLLINO C; FORZINETTI G; FERRER D; JUAREZ CP; SANCHEZ MC

Fort lauderdale

Otro; ARVO´s 2010 Annual Meeting (The Association for Research in Vision and Ophthalmology).; 2010

Purpose: The biochemical and molecular mechanisms responsible for the pathogenesis of wet and dry age-related macular degeneration (ARMD) are not yet established. Hence, in the present work we apply discriminant statistical analysis associating biochemical parameters with funduscopic characteristics from wet and dry ARMD patients.Methods: After a complete eye examination, peripheral whole blood was obtained from patients with ARMD (n=40) and age-matched non-ARMD patients (n=15). The ARMD group was clinically divided into two subgroups: wet ARMD (20) and dry ARMD (20). Quantitative assays were performed for more than 22 different biochemical parameters measured by conventional clinical laboratory tests and flow cytometry. LRP1 was determined from monocytes of peripheral blood by flow cytometry using RD1-conjugated monoclonal antibody against human LRP1 alpha chain. At least 2,000 gated monocytes were acquired in each sample using the flow cytometer. All biochemical, cytometric and clinical parameters were analyzed using Lineal Discriminant Analysis (forward stepwise mode) and Kruskal Wallis (Statistica version7.0).Results: A principal component analysis allowed us to select 18 biochemical parameters (out of 22 analyzed) as the most important for discerning these three different groups. The parameters found were: LRP1 together with LDL; HDL-cholesterol; Lymphocytes (Ly); subpopulation CD3 (CD3); subpopulation CD8 (CD8) and CD4 ; double positive subpopulation CD4CD8 (DP); Red cell distribution width (RDW) between others 9 basic parameters . These 18 parameters allow us to differentiate these three groups with a 66.5% certainty. Conclusions: These results indicate that these 18 biochemical parametersare simple parameters that could predict dry ARMD from wet ARMD and age-matched non-ARMD patients.