%0 Journal Article
%T Identifying subtypes of patients with neovascular age-related macular degeneration by genotypic and cardiovascular risk characteristics
%A Michael Feehan
%A John Hartman
%A Richard Durante
%A Margaux A Morrison
%A Joan W Miller
%A Ivana K Kim
%A Margaret M DeAngelis
%J BMC Medical Genetics
%D 2011
%I BioMed Central
%R 10.1186/1471-2350-12-83
%X We identified a sample of patients with neovascular AMD, that in previous studies had been shown to be at elevated risk for the disease through environmental factors such as cigarette smoking and genetic variants including the complement factor H gene (CFH) on chromosome 1q25 and variants in the ARMS2/HtrA serine peptidase 1 (HTRA1) gene(s) on chromosome 10q26. We conducted a multivariate segmentation analysis of 253 of these patients utilizing available epidemiologic and genetic data.In a multivariate model, cigarette smoking failed to differentiate subtypes of patients. However, four meaningfully distinct clusters of patients were identified that were most strongly differentiated by their cardiovascular health status (histories of hypercholesterolemia and hypertension), and the alleles of ARMS2/HTRA1 rs1049331.These results have significant personalized medicine implications for drug developers attempting to determine the effective size of the treatable neovascular AMD population. Patient subtypes or clusters may represent different targets for therapeutic development based on genetic pathways in AMD and cardiovascular pathology, and treatments developed that may elevate CV risk, may be ill advised for certain of the clusters identified.The current medical literature is increasing weekly with studies identifying DNA variants and their possible interaction with environmental factors that may have impact on risk of disease. The growth of such studies has been spurred by the promise of understanding the genetic and environmental basis of complex diseases, and the possibility of identifying therapeutically responsive targets for drug development. Enormous numbers of DNA variants have been associated with diseases and traits and this number will only grow as it becomes economically feasible to sequence an individual patient's entire genome[1].One key data interpretation challenge lies in how best to assess the phenotypic heterogeneity and risk factor heterogeneity with
%U http://www.biomedcentral.com/1471-2350/12/83