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Open Access Research article

Identifying subtypes of patients with neovascular age-related macular degeneration by genotypic and cardiovascular risk characteristics

Michael Feehan1, John Hartman1, Richard Durante1, Margaux A Morrison23, Joan W Miller2, Ivana K Kim2 and Margaret M DeAngelis23*

Author Affiliations

1 Observant LLC, 1601 Trapelo Road, Waltham, MA, 02451, USA

2 Ocular Molecular Genetics Institute and the Retina Service, Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, 243 Charles Street, Boston, MA, 02114, USA

3 3 Ophthalmology and Visual Sciences, University of Utah, Moran Eye Center, 65 Mario Capecchi Drive, Salt Lake City, UT, 84132, USA

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BMC Medical Genetics 2011, 12:83  doi:10.1186/1471-2350-12-83

Published: 17 June 2011

Abstract

Background

One of the challenges in the interpretation of studies showing associations between environmental and genotypic data with disease outcomes such as neovascular age-related macular degeneration (AMD) is understanding the phenotypic heterogeneity within a patient population with regard to any risk factor associated with the condition. This is critical when considering the potential therapeutic response of patients to any drug developed to treat the condition. In the present study, we identify patient subtypes or clusters which could represent several different targets for treatment development, based on genetic pathways in AMD and cardiovascular pathology.

Methods

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.

Results

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.

Conclusions

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.