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Genetic analysis of simultaneous geographic atrophy and choroidal neovascularization.

ABSTRACT: To investigate clinical presentation and genotypes in patients with simultaneous geographic atrophy (GA) and choroidal neovascularization (CNV) and to compare with patients with GA or CNV only.Twenty patients with combined CNV-GA and 154 CNV only and 154 GA only were chosen based on clinical exam and imaging. Six single-nucleotide polymorphisms (SNPs)-rs2274700 and rs1061170 (complement factor H), rs10490924 and rs11200638 (HTRA1/LOC387715), rs2230199 (C3), rs9332739 (C2)-were genotyped using the SNaPshot method. Chi-squared tests were used for genetic analysis.In patients with CNV-GA, GA progressed slowly and often preceded CNV. CNV presented as subretinal haemorrhage or fluid, with a sudden drop in visual acuity (VA). Comparing combined CNV-GA to GA and CNV only, patients with both had a higher frequency of at-risk alleles at both SNPs within the HTRA1 gene-rs10490924 (52.5%), rs11200638 (52.6%). Statistical significance was not achieved. CNV-GA patients had no protective alleles at SNP rs9332739 (C2), compared with GA (27%) and CNV only (10%).There is a paucity of reports describing simultaneous CNV-GA. Clinical and genetic results may support the fact that GA and CNV fit on an age-related macular degeneration (AMD)-disease continuum and may clarify the disease processes in AMD.

SUBMITTER: Grob S

PROVIDER: S-EPMC3420042 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Genetic analysis of simultaneous geographic atrophy and choroidal neovascularization.

Grob S S Luo J J Hughes G G Lee C C Zhou X X Lee J J Du H H Ferreyra H H Freeman W R WR Kozak I I Zhang K K

Eye (London, England) 20120615 8

<h4>Aim</h4>To investigate clinical presentation and genotypes in patients with simultaneous geographic atrophy (GA) and choroidal neovascularization (CNV) and to compare with patients with GA or CNV only.<h4>Patients and methods</h4>Twenty patients with combined CNV-GA and 154 CNV only and 154 GA only were chosen based on clinical exam and imaging. Six single-nucleotide polymorphisms (SNPs)-rs2274700 and rs1061170 (complement factor H), rs10490924 and rs11200638 (HTRA1/LOC387715), rs2230199 (C3 ...[more]

PMID: 22699975

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Project description:PurposeThe accuracy of predicting conversion from early-stage age-related macular degeneration (AMD) to the advanced stages of choroidal neovascularization (CNV) or geographic atrophy (GA) was evaluated to determine whether inclusion of clinically relevant genetic markers improved accuracy beyond prediction using phenotypic risk factors alone.DesignCohort study.ParticipantsWhite, non-Hispanic subjects participating in the Age-Related Eye Disease Study (AREDS) sponsored by the National Eye Institute consented to provide a genetic specimen. Of 2415 DNA specimens available, 940 were from disease-free subjects and 1475 were from subjects with early or intermediate AMD.MethodsDNA specimens from study subjects were genotyped for 14 single nucleotide polymorphisms (SNPs) in genes shown previously to associate with CNV: ARMS2, CFH, C3, C2, FB, CFHR4, CFHR5, and F13B. Clinical demographics and established disease associations, including age, sex, smoking status, body mass index (BMI), AREDS treatment category, and educational level, were evaluated. Four multivariate logistic models (phenotype; genotype; phenotype + genotype; and phenotype + genotype + demographic + environmental factors) were tested using 2 end points (CNV, GA). Models were fitted using Cox proportional hazards regression to use time-to-disease onset data.Main outcome measuresBrier score (measure of accuracy) was used to identify the model with the lowest prediction error in the training set. The most accurate model was subjected to independent statistical validation, and final model performance was described using area under the receiver operator curve (AUC) or C-statistic.ResultsThe CNV prediction models that combined genotype with phenotype with or without age and smoking revealed superior performance (C-statistic = 0.96) compared with the phenotype model based on the simplified severity scale and the presence of CNV in the nonstudy eye (C-statistic = 0.89; P<0.01). For GA, the model that combined genotype with phenotype demonstrated the highest performance (AUC = 0.94). Smoking status and ARMS2 genotype had less of an impact on the prediction of GA compared with CNV.ConclusionsInclusion of genotype assessment improves CNV prediction beyond that achievable with phenotype alone and may improve patient management. Separate assessments should be used to predict progression to CNV and GA because genetic markers and smoking status do not equally predict both end points.Financial disclosure(s)Proprietary or commercial disclosure may be found after the references.

Dataset Information

Genetic analysis of simultaneous geographic atrophy and choroidal neovascularization.

Publications

Genetic analysis of simultaneous geographic atrophy and choroidal neovascularization.

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