Dataset Information

Risk Prediction for Progression of Macular Degeneration: 10 Common and Rare Genetic Variants, Demographic, Environmental, and Macular Covariates.

ABSTRACT: To determine the association between genetic variants and transition to advanced age-related macular degeneration (AMD), and to develop a predictive model and online application to assist in clinical decision making.Among 2951 subjects in the Age-Related Eye Disease Study, 834 progressed from no AMD, early AMD, or intermediate AMD to advanced disease. Survival analysis was used to assess which genetic, demographic, environmental, and macular covariates were independently associated with progression. Attributable risk, area under the curve statistics (AUCs), and reclassification odds ratios (ORs) were calculated. Split-sample validation was performed. An online risk calculator was developed and is available in the public domain at www.seddonamdriskscore.org.Ten genetic loci were independently associated with progression, including newly identified rare variant C3 K155Q (hazard ratio: 1.7, 95% confidence interval: 1.2-2.5, P = 0.002), three variants in CFH, and six variants in ARMS2/HTRA1, CFB, C3, C2, COL8A1, and RAD51B. Attributable risk calculations revealed that 80% of incident AMD is attributable to genetic factors, adjusting for demographic covariates and baseline macular phenotypes. In a model including 10 genetic loci, age, sex, education, body mass index, smoking, and baseline AMD status, the AUC for progression to advanced AMD over 10 years was 0.911. Split-sample validation showed a similar AUC (0.907). Reclassification analyses indicated that subjects were categorized into a more accurate risk category if genetic information was included (OR 3.2, P < 0.0001).Rare variant C3 K155Q was independently associated with AMD progression. The comprehensive model may be useful for identifying and monitoring high-risk patients, selecting appropriate therapies, and designing clinical trials.

SUBMITTER: Seddon JM

PROVIDER: S-EPMC4405097 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Risk Prediction for Progression of Macular Degeneration: 10 Common and Rare Genetic Variants, Demographic, Environmental, and Macular Covariates.

Seddon Johanna M JM Silver Rachel E RE Kwong Manlik M Rosner Bernard B

Investigative ophthalmology & visual science 20150401 4

<h4>Purpose</h4>To determine the association between genetic variants and transition to advanced age-related macular degeneration (AMD), and to develop a predictive model and online application to assist in clinical decision making.<h4>Methods</h4>Among 2951 subjects in the Age-Related Eye Disease Study, 834 progressed from no AMD, early AMD, or intermediate AMD to advanced disease. Survival analysis was used to assess which genetic, demographic, environmental, and macular covariates were indepe ...[more]

PMID: 25655794

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Project description:PurposeTo expand our predictive models for progression to advanced stages of age-related macular degeneration (AMD) based on demographic, environmental, genetic, and ocular factors, using longer follow-up, time varying analyses, calculation of absolute risks, adjustment for competing risks, and detailed baseline AMD and drusen status.DesignProspective, longitudinal study.ParticipantsWe included 2937 individuals in the Age-Related Eye Disease Study, of which 819 subjects progressed to advanced AMD during 12 years of follow-up.MethodsCox proportional hazards regression analyses were performed to calculate hazard ratios for progression. Covariates included demographic and environmental factors, 6 variants in 5 genes, baseline macular drusen size, and presence and type of advanced AMD in 1 eye at baseline. To assess the ability of risk scores based on all covariates to discriminate between progressors and nonprogressors, an algorithm was developed and the area under the receiver operating characteristic curve (AUC) was calculated. To validate the overall model, the total sample was randomly subdivided into derivation and test samples. Another model was built based on the derivation sample and assessed for calibration and discrimination in the test sample. Sample sizes needed for testing new treatments in clinical trials were estimated based on models with and without genetic variables.Main outcome measuresProgression to advanced AMD, including geographic atrophy and neovascular disease.ResultsIn multivariate models, age, smoking, body mass index, single nucleotide polymorphisms in the CFH, ARMS2/HTRA1, C3, C2, and CFB genes, as well as presence of advanced AMD in 1 eye and drusen size in both eyes were all independently associated with progression. The AUC for progression at 10 years in the model with genetic factors, drusen size, and environmental covariates was 0.915 in the total sample. In the test sample, based on a model estimated from the derivation sample, the AUC was 0.908. The sample sizes needed for clinical trials were estimated to be lower when genetic susceptibility was considered.ConclusionsFactors reflective of nature and nurture were incorporated into an expanded algorithm for risk prediction, which performed very well in both derivation and test samples. Risk scores and predicted progression rates will be useful for AMD surveillance and for designing clinical trials.Financial disclosure(s)Proprietary or commercial disclosure may be found after the references.

Project description:PurposeThe joint effects of genetic, ocular, and environmental variables were evaluated and predictive models for prevalence and incidence of AMD were assessed.MethodsParticipants in the multicenter Age-Related Eye Disease Study (AREDS) were included in a prospective evaluation of 1446 individuals, of which 279 progressed to advanced AMD (geographic atrophy or neovascular disease) and 1167 did not progress during 6.3 years of follow-up. For prevalent AMD, 509 advanced cases were compared with 222 controls. Covariates for the incidence analysis included age, sex, education, smoking, body mass index (BMI), baseline AMD grade, and the AREDS vitamin-mineral treatment assignment. DNA specimens were evaluated for six variants in five genes related to AMD. Unconditional logistic regression analyses were performed for prevalent and incident advanced AMD. An algorithm was developed and receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from nonprogressors.ResultsAll genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS treatment. Multivariate odds ratios (ORs) were 3.5 (95% confidence interval [CI], 1.7-7.1) for CFH Y402H; 3.7 (95% CI, 1.6-8.4) for CFH rs1410996; 25.4 (95% CI, 8.6-75.1) for LOC387715 A69S (ARMS2); 0.3 (95% CI, 0.1-0.7) for C2 E318D; 0.3 (95% CI, 0.1-0.5) for CFB; and 3.6 (95% CI, 1.4-9.4) for C3 R102G, comparing the homozygous risk/protective genotypes to the referent genotypes. For incident AMD, all these variants except CFB were significantly related to progression to advanced AMD, after controlling for baseline AMD grade and other factors, with ORs from 1.8 to 4.0 for presence of two risk alleles and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment, after controlling for all genotypes. Smoking was independently related to AMD, with a multiplicative joint effect with genotype on AMD risk. The C statistic for the full model with all variables was 0.831 for progression to advanced AMD.ConclusionsFactors reflective of nature and nurture are independently related to prevalence and incidence of advanced AMD, with excellent predictive power.

Project description:ImportanceRisk score models predicting the progression of age-related macular degeneration (AMD) to its advanced forms may be useful for targeting high-risk individuals for lifestyle changes that reduce risk for AMD progression, helping with differential diagnosis of AMD and its subtypes, identifying high-risk subjects for participation in clinical trials, and selecting appropriate therapies.ObjectiveTo develop and validate a predictive model for progression to advanced stages of AMD in 2 independent cohorts. DESIGN Participants in a validation cohort and an independent derivation population were classified into 5 stages of AMD based on ocular examination and fundus photographs at baseline. Progression was defined as either eye progressing from stage 1, 2, or 3 to either stage 4 or stage 5 at any follow-up visit to the end of the study. Cox proportional hazards models were used for progression analyses. Covariates included demographic and environmental factors, 6 variants in 5 genes, and baseline AMD grades in both eyes. The algorithm developed with the derivation sample was assessed for calibration and discrimination in the validation data set.SettingClinic populations and referrals.ParticipantsThe derivation population comprised 2914 subjects with 809 progressors. The independent validation cohort comprised 980 individuals with no, early, or intermediate AMD in at least one eye at baseline, of whom 294 progressed to advanced stages of geographic atrophy or neovascular disease.Main outcome measureProgression to advanced AMD. RESULTS For the model with all nongenetic and genetic factors, the respective C statistics for progression to advanced AMD in the derivation and validation samples were 0.858 and 0.750 at 5 years and 0.884 and 0.809 at 10 years, and models also discriminated risk for progression to geographic atrophy and neovascular disease separately. For unilateral or bilateral intermediate AMD, 5-year cumulative incidence rates of progression to advanced AMD were 10% with the low-risk score and 50% with the high-risk score; for unilateral advanced disease, the progression rates were 22% and 80% for the fellow eye.Conclusions and relevanceThe risk prediction model was validated in an independent study of progression from no, early, or intermediate stages to advanced subtypes of AMD and will be useful for research, clinical trials, and personalized medicine.

Dataset Information

Risk Prediction for Progression of Macular Degeneration: 10 Common and Rare Genetic Variants, Demographic, Environmental, and Macular Covariates.

Publications

Risk Prediction for Progression of Macular Degeneration: 10 Common and Rare Genetic Variants, Demographic, Environmental, and Macular Covariates.

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