June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Risk prediction for progression of macular degeneration including 10 common and rare genetic variants
Author Affiliations & Notes
  • Johanna M Seddon
    Ophthalmic Epidemiology and Genetics Service, Tufts Medical Center, Boston, MA
    Department of Ophthalmology, Tufts University School of Medicine, Boston, MA
  • Rachel E Silver
    Ophthalmic Epidemiology and Genetics Service, Tufts Medical Center, Boston, MA
  • Manlik Kwong
    Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA
  • Bernard Rosner
    Channing Laboratory, Brigham and Women’s Hospital and Harvard School of Public Health, Boston, MA
  • Footnotes
    Commercial Relationships Johanna Seddon, Tufts Medical Center (P); Rachel Silver, None; Manlik Kwong, None; Bernard Rosner, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 796. doi:
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      Johanna M Seddon, Rachel E Silver, Manlik Kwong, Bernard Rosner; Risk prediction for progression of macular degeneration including 10 common and rare genetic variants. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):796.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

To determine the association between new rare genetic variants and transition to advanced age-related macular degeneration (AMD), and to develop a predictive model as well as an online clinical application to assist in research and collaborative disease management.

 
Methods
 

Among 2951 subjects participating in the Age-Related Eye Disease Study, 834 progressed from no AMD, early, or intermediate AMD to advanced AMD, classified as geographic atrophy or neovascular disease, in either eye. Survival analysis was used to assess which genetic loci were independently associated with progression after adjusting for age, sex, education, smoking, baseline macular phenotype, body mass index, and known AMD genes. Attributable risk (AR) and area under the curve statistics (AUCs) were calculated. Reclassification methodology was used to compare models with and without genes.

 
Results
 

Rare variant K155Q in the C3 gene was newly identified as an independent risk factor for AMD progression (hazard ratio: 1.7, 95% confidence interval: 1.2-2.5, p=0.002). Other genetic predictors for transition to advanced stages included 3 common and rare variants in CFH, and 6 common variants in ARMS2/HTRA1, CFB, C3, C2, COL8A1 and RAD51B. AR calculations revealed that 80% of incident AMD is attributable to genetic factors after adjusting for baseline macular phenotypes. The AUC for progression to advanced AMD over 10 years was 90.8%. Reclassification analyses indicated that subjects will be categorized into a more accurate risk category if genetic information is added to a model without genes (odds ratio: 3.2, p <0.0001). This 10 genetic loci model can differentiate between low, medium, and high risk of progression to advanced AMD, even among individuals with the same macular status at baseline.

 
Conclusions
 

Genotype information enhanced the predictive capacity of risk models, as shown by AR, AUC and reclassification analyses. An online risk calculator was developed for this 10 genetic loci model incorporating demographic, behavioral, and macular characteristics. Newly discovered genes can be assessed for their independent effects on progression and added to the model to further enhance prediction. The online risk calculator (available at www.seddonamdriskscore.org) can be used for initial screening, collaborative disease management, and clinical research.

 
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