June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Known Age-Related Macular Degeneration Risk Variants Are Not Associated with Rapid Disease Progression or Good Treatment Response
Author Affiliations & Notes
  • Monique D Courtenay
    Hussman Institute for Human Genomics, University of Miami, Miami, FL
  • William Cade
    Hussman Institute for Human Genomics, University of Miami, Miami, FL
  • Gaofeng Wang
    Hussman Institute for Human Genomics, University of Miami, Miami, FL
  • Stephen G Schwartz
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL
  • Jaclyn L Kovach
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL
  • Anita Agarwal
    Ophthalmology and Visual Sciences, Vanderbilt University, Nashville, TN
  • Milam A Brantley
    Ophthalmology and Visual Sciences, Vanderbilt University, Nashville, TN
  • William K Scott
    Hussman Institute for Human Genomics, University of Miami, Miami, FL
  • Jonathan L Haines
    Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH
  • Margaret A Pericak-Vance
    Hussman Institute for Human Genomics, University of Miami, Miami, FL
  • Footnotes
    Commercial Relationships Monique Courtenay, None; William Cade, None; Gaofeng Wang, None; Stephen Schwartz, None; Jaclyn Kovach, None; Anita Agarwal, None; Milam Brantley, None; William Scott, None; Jonathan Haines, None; Margaret Pericak-Vance, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 797. doi:https://doi.org/
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      Monique D Courtenay, William Cade, Gaofeng Wang, Stephen G Schwartz, Jaclyn L Kovach, Anita Agarwal, Milam A Brantley, William K Scott, Jonathan L Haines, Margaret A Pericak-Vance; Known Age-Related Macular Degeneration Risk Variants Are Not Associated with Rapid Disease Progression or Good Treatment Response. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):797. doi: https://doi.org/.

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

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Abstract
 
Purpose
 

AMD is the leading cause of irreversible vision loss among older adults in developed countries. Genome-wide association meta-analysis has implicated common variations in 19 genes as AMD risk factors. Given the strong genetic influence on the risk of developing AMD, and the substantial variation in progression to advanced AMD and in treatment response, we investigated whether these clinical endpoints are also influenced by the known genetic variation.

 
Methods
 

In an existing dataset, 16 of the 19 GWAS loci were used to calculate a genetic risk score (summed number of risk alleles weighted by effect sizes) for each individual as outlined in Fritsche et al., 2013. To maximize our power for discovery, we created two “clinically extreme” case/control datasets with the following characteristics: 1) Rapid clinical progression of 36 individuals with early AMD or geographic atrophy to neovascular AMD within one year vs. 31 early AMD patients who did not progress over five or more years, and 2) 20 patients with bilateral neovascular AMD who were treated with intravitreal injections of anti-angiogenic agents for one year and demonstrated bilateral good treatment response (three lines of vision gain on the Snellen vision chart, prolonged or persistent (at least 6 months) absence of subretinal fluid (SRF) and absence of intraretinal fluid (IRF) on OCT, presence of unchanged small intraretinal cysts with no recurrence of SRF) vs. 22 neovascular AMD patients who demonstrated a poor response in one or both eyes (three lines of vision loss, persistent SRF and IRF, formation of disciform scar). The genetic risk score was tested for association with rapid progression or good treatment response with logistic regression adjusting for age and sex.

 
Results
 

Risk score was not associated in either dataset in our study (progression P=0.43 and treatment P=0.63). Therefore, the genetic effects of the 19 known AMD risk loci are not associated with rapid progression or good treatment response in this small dataset, but perhaps a larger sample size would have sufficient power to demonstrate an effect.

 
Conclusions
 

Our results suggest that unknown genetic factors may still be regulating variability in progression and treatment response. Whole exome sequencing is currently underway in this dataset to test if novel rare or common variants are associated with these clinical endpoints.

 
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