September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Influence of Risk Alleles for Age-Related Macular Degeneration on Recessive Stargardt Disease Phenotypes
Author Affiliations & Notes
  • Robert Sisk
    Ophthalmology, University of Cincinnati, Cincinnati, Ohio, United States
    Ophthalmology, Cincinnati Children's Hospital, Cincinnati, Ohio, United States
  • Robert B Hufnagel
    Otolaryngology, University of Maryland, Baltimore, Maryland, United States
  • Brent Zanke
    Arctic Dx, Bonita Springs, Florida, United States
  • Zubair Ahmed
    Otolaryngology, University of Maryland, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Robert Sisk, None; Robert Hufnagel, None; Brent Zanke, None; Zubair Ahmed, Arctic Dx (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 3164. doi:
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    • Get Citation

      Robert Sisk, Robert B Hufnagel, Brent Zanke, Zubair Ahmed; Influence of Risk Alleles for Age-Related Macular Degeneration on Recessive Stargardt Disease Phenotypes. Invest. Ophthalmol. Vis. Sci. 2016;57(12):3164.

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

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Purpose : Phenotypic variability, familial disconcordance, and inconsistency in reports describing pathogenicity of specific alleles all suggest autosomal recessive Stargardt disease (STGD1) phenotypes are inadequately explained by ABCA4 genotypes alone. We hypothesized that genes associated with age-related macular degeneration (AMD) may influence the age of presentation and severity of macular degeneration in STGD1.

Methods : IRB-approved, prospective genetic evaluation using Macula Risk™ PGx platform and corresponding retrospective records review of patients with genetically confirmed STGD1 (one or more ABCA4 mutations and typical clinical phenotype). Patients with ELOVL4, RDS, and PROM1 mutations were excluded. All patients underwent phenotypic evaluation that included funduscopy, spectral domain optical coherence tomography, fundus autofluorescence, and/or full field electroretinography (ffERG). CFH, CFI, C3, C2, CFB, LIPC, ABCA1, CETP, Col8A1, APOE, TIMP3, and ARMS2 alleles were graded per AMD risk classifications and patients were assigned a genetic risk subscore for AMD risk. Results from STGD1 patients were then compared with 379 age-matched Caucasian controls without STGD1 from the 1000 Genomes Project and with advanced dry AMD patients from the AREDS 2 trial (courtesy of ArcticDx®).

Results : 23 patients with STGD1 (5 males) presented at a mean age of 18 years (range 7 to 47) with mean VA of 20/83 (range 20/20 to 20/400) and were followed a median of 4 years. At presentation, 16 (70%) had visible lipofuscin flecks, 15 (65%) had atrophy, and 3 (13%) had severe reduction in ffERG waveforms. Mean AMD genetic risk subscore from the Macula Risk PGx® platform was elevated at 60% compared to advanced AMD patients at 56%, but this was not statistically significant. There was no observed association between age at presentation, severity of macular degeneration, or Gass grouping with the AMD genetic risk subscore. No individual SNP frequency differed significantly between STGD1 patients and controls.

Conclusions : STGD1 may exhibit significant phenotypic variability, but preliminary data suggest this is not strongly influenced by pathogenic AMD risk alleles. However, small sample size may have limited determination of these associations. A collaborative project, currently in progress, will add power and clarify which trends may become significant.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.


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