June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
SNPs Associated with Complement Factor I Do Not Predict 4-month Lesion Growth Rate in Geographic Atrophy
Author Affiliations & Notes
  • John I Wurzelmann
    GlaxoSmithKline, Research Triangle Park, NC
  • Francisco J Lopez
    GlaxoSmithKline, Research Triangle Park, NC
  • Mike Fries
    GlaxoSmithKline, Research Triangle Park, NC
  • Shawn Patrick Shearn
    GlaxoSmithKline, Research Triangle Park, NC
  • Michael R Schwartz
    GlaxoSmithKline, Research Triangle Park, NC
  • Astrid Yeo
    GlaxoSmithKline, Research Triangle Park, NC
  • Lingkang Huang
    GlaxoSmithKline, Research Triangle Park, NC
  • Amitha Domalpally
    University of Wisconsin, Madison, WI
  • Ronald P Danis
    University of Wisconsin, Madison, WI
  • Rabia Ozden
    GlaxoSmithKline, Research Triangle Park, NC
  • Footnotes
    Commercial Relationships John Wurzelmann, GSK (E); Francisco Lopez, GSK (E); Mike Fries, GSK (E); Shawn Shearn, GSK (E); Michael Schwartz, GSK (E); Astrid Yeo, GSK (E); Lingkang Huang, GSK (E); Amitha Domalpally, GSK (C); Ronald Danis, GSK (C); Rabia Ozden, GSK (E)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 2850. doi:
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    • Get Citation

      John I Wurzelmann, Francisco J Lopez, Mike Fries, Shawn Patrick Shearn, Michael R Schwartz, Astrid Yeo, Lingkang Huang, Amitha Domalpally, Ronald P Danis, Rabia Ozden, ; SNPs Associated with Complement Factor I Do Not Predict 4-month Lesion Growth Rate in Geographic Atrophy. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):2850.

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

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Abstract
 
Purpose
 

BAM114341 is a GSK-sponsored, randomized, double masked, placebo-controlled phase II study to investigate the safety and efficacy of a monoclonal antibody directed against β-amyloid in patients with Geographic Atrophy (GA). Understanding determinants of GA growth rates will help patients, clinicians and researchers by informing prognosis, treatment options and future study designs. The MAHALO study reported that a subgroup carrying the risk allele for SNP rs17440077 near the Complement Factor I (CFI) locus was associated with rapid growth of GA . We sought to evaluate the effect of genetic variants near the CFI locus on GA growth rate (GR).

 
Methods
 

BAM114341 includes a 4 month observation period prior to randomization. Baseline GRs were measured by color fundus photography (CP) and fundus autofluorescence (FAF). These rates are to be used for later comparison with post-intervention rates. Subjects were required to have GA of total area 1.9-17 mm2. Blood for genetic analysis was drawn at study entry. Genetic variants rs4698775 and rs17440077 near CFI were genotyped using TaqMan® Assays. Predictors of GR were identified by mixed models repeated measures regression which included baseline lesion size, period of observation, genotype and interaction terms as covariates. Models considering GA measured by CP and FAF were considered separately.

 
Results
 

191 subjects completed the 4 month observation period. The average age of participants was 77.2 years (SD 8.6), and average baseline lesion size by CP was 7.7 mm2 (SD 4.6). Average GR at baseline (~ 4 months after screening) was 2.16 mm2/year. Genetic data were available for 170 subjects. All models contained terms for baseline lesion size and time of observation and these were consistently significant predictors of GR. In no model was either SNP a statistically significant predictor of GR. This was true for both CP and FAF based models.

 
Conclusions
 

SNPs associated with the CFI locus did not predict GR during a 4 month observation period. The MAHALO association between carriage of the rs17440077 risk allele and rapid GA growth was not observed in this study. The different results from the two studies may be attributed to differences in methodology, in the populations under study or due to the short observation period of the current study. Repeat analyses as the study progresses may support a relationship as statistical power increases.

 
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