Research Article

Effect of ARMS2 gene polymorphism on intravitreal ranibizumab treatment for neovascular age-related macular degeneration.

Published: December 31, 1969
Genet. Mol. Res. 15(4): gmr15049164 DOI: https://doi.org/10.4238/gmr15049164
Cite this Article:
(2016). Effect of ARMS2 gene polymorphism on intravitreal ranibizumab treatment for neovascular age-related macular degeneration.. Genet. Mol. Res. 15(4): gmr15049164. https://doi.org/10.4238/gmr15049164
335 views

Abstract

Age-related macular degeneration (AMD) is a leading cause of blindness in developed countries. The ARMS2 gene has been found to be associated with AMD. Currently, intravitreal ranibizumab (IVR) treatment is one of the widely used treatments for neovascular AMD. The aim of this study was to investigate the association between the genotype of ARMS2 rs10490924 polymorphism and IVR treatment responsiveness in patients with neovascular AMD. The study included 39 patients with advanced neovascular AMD (patient group) and 250 healthy individuals with exome sequencing data (control group). The patient group was divided into three subgroups: GG (N = 10), TG (N = 14), and TT (N = 15). Before IVR treatment, all patients had intraretinal or subretinal fluid or both. They received three monthly IVR-injection treatments. One month after the third injection, the patients were evaluated as either "responders" or "non-responders" based on the presence or absence of intraretinal or subretinal fluid or both. The patient subgroups TG and TT had an 8.56- and 39-fold higher risk of AMD, respectively, than patient subgroup GG had. The allele frequency was 0.537 and 0.10 in the patient and control groups, respectively. Within the patient subgroup TT, there was a significant difference between the "responders" and "non-responders" (P = 0.025). In conclusion, in neovascular AMD patients undergoing IVR treatment, TT genotype tended to be a better predictor of good short-term treatment response, compared to the GG and TG genotypes. Further studies using confirmed genetic biomarkers for individualized optimal treatments are required.