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Variants in the 10q26 Gene Cluster (LOC387715 and HTRA1) Exhibit Enhanced Risk of Age-Related Macular Degeneration along with CFH in Indian Patients

¹From the Kallam Anji Reddy Molecular Genetics Laboratory and the ³Smt. Kannuri Santhamma Retina Vitreous Services, L. V. Prasad Eye Institute, Hyderabad, India.

PURPOSE. Single nucleotide polymorphisms (SNPs) in the LOC387715 (rs10490924), HTRA1 (rs11200638), and CFH (rs1061170) genes have been implicated in age-related macular degeneration (AMD). The present study was undertaken to determine the involvement of the LOC387715 and HTRA1 in an AMD cohort from India.

METHODS. The coding region of LOC387715 (exon 1) and the promoter of HTRA1 were screened by resequencing in AMD cases and normal controls. Odds ratios were calculated to assess the risk of individual genotypes. Linkage disequilibrium (LD) and haplotype frequencies were estimated with Haploview software. Population attributable risk (PAR %) for the associated SNPs and their combined effects were calculated.

RESULTS. Resequencing revealed seven different SNPs in these genes, of which significant associations were noted with the risk alleles of rs10490924 (T allele; P = 5.34 x 10^–12) in LOC387715, and rs11200638 (A allele; P = 4.32 x 10^–12) and rs2672598 (C allele; P = 3.39 x 10^–11) in HTRA1 among the cases. Correspondingly, the homozygous risk genotypes TT, AA, and CC in these SNPs exhibited higher disease odds and PAR %. rs10490924 and rs11200638 were in tight LD (D', 0.90; 95% CI, 0.84–0.93). G-C-T-A-C was the risk haplotype (P = 8.04 x 10^–15), whereas the G-C-G-G-T haplotype was protective (P = 2.01 x 10^–4). The combined effect of the CFH (CC) and LOC387715 (TT) risk genotypes exhibited a PAR of 93.7% (OR, 73.89; 95% CI, 8.69–628.13).

CONCLUSIONS. The present data provided an independent validation of the association of LOC387715 and HTRA1 SNPs, along with their risk estimates among Indian patients with AMD. These associations underscore their significant involvement in AMD susceptibility, which may be useful for predictive testing.

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