Cigarette Smoking Strongly Modifies the Association of LOC387715 and Age-Related Macular Degeneration

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We used iterative association mapping to identify a susceptibility gene for age-related macular degeneration (AMD) on chromosome 10q26, which is one of the most consistently implicated linkage regions for this disorder. We employed linkage analysis methods, followed by family-based and case-control association analyses, using two independent data sets. To identify statistically the most likely AMD-susceptibility allele, we used the Genotype-IBD Sharing Test (GIST) and conditional haplotype analysis. To incorporate the two most important known AMD risk factors—smoking and the Y402H variant of the complement factor H gene (CFH)—we used logistic regression modeling to test for gene-gene and gene-environment interactions in the case-control data set and used the ordered-subset analysis to account for genetic linkage heterogeneity in the family-based data set. Our results strongly implicate a coding change (Ala69Ser) in the LOC387715 gene as the second major identified AMD-susceptibility allele, confirming earlier suggestions. This variant's effect on AMD is statistically independent of CFH and is of similar magnitude to the effect of Y402H. The overall effect is driven primarily by a strong association in smokers, since we observed significant evidence for a statistical interaction between the LOC387715 variant and a history of cigarette smoking. This gene-environment interaction is supported by statistically independent family-based and case-control analysis methods. We estimate that CFH, LOC387715, and cigarette smoking together explain 61% of the population-attributable risk (PAR) of AMD. The adjusted PAR percentage estimates are 20% for smoking, 36% for LOC387715, and 43% for CFH. We demonstrate, for the first time, that a genetic susceptibility coupled with a modifiable lifestyle factor such as cigarette smoking confers a significantly higher risk of AMD than either factor alone.

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The novel SNPs discovered in this study were submitted to the National Center for Biotechnology Information's SNP database (dbSNP) and will have “rs” numbers when dbSNP build 126 is released.

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These two authors contributed equally to this work.