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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Arch Ophthalmol. Author manuscript; available in PMC 2012 April 14.
Published in final edited form as:
PMCID: PMC3326353
NIHMSID: NIHMS368228

Population Differences in Genetic Risk for Age-related Macular Degeneration and Implications for Genetic Testing

To the Editor:

The personal genetics revolution has promised patients an accounting of their individual risk of common, complex diseases based on their DNA sequence. Though under increased scrutiny from the Food and Drug Administration, several direct-to-consumer (DTC) genetic testing companies offer such services, and conflicting results for the same disease in the same individual are commonly reported1. Even for an unusual case like age-related macular degeneration (AMD) for which a small number of loci with strong effects has consistently replicated across studies, it is extremely difficult to predict who will or will not develop disease2. Furthermore, most genetic association studies have been conducted in European Americans, and because the frequency of genetic polymorphisms varies across race-ethnicities, the predictive value of any genetic algorithm developed in one population may not translate to another. We have seen an extreme example of this for the ARMS2 AMD susceptibility locus.

The non-synonymous coding variant A69S within ARMS2 is one of the strongest genetic risk factors for AMD (odds ratios (OR) ~2.2 in heterozygotes, ~7.1 in homozygotes3 in European Americans). This variant (or others in strong linkage disequilibrium with it) has been used in predictive algorithms published in the scientific literature2, 4, marketed by DTC companies, and in the Macula Risk™ test available by physician order.

Methods

As part of the Population Architecture using Genomics and Epidemiology (PAGE) Study, we characterized ARMS2 A69S in the National Health and Nutrition Examination Surveys (NHANES), a cross-sectional survey of Americans representing non-Hispanic whites (W), non-Hispanic blacks (B), and Mexican-Americans (MA). AMD was assessed according to the Wisconsin Age-related Maculopathy Grading System5 of fundus photographs of one randomly selected eye in participants ages 60 and older in NHANES III. Both early AMD cases (large, soft drusen, pigmentary abnormalities, degeneration of the retinal pigment epithelium) and advanced AMD cases (geographic atrophy, choroidal neovascularization) were included6.

Results

The T allele of the ARMS2 variant, which changes the amino acid residue from alanine to serine, was in Hardy-Weinberg equilibrium in all three race-ethnicities and of similar frequency across groups (~0.22–0.25). As expected, the T allele was associated with AMD in all groups in models adjusted for age, sex, smoking status, and CFH Y402H genotype (Table 1, p=0.001 W, p=0.032 MA, p=0.052 B). However, the direction of the effect was reversed in blacks (OR=0.43) compared to whites (OR=2.10) and Mexican-Americans (OR=2.45). In contrast to whites and Mexican-Americans, the T allele frequency was ~13% lower in black cases compared to black controls.

Table 1
Association of ARMS2 A69S with AMD in 3 Race-ethnicities

Comment

There are several possible explanations. ARMS2 A69S may not be a “functional” variant, and though it tags a true risk allele in whites and Mexican-Americans, it is not highly correlated with this unknown functional variant(s) in blacks. Alternatively, ARMS2 A69S may affect disease risk differently in different race-ethnicities due to interactions with other genetic or environmental risk factors that vary between the populations. Lastly, other variants in the region, such as the complex insertion/deletion in the untranslated region of ARMS2, the nonsense R38X variant, or a promoter polymorphism in the adjacent HTRA1 gene, may also affect susceptibility.

Regardless of the reason, if this inverse association in blacks is confirmed, genetic tests that naively incorporate ARMS2 A69S without considering ancestry will consistently give incorrect results to non-Hispanic blacks. Falsely inflated risk estimates may lead to unnecessary follow-up care, increasing both cost and anxiety for these patients, while falsely decreased estimates may decrease vigilance in monitoring eye health. Furthermore, the relationship between AMD and this variant in other ethnic groups, and thus the possibility for systemic errors in other groups, remains largely unexplored.

As our results highlight, predictive genetic testing for complex diseases faces many challenges, and until we fully understand how a particular genetic variant acts on disease susceptibility, great care must be taken when translating genetic tests from one race-ethnicity to another.

Acknowledgments

Funded by U01HG004798 to Dana Crawford from the National Institutes of Health

References

1. Ng PC, Murray SS, Levy S, Venter JC. An agenda for personalized medicine. Nature. 2009;461:724–726. [PubMed]
2. Jakobsdottir J, Gorin MB, Conley YP, Ferrell RE, Weeks DE. Interpretation of genetic association studies: markers with replicated highly significant odds ratios may be poor classifiers. PLoS. Genet. 2009;5:e1000337. [PMC free article] [PubMed]
3. Schaumberg DA, Hankinson SE, Guo Q, Rimm E, Hunter DJ. A prospective study of 2 major age-related macular degeneration susceptibility alleles and interactions with modifiable risk factors. Arch. Ophthalmol. 2007;125:55–62. [PubMed]
4. Seddon JM, et al. Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables. Invest Ophthalmol. Vis. Sci. 2009;50:2044–2053. [PubMed]
5. Klein R, et al. The Wisconsin age-related maculopathy grading system. Ophthalmology. 1991;98:1128–1134. [PubMed]
6. Centers for Disease Control and Prevention. Plan and Operation of the Third National Health and Nutrition Examination Survey, 1988–94. Bethesda, MD: 2004.