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Table. Association of ARMS2 A69S With Age-Related Macular Degeneration in 3 Race-Ethnicities
Table. Association of ARMS2 A69S With Age-Related Macular Degeneration in 3 Race-Ethnicities
1.
Ng PC, Murray SS, Levy S, Venter JC. An agenda for personalized medicine.  Nature. 2009;461(7265):724-726PubMedArticle
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(2):e1000337PubMedArticle
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(1):55-62PubMedArticle
4.
Seddon JM, Reynolds R, Maller J, Fagerness JA, Daly MJ, Rosner B. 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(5):2044-2053PubMedArticle
5.
Klein R, Davis MD, Magli YL, Segal P, Klein BE, Hubbard L. The Wisconsin age-related maculopathy grading system.  Ophthalmology. 1991;98(7):1128-1134PubMed
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Centers for Disease Control and Prevention.  Plan and Operation of the Third National Health and Nutrition Examination Survey, 1988-94. Atlanta, GA: Centers for Disease Control and Prevention; 2004
Research Letters
Jan 2012

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

Author Affiliations

Author Affiliations: Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee. Dr Spencer is now with the Department of Biology, Heidelberg University, Tiffin, Ohio.

Arch Ophthalmol. 2012;130(1):116-117. doi:10.1001/archopthalmol.2011.1370

The personal genetics revolution has promised patients an account of their individual risks of common, complex diseases based on their DNA sequence. Although under increased scrutiny from the US Food and Drug Administration, several direct-to-consumer genetic testing companies offer such services, and conflicting results for the same disease in the same individual are commonly reported.1 Even for an unusual case like age-related macular degeneration (AMD) for which a small number of loci with strong effects has consistently been replicated across studies, it is extremely difficult to predict who will or will not develop disease.2 Furthermore, most genetic association studies have been conducted in European American individuals, 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 (GenBank BC066349) AMD susceptibility locus.

The nonsynonymous coding variant A69S within ARMS2 is one of the strongest genetic risk factors for AMD (in European American individuals3: odds ratio [OR] = 2.2 in heterozygotes; OR = 7.1 in homozygotes). This variant (or others in strong linkage disequilibrium with it) has been used in predictive algorithms published in the scientific literature,2,4 marketed by direct-to-consumer companies, and used in the Macula Risk test available by physician order.

Methods

As part of the Population Architecture Using Genomics and Epidemiology Study, we characterized ARMS2 A69S in the National Health and Nutrition Examination Survey, a cross-sectional survey of non-Hispanic white individuals, non-Hispanic black individuals, and Mexican American individuals. We assessed AMD according to the Wisconsin Age-Related Maculopathy Grading System5 using fundus photographs of 1 randomly selected eye in participants aged 60 years and older in the Third National Health and Nutrition Examination Survey. Both early AMD cases (large, soft drusen, pigmentary abnormalities, degeneration of the retinal pigment epithelium) and advanced AMD cases (geographic atrophy, choroidal neovascularization) were included.6

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 3 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 (P = .001 in non-Hispanic white individuals; P = .03 in Mexican American individuals; P = .05 in non-Hispanic black individuals) (Table). However, the direction of the effect was reversed in non-Hispanic black individuals (OR = 0.43) compared with non-Hispanic white individuals (OR = 2.10) and Mexican American individuals (OR = 2.45). In contrast to non-Hispanic white and Mexican American individuals, the T-allele frequency was approximately 13% lower in non-Hispanic black patients compared with non-Hispanic black control subjects.

Comment

There are several possible explanations for our findings. The ARMS2 A69S variant may not be a functional variant, and although it tags a true risk allele in non-Hispanic white and Mexican American individuals, it is not highly correlated with the unknown functional variant(s) in non-Hispanic black individuals. Alternatively, ARMS2 A69S may affect disease risk differently in different race-ethnicities owing 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 non-Hispanic black individuals is confirmed, genetic tests that naively incorporate ARMS2 A69S without considering ancestry will consistently give incorrect results to non-Hispanic black individuals. 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. 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.

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Article Information

Correspondence: Dr Spencer, Department of Biology, Heidelberg University, 310 E Market St, Tiffin, OH 44883 (kspencer@heidelberg.edu).

Financial Disclosure: Drs Spencer and Haines are listed as inventors on patent PCT/US09/034882, “Methods and Compositions for Diagnosis of Age-Related Macular Degeneration,” which covers rights to a particular variant that is used in the calculation of risk in the Macula Risk test and is licensed by ArcticDx Inc, the makers of Macula Risk.

Funding/Support: This work was supported by grant U01HG004798 from the National Institutes of Health (Dr Crawford).

Role of the Sponsor: The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.

References
1.
Ng PC, Murray SS, Levy S, Venter JC. An agenda for personalized medicine.  Nature. 2009;461(7265):724-726PubMedArticle
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(2):e1000337PubMedArticle
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(1):55-62PubMedArticle
4.
Seddon JM, Reynolds R, Maller J, Fagerness JA, Daly MJ, Rosner B. 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(5):2044-2053PubMedArticle
5.
Klein R, Davis MD, Magli YL, Segal P, Klein BE, Hubbard L. The Wisconsin age-related maculopathy grading system.  Ophthalmology. 1991;98(7):1128-1134PubMed
6.
Centers for Disease Control and Prevention.  Plan and Operation of the Third National Health and Nutrition Examination Survey, 1988-94. Atlanta, GA: Centers for Disease Control and Prevention; 2004
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