• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of molvisLink to Publisher's site
Mol Vis. 2009; 15: 1819–1826.
Published online Sep 9, 2009.
PMCID: PMC2742636

SOD2 gene polymorphisms in neovascular age-related macular degeneration and polypoidal choroidal vasculopathy



A nonsynonymous coding variant in the manganese superoxide dismutase (SOD2) gene (V16A, rs4880) has been implicated in neovascular age-related macular degeneration (AMD). However, the findings have been inconsistent. Two studies in Japanese populations reported an opposite direction of association of the same allele at the V16A variant, whereas one study in a Northern Irish population found no effect of the variant on the risk of developing neovascular AMD. To address these apparently contradictory reports, we validated the association in a Japanese population.


In a Japanese population, we genotyped the V16A variant in 116 neovascular AMD patients, 140 polypoidal choroidal vasculopathy (PCV) patients, and 189 control participants. This association was also tested in a population of PCV participants to avoid variable findings across studies due to underlying sample heterogeneity and because disease phenotype was not well described in previous studies. We analyzed a tagging single nucleotide polymorphism (SNP) in addition to the V16A variant to capture all common SOD2 variations verified by the HapMap project. Genotyping was conducted using TaqMan technology. Associations were tested using single-SNP and haplotype analyses as well as a meta-analysis of the published literature. Population stratification was also evaluated in our study population.


We found no detectable association of the V16A variant or any other common SOD2 variation with either neovascular AMD or PCV, as demonstrated by both single-SNP and haplotype analyses. Population structure analyses precluded stratification artifacts in our study cohort. A meta-analysis of the association between the V16A variant and neovascular AMD also failed to detect a significant association.


We found no evidence to support the role of any common SOD2 variations including the V16A variant in the susceptibility to neovascular AMD or PCV. Our study highlights the importance and difficulty in replicating genetic association studies of complex human diseases.


Age-related macular degeneration (AMD) is a leading cause of blindness among elderly in developed nations [1]. AMD is a phenotypically heterogeneous disorder manifested at an early stage by large drusen and pigmentary abnormalities in retinal pigment epithelium (RPE). It progresses to an advanced stage by atrophy of the RPE and photoreceptors of the macula (geographic atrophy or dry AMD), or by the development of choroidal neovascularization (CNV) underneath the retina (neovascular or wet AMD) [2].

Polypoidal choroidal vasculopathy (PCV) is a hemorrhagic and exudative macular disorder that is characterized by the development of vascular networks with terminal polypoidal lesions within the inner choroid [3]. PCV is proposed to be a specific type of CNV [3,4] and much debate exists as to whether they represent different entities with distinct etiology or neovascular subsets within a common etiologic pathway [5-7]. PCV occurs much more frequently in Asians than in Caucasians, accounting for 54.7% of patients with findings suggestive of neovascular AMD in the Japanese population [8], for 24.5% in the Chinese population [9], but for only about 10% in Caucasians [3].

Numerous studies have presented evidence of a strong underlying genetic liability in AMD [10,11]. A total of four AMD risk loci have been identified with convincing statistical evidence, including the complement factor H gene (CFH) on chromosome 1q32 [12-17], the ARMS2/HTRA1 locus on 10q26 [18-23], the complement component 3 gene on 19p13 [24-28], and two neighboring genes on 6p21: complement factor B, and complement component 2 [29-32]. These four loci are associated with both types of advanced AMD: geographic atrophy and neovascular AMD [16,22,25,29].

A large number of additional candidate susceptibility genes have been studied, but findings from most studies are inconclusive because of a lack of consistent replication [10,11]. Kimura et al. [33] reported that a nonsynonymous coding variant in the manganese superoxide dismutase (SOD2) gene (V16A, rs4880) was significantly associated with neovascular AMD in a Japanese population. However, a subsequent study by Esfandiary et al. [34] on a Northern Irish population reported no effect of the V16A variant on the risk of developing neovascular AMD. A recent Japanese study by Gotoh et al. [35] was also unable to replicate the initially reported association; on the contrary, this group found a significant negative association of the same allele with neovascular AMD— I.E., this variant allele was significantly protective against neovascular AMD.

To address these apparently contradictory reports, the current study evaluated the association between the V16A variant and neovascular AMD in a Japanese population. We analyzed a tagging single nucleotide polymorphism (SNP) in addition to the V16A variant to capture all common SOD2 variations verified by the HapMap project [36]. Therefore, there was an increased coverage of this gene in our study as compared to the two previous studies in Japanese populations, which only examined the V16A variant [33,35]. We also tested for their association with PCV because the disease phenotype was not well described in previous studies [33,35]. Particularly, the initial study by the Japanese group did not consider the findings from indocyanine green (ICG) angiography in their evaluation [33], which is the only way to obtain a clear image of PCV lesions. This raises the possibility that their cohort may have included a measurable amount of PCV given its high prevalence in the Japanese population [8]. It has been suggested that attention to phenotype classification is a key aspect of genetic studies of AMD, to avoid variable findings across studies due to underlying sample heterogeneity [37]. Additionally, we performed a meta-analysis to assess the overall effect of the V16A variant on neovascular AMD across the different independent studies.


Study participants

This study was approved by the Institutional Review Board at Kobe University Graduate School of Medicine and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. All case and control participants enrolled in this study were Japanese individuals recruited from the Department of Ophthalmology at Kobe University Hospital in Kobe, Japan. The majority of participants had participated in our previous studies [38,39] in which phenotyping criteria were fully described. In brief, all our neovascular AMD and PCV patients underwent comprehensive ophthalmic examinations including ICG angiography, and were defined as having angiographically well defined lesions of CNV or PCV. The control participants, who were not related to the case participants, were defined as individuals without macular degeneration and changes such as drusen or pigment abnormalities, and thus were categorized as having clinical age-related maculopathy staging system stage 1 [40]. The demographic details of our study population are presented in Table 1.

Table 1
Characteristics of the study population.

Marker selection

To comprehensively and effectively cover common variations in the SOD2 locus, we ran the Tagger tool [41] from the HapMap project database [36] for the Japanese in Tokyo (JPT) population. The minor allele frequency (MAF) cutoff was set at 0.05; the r2 cutoff was set at 0.9; and the Tagger Pairwise mode was used. Two SNPs, the V16A variant (rs4880) and rs5746136, were selected for genotyping. On the basis of the HapMap JPT data, these two SNPs captured all seven HapMap SNPs in SOD2, with a MAF greater than 5% and a mean r2 value of 1.0. Therefore, this set of two SNPs is representative of the common genetic variations in SOD2 because it acts as a proxy marker for other untyped SNPs in this locus.

SNP genotyping

Genomic DNA was extracted from peripheral blood immediately after it was drawn using QIAamp DNA Blood Maxi Kit (Qiagen, Valencia, CA) according to the manufacturer’s instructions. Genotyping was conducted using TaqMan® SNP Genotyping Assays (Applied Biosystems, Foster City, CA) on a StepOnePlus™ Real-Time PCR system (Applied Biosystems), in accordance with the manufacturer’s instructions.

Statistical analysis

Testing for association was performed using a software package PLINK v1.00 [42]. Deviations from Hardy–Weinberg equilibrium were tested using the exact test [43] implemented in PLINK. The two SNPs reported in the present study did not show significant deviation from Hardy–Weinberg equilibrium in neovascular AMD, PCV, or control participants (all p>0.05). Single-marker association analyses were performed using the χ2-test or Fisher’s exact test under allele (1 degree of freedom, df), genotypic (2 df), dominant (1 df), and recessive (1 df) genetic models. To adjust for differences in age and sex between case and control subjects, we performed logistic regression analyses using SNPStats software [44], assuming an additive genetic model by fitting age and sex as continuous and categorical covariates, respectively. A p>0.05 was considered statistically significant. Measures of linkage disequilibrium (LD) and haplotype association statistics were calculated using Haploview software [45]. Omnibus tests of haplotype associations were performed with PLINK.

Power calculations were conducted using QUANTO version 1.2 [46]. Assuming an additive genetic model, we had 80% power to detect an association of the V16A variant with an odds ratio (OR) ≥1.79 (or ≤0.47) for the neovascular AMD sample, and ≥1.70 (or ≤0.51) for the PCV sample.

Hidden population stratification in genetic association studies can generate a spurious positive or negative association [47]. To prevent potential stratification in our study cohort, population stratification was evaluated using STRUCTURE software [48] as described in previous studies [38,39,49,50]. The following 38 polymorphic SNPs, which are not in LD with each other (r2<0.04), were used for this analysis: rs3818729 (1p13.2), rs696619 (1p21.3), rs9434 (1p36.12), rs1554286 (1q32.1), rs13388696 (2p23.1), rs1042034 (2p24.1), rs10932613 (2q35), rs7641926 (3p26.2), rs2305619 (3q25.32), rs4074 (4q13.3), rs6876885 (5p15.1), rs6459193 (6p11.2), rs3779109 (7p22.1), rs2227667 (7q22.1), rs6468284 (8p12), rs10757278 (9p21.3), rs955220 (9p24.3), rs1927911 (9q33.1), rs4838590 (10q11.22), rs12806 (10q24.2), rs2019938 (11p15.5), rs609017 (11q24.3), rs3912640 (12p13.2), rs2283299 (12p13.33), rs715948 (12q13.3), rs7328193 (13q12.11), rs1048990 (14q13.2), rs911669 (14q32.13), rs16948719 (15q22.31), rs11076720 (16q24.3), rs1051009 (17p13.2), rs1292033 (17q23.1), rs7239116 (18q11.2), rs892115 (19p13.2), rs3826945 (19p13.3), rs844906 (20p11.21), rs2825761 (21q21.1), and rs3884935 (22q13.1). The log likelihood of each analysis with a varying number of populations (K) was computed from three independent runs (20,000 burn-in and 30,000 iterations). The best estimate of K was defined by calculating posterior probabilities (Pr, K=1, 2, 3, 4, or 5) based on the log likelihood, as described by Pritchard et al. [51].

A meta-analysis was performed using R and StatsDirect software (StatsDirect, Cheshire, UK). Data from our own study and two earlier case-control studies performed by Kimura et al. [33] and Gotoh et al. [35] were used for the meta-analysis. The study by Esfandiary et al. [34] was not included in the meta-analysis, because the allele and genotype data were unavailable. A summary OR was calculated using the random-effects model of DerSimonian and Laird [52]. Heterogeneity between studies was tested using Cochran’s Q statistic [53,54] and the I2 statistic for inconsistency [53,54]. I2 is a measure of the proportion of total variation across studies due to heterogeneity beyond chance. I2 is provided by the formula I2=100% × Q − (k − 1)/Q, where Q is the Cochran’s heterogeneity statistic and k is the number of studies. The Q-test is known to have poor power if there are few studies and is typically considered statistically significant at p<0.1 [53,54]. On the other hand, I2 is unaffected by the number of studies, and it is regarded as large for values >50% [55].


We genotyped V16A (rs4880) to validate the previously reported association and this SNP was supplemented by an additional SNP rs5474613 to increase coverage of the variations in SOD2. These two SNPs captured all common SOD2 SNPs (MAF > 0.05) observed in the HapMap JPT subjects with a mean r2 of 1.0. The allele and genotype counts and results of single-SNP association analysis are given in Table 2. Neither of the two SNPs showed a significant association with either neovascular AMD or PCV in any of the genetic models (all p>0.05; Table 2). Adjustment for age and sex by logistic regression analyses under an additive model did not affect this conclusion (neovascular AMD, p=0.18 and 0.76 for rs4880 and rs5474613, respectively; PCV, p=0.25 and 0.83 for rs4880 and rs5474613, respectively).

Table 2
Allele and genotype distributions of rs4880 (V16A) and rs5746136 and the results of association tests

The two SNPs genotyped were in moderate LD with each other (D´=0.75) and haplotype association analyses were conducted using these two SNPs. No significant haplotype associations were found for either neovascular AMD (omnibus p=0.51, 3 df; Table 3) or PCV (omnibus p=0.80, 3 df; Table 3).

Table 3
Results of a haplotype-based association study

Next, population stratification was evaluated by STRUCTURE [48] using 38 unlinked genome-wide SNPs. No evidence of stratification was found in our study cohort [Pr (K=1>0.99)] indicating that population stratification did not account for the results observed in the present study.

Finally, a meta-analysis was performed to assess the association of the V16A variant with neovascular AMD across the different independent studies. Association results from our study (only neovascular AMD) and the two previous Japanese studies [33,35] were combined using the random-effects model of DerSimonian and Laird [52], and a summary OR for the model was calculated based on the allele frequency data. As shown in Figure 1, the heterogeneity test across studies (Cochran’s Q statistic) was significant for this variant (p=0.0014), and inconsistency of the genetic effects across the three studies was high (I2=84.8%). No significant association was detected for the V16A variant, with a random-effects summary OR of 0.89 (95% CI, 0.47–1.67). Allele and genotype frequencies of the V16A variant observed in the two previous Japanese studies [33,35] are shown in Table 4.

Figure 1
Meta-analysis of the V16A variant for its association with neovascular AMD. Odds ratios (ORs, black squares) and 95% confidence intervals (CIs, bars) are presented for each study. Also shown is the shaded diamond of the summary OR using the random-effects ...
Table 4
Allelic distributions of the V16A variant reported by earlier studies


To validate the previously described associations of the SOD2 V16A variant with neovascular AMD in Japanese populations [33,35], we examined this variant together with an additional SNP to increase coverage of the gene in an independent Japanese population with neovascular AMD. These two SNPs are perfect surrogates of all SOD2 SNPs identified by the HapMap project [36], and are representative of the common SOD2 variations. We also tested for an association with PCV, given the possibility that the study cohort in previous Japanese studies might have had a measurable amount of PCV [33,35]. We found no detectable association of the V16A variant or any other common SOD2 variation with either neovascular AMD or PCV by single-SNP or haplotype analysis. Population structure analyses precluded stratification artifact in our study cohort. A meta-analysis of the association between the V16A variant and neovascular AMD also failed to detect a significant association.

SOD2 plays a crucial role in the detoxification of superoxide free radicals, which protects cells from reactive oxygen species–induced oxidative damage [56]. Oxidative stress is a hypothesized pathway for the pathophysiology of AMD [56], and SOD2 is a reasonable candidate gene for the disease. Kimura et al. [33] and Gotoh et al. [35] reported that opposite alleles at the same variant V16A in the SOD2 gene are positively associated with neovascular AMD in Japanese populations. This phenomenon, referred to as “flip-flop” associations, may serve as additional evidence of a true genetic association in populations of different ancestry (i.e., when noncausal variants are tested, observed effects of the variants can vary between studies because of differences in their correlation with other causative variants) [57]. Theoretically, flip-flop associations for a genuine causative variant would not occur in samples of the same ethnic origin and are often regarded as spurious findings [57].

Minor allele frequencies of the V16A variant in control subjects were similar among the two earlier Japanese studies and our own study: 16.8% in the studies by Kimura et al. [33], 14.5% in Gotoh et al. [35], and 15.9% in the present study. However, minor allele frequencies of the V16A variant in case subjects were widely divergent; 24.7% in the studies by Kimura et al. [33], 9.1% in Gotoh et al. [35], and 12.1% in the present study. This inconsistency could possibly be due to differences in case selection criteria. Given the possibility that the original study might include a measurable number of PCV subjects, the potential role of the V16A variant in PCV was also explored in the present study. We found that the allele and genotype distributions of this variant were very similar between subjects with PCV and neovascular AMD, and the association results were consistent across these two phenotypes. Another possible reason for the much higher frequency of the V16A variant allele observed in the initial study is genotyping error. There are between-study differences in genotyping methods. The initial study used polymerase chain reaction restriction fragment length polymorphism analysis to genotype this variant [33], whereas we and Gotoh et al. [35] employed the TaqMan technology, which is now a well established technology for genotyping the V16A variant [58,59]. As shown in previous studies [60,61], different genotyping technologies can yield inconsistent genotyping results.

SOD2 maps to chromosome 6q25.3, a region that has not been implicated in AMD by any genome-wide scans [10]. To further validate its association, we accessed the NEI/NCBI dbGAP database, which provides results of genome-wide association study on 395 individuals with AMD and 198 controls from the National Eye Institute Age-Related Eye Disease Study (AREDS). This study looked at three SOD2 SNPs, including the V16A variant and two other SNPs (rs8031 and rs2855116), and found no significant association (all nominal p>0.1), confirming our findings and those of Esfandiary et al. [34].

In conclusion, we found no evidence to support the role of any common SOD2 variation including the V16A variant in the susceptibility to neovascular AMD or PCV. Our study highlights the importance and difficulty in replicating genetic association studies of complex human diseases. The only way to have complete confidence in genetic association is by conducting independent replications. Further replications will allow a definitive conclusion regarding the etiological relevance of this variant in AMD.


This study was supported by a Grant-in-Aid (C) 17591836 from the Ministry of Education, Science, and Culture, Tokyo, Japan. The authors have no financial or conflicting interests to disclose.


1. Friedman DS, O’Colmain BJ, Munoz B, Tomany SC, McCarty C, de Jong PT, Nemesure B, Mitchell P, Kempen J, Eye Diseases Prevalence Research Group. Prevalence of age-related macular degeneration in the United States. Arch Ophthalmol. 2004;122:564–72. [PubMed]
2. Jager RD, Mieler WF, Miller JW. Age-related macular degeneration. N Engl J Med. 2008;358:2606–17. [PubMed]
3. Ciardella AP, Donsoff IM, Huang SJ, Costa DL, Yannuzzi LA. Polypoidal choroidal vasculopathy. Surv Ophthalmol. 2004;49:25–37. [PubMed]
4. Takahashi K, Ishibashi T, Ogur Y, Yuzawa M. Classification and diagnostic criteria of age-related macular degeneration. Nippon Ganka Gakkai Zasshi. 2008;112:1076–84. [PubMed]
5. Kikuchi M, Nakamura M, Ishikawa K, Suzuki T, Nishihara H, Yamakoshi T, Nishio K, Taki K, Niwa T, Hamajima N, Terasaki H. Elevated C-reactive protein levels in patients with polypoidal choroidal vasculopathy and patients with neovascular age-related macular degeneration. Ophthalmology. 2007;114:1722–7. [PubMed]
6. Nakashizuka H, Mitsumata M, Okisaka S, Shimada H, Kawamura A, Mori R, Yuzawa M. Clinicopathologic findings in polypoidal choroidal vasculopathy. Invest Ophthalmol Vis Sci. 2008;49:4729–37. [PubMed]
7. Yuzawa M, Mori R, Kawamura A. The origins of polypoidal choroidal vasculopathy. Br J Ophthalmol. 2005;89:602–7. [PMC free article] [PubMed]
8. Maruko I, Iida T, Saito M, Nagayama D, Saito K. Clinical characteristics of exudative age-related macular degeneration in Japanese patients. Am J Ophthalmol. 2007;144:15–22. [PubMed]
9. Liu Y, Wen F, Huang S, Luo G, Yan H, Sun Z, Wu D. Subtype lesions of neovascular age-related macular degeneration in Chinese patients. Graefes Arch Clin Exp Ophthalmol. 2007;245:1441–5. [PubMed]
10. Haddad S, Chen CA, Santangelo SL, Seddon JM. The genetics of age-related macular degeneration: a review of progress to date. Surv Ophthalmol. 2006;51:316–63. [PubMed]
11. Scholl HP, Fleckenstein M, Charbel Issa P, Keilhauer C, Holz FG, Weber BH. An update on the genetics of age-related macular degeneration. Mol Vis. 2007;13:196–205. [PMC free article] [PubMed]
12. Edwards AO, Ritter R, 3rd, Abel KJ, Manning A, Panhuysen C, Farrer LA. Complement factor H polymorphism and age-related macular degeneration. Science. 2005;308:421–4. [PubMed]
13. Haines JL, Hauser MA, Schmidt S, Scott WK, Olson LM, Gallins P, Spencer KL, Kwan SY, Noureddine M, Gilbert JR, Schnetz-Boutaud N, Agarwal A, Postel EA, Pericak-Vance MA. Complement factor H variant increases the risk of age-related macular degeneration. Science. 2005;308:419–21. [PubMed]
14. Klein RJ, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C, Henning AK, SanGiovanni JP, Mane SM, Mayne ST, Bracken MB, Ferris FL, Ott J, Barnstable C, Hoh J. Complement factor H polymorphism in age-related macular degeneration. Science. 2005;308:385–9. [PMC free article] [PubMed]
15. Hageman GS, Anderson DH, Johnson LV, Hancox LS, Taiber AJ, Hardisty LI, Hageman JL, Stockman HA, Borchardt JD, Gehrs KM, Smith RJ, Silvestri G, Russell SR, Klaver CC, Barbazetto I, Chang S, Yannuzzi LA, Barile GR, Merriam JC, Smith RT, Olsh AK, Bergeron J, Zernant J, Merriam JE, Gold B, Dean M, Allikmets R. A common haplotype in the complement regulatory gene factor H (HF1/CFH) predisposes individuals to age-related macular degeneration. Proc Natl Acad Sci USA. 2005;102:7227–32. [PMC free article] [PubMed]
16. Magnusson KP, Duan S, Sigurdsson H, Petursson H, Yang Z, Zhao Y, Bernstein PS, Ge J, Jonasson F, Stefansson E, Helgadottir G, Zabriskie NA, Jonsson T, Björnsson A, Thorlacius T, Jonsson PV, Thorleifsson G, Kong A, Stefansson H, Zhang K, Stefansson K, Gulcher JR. CFH Y402H confers similar risk of soft drusen and both forms of advanced AMD. PLoS Med. 2006;3:e5. [PMC free article] [PubMed]
17. Maller J, George S, Purcell S, Fagerness J, Altshuler D, Daly MJ, Seddon JM. Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration. Nat Genet. 2006;38:1055–9. [PubMed]
18. Jakobsdottir J, Conley YP, Weeks DE, Mah TS, Ferrell RE, Gorin MB. Susceptibility genes for age-related maculopathy on chromosome 10q26. Am J Hum Genet. 2005;77:389–407. [PMC free article] [PubMed]
19. Rivera A, Fisher SA, Fritsche LG, Keilhauer CN, Lichtner P, Meitinger T, Weber BH. Hypothetical LOC387715 is a second major susceptibility gene for age-related macular degeneration, contributing independently of complement factor H to disease risk. Hum Mol Genet. 2005;14:3227–36. [PubMed]
20. Dewan A, Liu M, Hartman S, Zhang SS, Liu DT, Zhao C, Tam PO, Chan WM, Lam DS, Snyder M, Barnstable C, Pang CP, Hoh J. HTRA1 promoter polymorphism in wet age-related macular degeneration. Science. 2006;314:989–92. [PubMed]
21. Yang Z, Camp NJ, Sun H, Tong Z, Gibbs D, Cameron DJ, Chen H, Zhao Y, Pearson E, Li X, Chien J, Dewan A, Harmon J, Bernstein PS, Shridhar V, Zabriskie NA, Hoh J, Howes K, Zhang K. A variant of the HTRA1 gene increases susceptibility to age-related macular degeneration. Science. 2006;314:992–3. [PubMed]
22. Cameron DJ, Yang Z, Gibbs D, Chen H, Kaminoh Y, Jorgensen A, Zeng J, Luo L, Brinton E, Brinton G, Brand JM, Bernstein PS, Zabriskie NA, Tang S, Constantine R, Tong Z, Zhang K. HTRA1 variant confers similar risks to geographic atrophy and neovascular age-related macular degeneration. Cell Cycle. 2007;6:1122–5. [PubMed]
23. Fritsche LG, Loenhardt T, Janssen A, Fisher SA, Rivera A, Keilhauer CN, Weber BH. Age-related macular degeneration is associated with an unstable ARMS2 (LOC387715) mRNA. Nat Genet. 2008;40:892–6. [PubMed]
24. Yates JR, Sepp T, Matharu BK, Khan JC, Thurlby DA, Shahid H, Clayton DG, Hayward C, Morgan J, Wright AF, Armbrecht AM, Dhillon B, Deary IJ, Redmond E, Bird AC, Moore AT, Genetic Factors in AMD Study Group. Complement C3 variant and the risk of age-related macular degeneration. N Engl J Med. 2007;357:553–61. [PubMed]
25. Maller JB, Fagerness JA, Reynolds RC, Neale BM, Daly MJ, Seddon JM. Variation in complement factor 3 is associated with risk of age-related macular degeneration. Nat Genet. 2007;39:1200–1. [PubMed]
26. Spencer KL, Olson LM, Anderson BM, Schnetz-Boutaud N, Scott WK, Gallins P, Agarwal A, Postel EA, Pericak-Vance MA, Haines JL. C3 R102G polymorphism increases risk of age-related macular degeneration. Hum Mol Genet. 2008;17:1821–4. [PMC free article] [PubMed]
27. Despriet DD, van Duijn CM, Oostra BA, Uitterlinden AG, Hofman A, Wright AF, ten Brink JB, Bakker A, de Jong PT, Vingerling JR, Bergen AA, Klaver CC. Complement component C3 and risk of age-related macular degeneration. Ophthalmology. 2009;116:474–80. [PubMed]
28. Park KH, Fridley BL, Ryu E, Tosakulwong N, Edwards AO. Complement Component 3 (C3) Haplotypes and risk of advanced age-related macular degeneration. Invest Ophthalmol Vis Sci. 2009;50:3386–93. [PubMed]
29. Gold B, Merriam JE, Zernant J, Hancox LS, Taiber AJ, Gehrs K, Cramer K, Neel J, Bergeron J, Barile GR, Smith RT. AMD Genetics Clinical Study Group, Hageman GS, Dean M, Allikmets R. Variation in factor B (BF) and complement component 2 (C2) genes is associated with age-related macular degeneration. Nat Genet. 2006;38:458–62. [PMC free article] [PubMed]
30. Spencer KL, Hauser MA, Olson LM, Schmidt S, Scott WK, Gallins P, Agarwal A, Postel EA, Pericak-Vance MA, Haines JL. Protective effect of complement factor B and complement component 2 variants in age-related macular degeneration. Hum Mol Genet. 2007;16:1986–92. [PubMed]
31. Richardson AJ, Islam FM, Guymer RH, Baird PN. Analysis of rare variants in the complement component 2 (C2) and factor B (BF) genes refine association for age-related macular degeneration (AMD). Invest Ophthalmol Vis Sci. 2009;50:540–3. [PubMed]
32. McKay GJ, Silvestri G, Patterson CC, Hogg RE, Chakravarthy U, Hughes AE. Further assessment of the complement component 2 and factor B region associated with age-related macular degeneration. Invest Ophthalmol Vis Sci. 2009;50:533–9. [PubMed]
33. Kimura K, Isashiki Y, Sonoda S, Kakiuchi-Matsumoto T, Ohba N. Genetic association of manganese superoxide dismutase with exudative age-related macular degeneration. Am J Ophthalmol. 2000;130:769–73. [PubMed]
34. Esfandiary H, Chakravarthy U, Patterson C, Young I, Hughes AE. Association study of detoxification genes in age related macular degeneration. Br J Ophthalmol. 2005;89:470–4. [PMC free article] [PubMed]
35. Gotoh N, Yamada R, Matsuda F, Yoshimura N, Iida T. Manganese superoxide dismutase gene (SOD2) polymorphism and exudative age-related macular degeneration in the Japanese population. Am J Ophthalmol. 2008;146:146, 7. [PubMed]
36. The International HapMap Project Nature. 2003;426:789–96. [PubMed]
37. Swaroop A, Branham KE, Chen W, Abecasis G. Genetic susceptibility to age-related macular degeneration: a paradigm for dissecting complex disease traits. Hum Mol Genet. 2007;16:R174–82. [PubMed]
38. Kondo N, Honda S, Kuno S, Negi A. Role of RDBP and SKIV2L variants in the major histocompatibility complex class III region in polypoidal choroidal vasculopathy etiology. Ophthalmology. 2009;116:1502–9. [PubMed]
39. Bessho H, Kondo N, Honda S, Kuno S, Negi A. Coding variant Met72Thr in the PEDF gene and risk of neovascular age-related macular degeneration and polypoidal choroidal vasculopathy. Mol Vis. 2009;15:1107–14. [PMC free article] [PubMed]
40. Seddon JM, Sharma S, Adelman RA. Evaluation of the clinical age-related maculopathy staging system. Ophthalmology. 2006;113:260–6. [PubMed]
41. de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and power in genetic association studies. Nat Genet. 2005;37:1217–23. [PubMed]
42. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75. [PMC free article] [PubMed]
43. Wigginton JE, Cutler DJ, Abecasis GR. A note on exact tests of Hardy–Weinberg equilibrium. Am J Hum Genet. 2005;76:887–93. [PMC free article] [PubMed]
44. Solé X, Guinó E, Valls J, Iniesta R, Moreno V. SNPStats: a web tool for the analysis of association studies. Bioinformatics. 2006;22:1928–9. [PubMed]
45. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–5. [PubMed]
46. Gauderman WJ. Sample size requirements for matched case-control studies of gene-environment interaction. Stat Med. 2002;21:35–50. [PubMed]
47. Marchini J, Cardon LR, Phillips MS, Donnelly P. The effects of human population structure on large genetic association studies. Nat Genet. 2004;36:512–7. [PubMed]
48. Falush D, Stephens M, Pritchard JK. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics. 2003;164:1567–87. [PMC free article] [PubMed]
49. Kubo M, Hata J, Ninomiya T, Matsuda K, Yonemoto K, Nakano T, Matsushita T, Yamazaki K, Ohnishi Y, Saito S, Kitazono T, Ibayashi S, Sueishi K, Iida M, Nakamura Y, Kiyohara Y. A nonsynonymous SNP in PRKCH (protein kinase C eta) increases the risk of cerebral infarction. Nat Genet. 2007;39:212–7. [PubMed]
50. Yamada K, Gerber DJ, Iwayama Y, Ohnishi T, Ohba H, Toyota T, Aruga J, Minabe Y, Tonegawa S, Yoshikawa T. Genetic analysis of the calcineurin pathway identifies members of the EGR gene family, specifically EGR3, as potential susceptibility candidates in schizophrenia. Proc Natl Acad Sci USA. 2007;104:2815–20. [PMC free article] [PubMed]
51. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000;155:945–59. [PMC free article] [PubMed]
52. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177–88. [PubMed]
53. Ioannidis JP, Patsopoulos NA, Evangelou E. Heterogeneity in meta-analyses of genome-wide association investigations. PLoS One. 2007;2:e841. [PMC free article] [PubMed]
54. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–60. [PMC free article] [PubMed]
55. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–58. [PubMed]
56. Beatty S, Koh H, Phil M, Henson D, Boulton M. The role of oxidative stress in the pathogenesis of age-related macular degeneration. Surv Ophthalmol. 2000;45:115–34. [PubMed]
57. Lin PI, Vance JM, Pericak-Vance MA, Martin ER. No gene is an island: the flip-flop phenomenon. Am J Hum Genet. 2007;80:531–8. [PMC free article] [PubMed]
58. Packer BR, Yeager M, Staats B, Welch R, Crenshaw A, Kiley M, Eckert A, Beerman M, Miller E, Bergen A, Rothman N, Strausberg R, Chanock SJ. SNP500Cancer: a public resource for sequence validation and assay development for genetic variation in candidate genes. Nucleic Acids Res. 2004;32(Database issue):D528–32. [PMC free article] [PubMed]
59. Cox A, Dunning AM, Garcia-Closas M, Balasubramanian S, Reed MW, Pooley KA, Scollen S, Baynes C, Ponder BA, Chanock S, Lissowska J, Brinton L, Peplonska B, Southey MC, Hopper JL, McCredie MR, Giles GG, Fletcher O, Johnson N, dos Santos Silva I, Gibson L, Bojesen SE, Nordestgaard BG, Axelsson CK, Torres D, Hamann U, Justenhoven C, Brauch H, Chang-Claude J, Kropp S, Risch A, Wang-Gohrke S, Schürmann P, Bogdanova N, Dörk T, Fagerholm R, Aaltonen K, Blomqvist C, Nevanlinna H, Seal S, Renwick A, Stratton MR, Rahman N, Sangrajrang S, Hughes D, Odefrey F, Brennan P, Spurdle AB, Chenevix-Trench G, Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer. Beesley J, Mannermaa A, Hartikainen J, Kataja V, Kosma VM, Couch FJ, Olson JE, Goode EL, Broeks A, Schmidt MK, Hogervorst FB, Van't Veer LJ, Kang D, Yoo KY, Noh DY, Ahn SH, Wedrén S, Hall P, Low YL, Liu J, Milne RL, Ribas G, Gonzalez-Neira A, Benitez J, Sigurdson AJ, Stredrick DL, Alexander BH, Struewing JP, Pharoah PD, Easton DF, Breast Cancer Association Consortium A common coding variant in CASP8 is associated with breast cancer risk. Nat Genet. 2007;39:352–8. [PubMed]
60. Lorentzen AR, Celius EG, Ekstrøm PO, Wiencke K, Lie BA, Myhr KM, Ling V, Thorsby E, Vartdal F, Spurkland A, Harbo HF. Lack of association with the CD28/CTLA4/ICOS gene region among Norwegian multiple sclerosis patients. J Neuroimmunol. 2005;166:197–201. [PubMed]
61. Pearce CL, Van Den Berg DJ, Makridakis N, Reichardt JK, Ross RK, Pike MC, Kolonel LN, Henderson BE. No association between the SRD5A2 gene A49T missense variant and prostate cancer risk: lessons learned. Hum Mol Genet. 2008;17:2456–61. [PMC free article] [PubMed]

Articles from Molecular Vision are provided here courtesy of Emory University and the Zhongshan Ophthalmic Center, Sun Yat-sen University, P.R. China
PubReader format: click here to try


Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...


Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...