The CX3CR1 gene is located on chromosome 3 at position 3p21.3. The Figure was prepared based on the reverse strand in Hg19 covering chromosome 3: 39,304,985 to 39,323,226 base pairs (bp). The position and relative size of exons are depicted in red and the promoter region in blue. SNP rs1014638 lies 3057 bp 5′ of the CX3CR1 gene and SNP rs17038640 lies 4828 bp 3′ of the CX3CR1 gene.
r2 and D′ LD measures were calculated using Haploview32 for the combined case/control samples from 5 study populations (Women’s Health Study, Physicians’ Health Study, Women’s Antioxidant and Folic Acid Cardiovascular Study, Nurses’ Health Study, and Health Professionals Follow-up Study). In each panel, the upper left triangle shows LD for the study sample while the lower right triangle shows LD for the same SNPs in the 1000 Genomes European panel (381 individuals, release November 23, 2010) for comparison.34 Shading corresponds to the superimposed numeric estimates of LD for each pair of SNPs.
Schaumberg DA, Rose L, DeAngelis MM, Semba RD, Hageman GS, Chasman DI. Prospective Study of Common Variants in CX3CR1 and Risk of Macular DegenerationPooled Analysis From 5 Long-term Studies. JAMA Ophthalmol. 2014;132(1):84-95. doi:10.1001/jamaophthalmol.2013.5506
Copyright 2014 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
The CX3CR1 gene is implicated as a candidate gene for age-related macular degeneration (AMD) through several lines of evidence. There is uncertainty, however, as to whether common genetic variants in CX3CR1 alter risk of AMD, since prior studies have been inconsistent and mostly limited to evaluation of 2 nonsynonymous variants, T280M (rs3732378) and V249I (rs3732379).
To determine if common variants in CX3CR1 predict future risk of AMD.
Design, Setting, and Participants
Prospective nested case-control study within 5 large study populations with long-term follow-up. We measured genotypes for T280M, V249I, and 13 other common single-nucleotide polymorphisms (SNPs) of the CX3CR1 gene among people who developed AMD (n = 1110, including 369 with neovascular AMD) and 2532 age- and sex-matched controls.
Main Outcomes and Measures
We determined the incidence rate ratios (RR) and 95% CIs for incidence of AMD for each variant and examined interactions with other AMD-associated variants and modifiable risk factors.
In additive genetic models, we identified nonsignificant associations with AMD for T280M (RR, 0.87; P = .07) and 3 other SNPs, rs2853707 (RR, 0.88; P = .07), rs12636547 (RR, 0.85; P = .10), and rs1877563 (RR, 0.84; P = .06), 1 of which, rs2853707, is positioned in the CX3CR1 promoter region and was associated with neovascular AMD (RR, 0.75; P = .03). We observed that a recessive model was a better fit to the data for some SNPs, with associations between rs11715522 and AMD (RR, 1.27; P = .03) and between rs2669845 (RR, 3.10; P = .04), rs2853707 (RR, 0.48; P = .050), and rs9868689 (RR, 0.31; P = .02) and neovascular AMD. Moreover, in exploratory analyses, we identified a number of possible interactions including between V249I and rs2669845 and dietary intake of ω-3 fatty acids (P = .004 and P = .009, respectively) for AMD; between rs2669845 and obesity (P = .03) for neovascular AMD; between T280M and complement component 3 (C3) R102G for AMD (P = .03); between rs2669845 and Y402H in complement factor H for AMD (P = .04); and between rs2669845, rs2853707, and V249I and C3 R102G for neovascular AMD (P = .008; .04; and .002, respectively).
Conclusions and Relevance
This study failed to identify significant associations between common CX3CR1 variants and AMD after considering the number of SNPs analyzed and multiple comparisons. However, we observed evidence consistent with recessive modes of association and that an effect of CX3CR1 variants may depend on other factors including dietary intake of ω-3 fatty acids, obesity, and genotypes at CFH Y402H and C3 R102G. If replicated in other populations, these findings would support a role for CX3CR1 in AMD but also suggest that its role may involve mechanisms that are independent of the T280M/V249I variations.
The leading cause of blindness among white individuals in the United States and other industrialized countries,1 age-related macular degeneration (AMD) is a complex disease of aging caused by the interplay between predisposing genetic factors and exposure to environmental and lifestyle risk factors such as diet, cigarette smoking, and obesity.2,3 Vast strides in AMD research primarily over the past decade have resulted in the identification of a group of genes for which common variants exhibit very strong associations with AMD, providing what is perhaps one of the best examples in support of the “common disease–common variants” hypothesis.4,5
At the same time, continued research has underlined the complexity behind the genetic epidemiology of AMD. Part of the complexity of the AMD pathogenesis relates to evidence that even strongly associated single common genetic variants are, on their own, probably not sufficient to cause AMD.6 Instead, evidence suggests that a person's risk of AMD is determined by the interplay of multiple genetic variants with each other and with environmental and lifestyle factors (ie, it is determined by a combination of gene × gene and gene × environment interactions).7 Developing a more complete understanding of the genetic epidemiology of AMD is needed to lay the groundwork for the identification of more effective and targeted treatment or preventive strategies and to improve the accuracy of risk prediction models.7,8
There is clear evidence for a pivotal role of immune and inflammatory pathway alterations in AMD. Common variants within a handful of complement pathway genes alter risk of AMD, including variants in complement factor H (CFH) (1q32), complement component 2 (C2), complement factor B (CFB), and complement component 3 (C3).2,6 Some studies have also described significant associations with AMD for the functionally relevant T280M polymorphism in the CX3C chemokine receptor 1 (CX3CR1) gene,9- 11 and there are several other lines of evidence to support a role in AMD for CX3CR1 and its ligand CX3CL1 (aka fractalkine), including human, animal, and laboratory studies.12- 18 However, the largest genetic epidemiology study of CX3CR1 and AMD recently found no evidence for association of this single-nucleotide polymorphism (SNP) with the particularly visually devastating neovascular form of AMD.19
In the present study, we investigated the 2 previously identified nonsynonymous coding variants in CX3CR1 (T280M and V249I) as well as a set of 13 common variants across CX3CR1 in a prospective nested case-control study within 5 large study populations. We aimed to test for associations with AMD and to investigate potential interrelationships of this gene and other genetic and nongenetic risk factors.
The study population consisted of nested case-control samples of participants in 5 prospective studies: the Women’s Health Study, the Physicians’ Health Study, the Women’s Antioxidant and Folic Acid Cardiovascular Study, the Nurses’ Health Study, and the Health Professionals Follow-up Study. Study methods and characteristics of the study populations have been widely published.2,20- 28 The Women’s Health Study, Physicians’ Health Study, and Women’s Antioxidant and Folic Acid Cardiovascular Study were all randomized, placebo-controlled trials designed to investigate the effect of aspirin and antioxidants on cardiovascular or cancer outcomes. The Physicians’ Health Study is a population of initially healthy male physicians, whereas the Women’s Health Study comprises initially healthy female health professionals. Women’s Antioxidant and Folic Acid Cardiovascular Study participants are female health professionals at high risk of cardiovascular disease, with a history of myocardial infarction or at least 3 major risk factors for cardiovascular disease. The Health Professionals Follow-up Study and Nurses’ Health Study are observational cohorts that were not restricted based on initial health status. The Health Professionals Follow-up Study consists of male dentists, pharmacists, and other health professionals, and the Nurses’ Health Study consists of female nurses. Together, these study populations include a total of more than 100 000 men and women with stored baseline blood samples, who provided written consent. The research protocol was approved by the institutional review boards at Brigham and Women’s Hospital and the Harvard School of Public Health. A description of the contributing study populations is provided in Table 1.
We defined baseline as the time when participants provided a baseline blood sample and completed a mailed questionnaire on which they reported demographic information as well as a medical history and personal information on a number of lifestyle factors, including height, weight, and cigarette-smoking history. We excluded any participants with prevalent AMD at baseline, as well as participants who did not provide a baseline blood specimen, and more than 99% of all study participants reported their ethnicity as white. We followed up participants with yearly follow-up questionnaires (every 2 years in the Nurses’ Health Study and Health Professionals Follow-up Study) to obtain information on newly developed diseases including AMD.
We have previously described and validated procedures for our 2-stage documentation of incident AMD, which are nearly identical in each study population.22,25,29- 31 On each study questionnaire, we asked participants to report any new diagnosis of AMD, including the month and year of diagnosis as well as the name and address of the diagnosing eye physician, and for signed permission to review medical records. For each report of AMD, we sent a letter to the participant’s ophthalmologist or optometrist to obtain information from the medical record on the date of diagnosis, best-corrected visual acuity, and chorioretinal lesions present (drusen; retinal pigment epithelial changes including atrophy, hypertrophy, and retinal pigment epithelium detachment; geographic atrophy; subretinal neovascular membrane; or disciform scar), as well as treatment history. For the present study, we included confirmed cases of AMD associated with a visual acuity loss of 20/30 or worse. In those cases in which other ocular anomalies were also present, we asked the eye physician to judge whether the visual acuity would be expected to be 20/30 or worse as a result of AMD alone. We defined neovascular AMD as the documented presence of a retinal pigment epithelial detachment, subretinal neovascular membrane, or disciform scar that was not due to other causes (eg, histoplasmosis or choroidal rupture). Dry AMD included cases with the documented presence of drusen and/or retinal pigment epithelial changes but with no signs of neovascular AMD. We classified participants based on the most severely affected eye. We selected 2 controls for each case of dry AMD and 3 controls for each case of neovascular AMD at random from study participants in the same study population as the case who were still at risk of AMD at the time the case was diagnosed, who were of the same age within 1 year, and who reported having an eye examination in the past 2 years.
We examined 15 SNPs in or flanking CX3CR1 including 2 previously identified coding SNPs (rs3732378 [T280M] and rs3732379 [V249I]) and 13 tag SNPs selected using the phase II HapMap data from the CEU populations (release 22; www.hapmap.org). Tagging was done with the tagger module in Haploview, with criteria that each SNP must have had (1) a minor allele frequency of 5% or greater and (2) an r2 value of at least 0.8 for pairwise tagging.32 The position of these SNPs within the CX3CR1 gene is delineated in Figure 1. We also genotyped the following highly replicated AMD-associated SNPs: rs1061170 (CFH Y402H), rs2230199 (C3 R102G), and rs10490924 (ARMS2 A69S), all of which demonstrated highly significant associations with AMD in this study population (Table 2). DNA was extracted from the buffy coat fraction of centrifuged blood specimens using the QIAmp Blood Kit (Qiagen). The genotyping was carried out in a custom 384-SNP multiplex using an Illumina Golden Gate assay. Automated genotype calling was carried out using Illumina GenomeStudio version 2010.2, which uses GenCall software to automatically cluster, call genotypes, and assign confidence scores. All laboratory personnel were blinded to case/control status.
We examined allele distributions for each SNP and used χ2 tests for Hardy-Weinberg equilibrium and estimated linkage disequilibrium (LD) (both r2 and D′) between each pair of SNPs. We initially fit logistic regression models under an additive genetic model to estimate the incidence rate ratios (RRs) and 95% CIs for each genotype adjusted for other risk factors. We first obtained separate estimates of the incidence RR in each study population and tested for heterogeneity using the Cochrane Q test. Because there was no statistical evidence for heterogeneity between study populations (P for each SNP ≥.61), we present only pooled data from the study populations. Controlling for age, sex, cigarette smoking, and obesity, we modeled the allelic effects using a multiplicative (ie, additive) coding scheme using a single variable for each SNP coded 0 for participants homozygous for the major allele (or, alternatively for the candidate SNPs, the allele previously found to be associated with the lowest risk of AMD), 1 for heterozygotes, and 2 for participants homozygous for the minor allele (or, alternatively for the candidate SNPs, the allele previously found to be associated with increased risk of AMD). We next fit models using separate indicator variables for participants who were heterozygous and participants who were homozygous for the risk allele, as well as recessive models using an indicator variable for participants who were homozygous for the minor allele at each locus in reference to participants who were homozygous for the major allele or heterozygotes. To arrive at the best-fitting model, we compared these alternative models using the Akaike information criterion.33 As a rule of thumb, 2 models are statistically indistinguishable if the Akaike information criterion difference is less than 2. We then proceeded to fit both additive and recessive models for each SNP also adjusting for CFH Y402H, ARMS2 A69S, and C3 R102G, 3 SNPs with very well-validated associations with AMD.
For T280M and V249I, as well as any SNPs that were found to be associated with AMD with a P value of <.10, we next tested one by one for interactions with CFH Y402H, ARMS2 A69S, and C3 R102G, as well as for possible gene × environment interactions with cigarette smoking, obesity, and ω-3 fatty acid intake (known AMD risk factors). We used additive coding for CFHY402H, ARMS2 A69S, and C3 R102G and included product terms to test for interactions with other CX3CR1 SNPs using either additive or recessive coding. We used permutation tests to confirm the analytic significance tests for interactions, randomizing case vs control status within matched sets and performing association testing over 10 000 iterations.
The study population included the 1110 cases of incident AMD matched with 2532 controls, including 369 cases with neovascular AMD. Cases and controls were matched on age in each study population (mean age at baseline was 62 years), but not on other risk factors such as cigarette smoking and obesity (Table 3). Of the 15 CX3CR1 SNPs, genotype data were successfully obtained for each SNP in 97% or more of cases and controls. Genotype and allele frequencies are provided in Table 4. We found no significant departures from Hardy-Weinberg equilibrium for any of the 15 SNPs among the control group (each P > .10).
In logistic regression models controlling for age, sex, cigarette smoking status, and obesity, we observed no significant association between T280M or V249I with AMD in additive (RR, 0.92; 95% CI, 0.80-1.06; P = .24 for T280M; RR, 1.01; 95% CI, 0.90-1.14; P = .82 for V249I), dominant, or recessive models (Table 5). Models testing for associations of the other 13 SNPs showed a nonsignificant association of modest magnitude in additive models for rs2669845 (RR, 1.15; 95% CI, 0.99-1.35; P = .07) and rs1877563 (RR, 0.85; 95% CI, 0.73-1.00; P = .056), with similar results in the codominant models for these SNPs (Table 5). Further adjustment for CFH Y402H, ARMS2 A69S, and C3 R102G generally strengthened associations. In these models, the association with T280M was most consistent with a modest protective effect of the rare allele (RR, 0.87; 95% CI, 0.75-1.01; P = .07). Comparison of Akaike information criterion statistics identified 2 SNPs for which the recessive model was favored, revealing an increased risk for those with 2 copies of the rare G allele at rs11715522 (RR, 1.27; 95% CI, 1.02-1.58; P = .03) and a nonsignificant increased risk for participants with 2 copies of the rare C allele at rs13062158 (RR, 1.18; 95% CI, 0.88-1.58; P = .27).
For the subset of neovascular AMD cases, we observed a nonsignificant association with the CX3CR1 promoter SNP rs2853707 (RR, 0.82; 95% CI, 0.66-1.02; P = .07) in an additive model adjusting for age, sex, cigarette smoking, and obesity, and this relationship appeared somewhat stronger after additional control for CFH Y402H, ARMS2 A69S, and C3 R102G (RR, 0.75; 95% CI, 0.59-0.97; P = .03) (Table 6). Comparison of Akaike information criterion statistics identified 4 SNPs for which the recessive model was favored. In the recessively coded models adjusted for age, sex, cigarette smoking, and obesity, 3 of these CX3CR1 SNPs showed nominally significant associations with neovascular AMD, and 1 SNP showed borderline significance (Table 6). After further adjustment for CFH Y402H, ARMS2 A69S, and C3 R102G, participants with 2 copies of the minor T allele at rs2669845 had a 3-fold higher risk of development of neovascular AMD compared with participants with 1 or no copies of this allele (RR, 3.10; 95% CI, 1.08-8.87; P = .04). Increased risk of neovascular AMD was also observed for participants with 2 copies of the G allele at rs11715522 (RR, 1.47; 95% CI, 1.03-2.10; P = .03), but this was attenuated after adjustment for CFH Y402H, ARMS2 A69S, and C3 R102G (RR, 1.42; 95% CI, 0.96-2.10; P = .08). Protective effects were seen for participants with 2 copies of the minor A allele of rs9868689 and for participants with 2 copies of the minor C allele at the rs2853707 promoter SNP. After full adjustment, the RRs for association with neovascular AMD were 0.31 (95% CI, 0.12-0.82; P = .02) for rs9868689 and 0.48 (95% CI, 0.23-1.00; P = .050) for rs2853707 (Table 6).
The LD measures (Figure 2) showed D' = 1.0 and r2 = 0.54 between T280M and V249I. Measures of LD were lower between these 2 SNPs and the other CX3CR1 SNPs, showing significant or borderline associations with AMD. For example, LD was estimated at D' = 0.48 and r2 = 0.03 between T280M and rs11715522 and D' = 0.026 and r2 = 0.00 between T280M and rs2853707, suggesting that the observed associations of the other CX3CR1 SNPs with AMD are not due to LD with T280M.
Investigation of potential gene × environment interactions identified suggestive interactions between some CX3CR1 SNPs and dietary intake of ω-3 fatty acids and obesity (Table 7), but not with cigarette smoking (data not shown). Specifically, the increased risk of AMD associated with obesity appeared to be due to stronger associations in the subgroups of participants with at least 1 risk allele at either rs2669845 (RR, 1.83; 95% CI, 1.12-2.98) or rs11715522 (RR, 2.23; 95% CI, 1.00-4.99). Interactions with ω-3 fatty acids tended toward a protective effect of ω-3 fatty acids in the strata with the rare alleles (T and A, respectively) at rs3732379 and rs2669845; however, for rs11715522, we observed an increased risk of neovascular AMD associated with higher ω-3 fatty acid intake among the subgroup carrying at least 1 copy of the rarer G allele (RR, 1.62; 95% CI, 1.01-2.61).
Examination of gene × gene interactions (Table 8) suggested a possible interaction between rs2853707 and ARMS2 A69S (P for interaction = .08) for all AMD cases vs controls assuming additive effects at rs2853707. Separate models for those with vs without at least 1 ARMS2 A69S risk allele revealed that rs2853707 was associated with a reduced risk of AMD only among people with no ARMS2 A69S risk alleles (RR, 0.73; 95% CI, 0.58-0.92 for TC; RR, 0.53; 95% CI, 0.34-0.85 for CC), whereas there was no effect among those with at least 1 ARMS2 A69S risk allele (RR, 0.97; 95% CI, 0.74-1.28 for TC; RR, 0.94; 95% CI, 0.55-1.64 for CC). For all AMD cases vs controls, we also identified 1 statistically significant interaction assuming recessive effects between rs2669845 and CFH Y402H (P for interaction = .04), as well as 2 interactions of borderline significance (Table 8).
We also observed possible interactions for neovascular AMD assuming additive genetic effects of the CX3CR1 SNPs, specifically between rs11715522 and CFH Y402H (P for interaction = .08) and between T280M and C3 R102G (P for interaction = .051). In stratified models, the increased risk of neovascular AMD associated with rs11715522 appeared strongest among those who carried at least 1 CFH Y402H risk allele (RR, 1.28; 95% CI, 0.99-1.66 for TG; RR, 1.64; 95% CI, 0.98-2.76), whereas the 280M allele conferred decreased risk of neovascular AMD among the subset of participants with no C3 R102G risk alleles (RR, 0.53; 95% CI, 0.29-0.98 for 280T/M; RR, 0.28; 95% CI, 0.08-0.96). There were also 3 possible interactions with C3 R102G, specifically for rs2669845 (P for interaction = .008), rs2853707 (P for interaction = .04), and V249I (P for interaction = .002) (Table 8). Increased risk of neovascular AMD associated with rs2669845 was limited to participants who also carried at least 1 C3 R102G risk allele, whereas the minor allele of rs2853707 was associated with a decreased risk of AMD in the same subgroup. The V249I SNP tended toward a protective effect among those with 249I and no C3 R102G risk alleles but an increased risk when 249I was present along with at least 1 C3R102G risk allele (Table 9). In models assuming a recessive effect for the CX3CR1 SNP, we observed possible interactions between T280M and C3 R102G (P for interaction = .03) and between T280M and ARMS2 A69S (P for interaction = .09). Permutation tests confirmed the magnitude of the P values for all gene × gene interactions.
Similar to findings from a recent clinic-based cross-sectional study including 1093 cases with neovascular AMD,19 we failed to observed a statistically significant association of the T280M loss-of-function CX3CR1 SNP with incident AMD, and the data from this prospective evaluation tended in the direction of a modest protective association in contrast to the increased risks observed in some small clinic-based cross-sectional studies. We also observed no overall association between the V249I SNP and AMD. However, unlike previous studies, we examined not only the T280M and V249I SNPs, but included 13 other common SNPs in CX3CR1 including rs2853707, which lies within the CX3CR1 promoter region. Among these, we identified 1 SNP (rs11715522) that was nominally associated with incident AMD overall and 3 SNPs (rs2669845, rs2853707, and rs9868689) that showed associations with incident neovascular AMD, though these would not reach significance if adjusted for multiple testing. Further exploratory investigation suggested several possible interactions between CX3CR1 variants and CFH Y402H, C3 R102G, obesity, and dietary intake of ω-3 fatty acids.
Although this study is limited by our inability to perform standardized clinical assessments of retinal status among participants of these large geographically dispersed study populations of male and female health professionals, we have demonstrated that our case ascertainment method has high specificity,29,35 which minimizes bias in a prospective study.36 Furthermore, the consistency of our findings in these populations linking CFH Y402H and ARMS2 A69S with AMD, as well as our prior work on modifiable risk factors for AMD,29,35,37,38 and the strong associations demonstrated in the present data for CFH Y402H, ARMS2 A69S, and C3 R102G with AMD provide further reassurance of the validity of the findings for variants within CX3CR1. Findings of the study must also be interpreted in light of the large number of tests performed and the modest P values observed in the models for the primary tests of association of each SNP with AMD, none of which would be significant after adjustment for multiple testing, as well as the lack of replication in additional independent study populations.
CX3CR1 is the receptor for the CX3 chemokine ligand (CX3CL1, fractalkine). Fractalkine is an unusually large chemokine that induces directed chemotaxis in nearby responsive immune cells. Fractalkine is expressed on numerous cells, including activated endothelial cells and macrophages, and its expression is enhanced in the presence of inflammatory stimuli and in atherosclerosis. It is also the only one of the 200 or so known chemokines to exhibit not only a soluble but also a transmembrane form, the latter giving it the ability to mediate leukocyte adhesion to cells such as microglia (the resident macrophages in the retina) that express CX3CR1. The CX3CL1/CX3CR1 axis also appears to have novel functions in regard to cell adhesion, antiapotosis, and cell proliferation.39
CX3CR1-expressing microglia appear to have a complex role in relation to the evolution of neurodegenerative diseases. Evidence suggests microglia may both contribute to and limit tissue injury during the chronic low-level inflammation and neurodegeneration, and these effects may vary within different organs and diseases, as well as with age.39- 42 There may be a precarious balance between beneficial and detrimental effects, which may depend at least in part on presumed alterations in CX3CR1 that result from common genetic variation as well as on interactions with other key AMD-associated factors (both genetic and environmental). A recent investigation based on a rat model of blue light–induced photoreceptor degeneration combined with cell culture studies demonstrated that apoptosis of retinal photoreceptors was followed by increased levels of fractalkine and CX3CR1 in conjunction with microglial activation and migration and upregulation of proinflammatory factors such as interleukin 1β and tumor necrosis factor α. Blockage of soluble fractalkine decreased the inflammatory response, whereas overexpression of the membrane-bound form was associated with neuroprotection.15 In human AMD donor eyes, others have observed CX3CR1 deposits in drusen and CX3CR1-positive microglial cells interposed between choroidal vessels and in close contact with neovascular lesions.14 There are 2 known nonsynonymous SNPs in CX3CR1, and laboratory studies have shown defective migration of retinal microglial cells isolated from individuals carrying the 280M allele, and this effect was shown to be related to interactions with the membrane-bound form of fractalkine.14 Aged CX3CR1-deficient mice show accentuated subretinal accumulation of microglial cells, drusenlike lesions (shown to be lipid-bloated microglial cells), and outer retinal degeneration, which could be prevented by raising the mice in a light-restricted environment. Laser injury to CX3CR1-deficient mice resulted in significantly greater choroidal neovascularization.14 When interpreting this literature, there may be important differences between mouse and human CX3CL1/CX3CR1.43
Previous epidemiological studies have largely been limited to studies of the possible association between 1 or both of the nonsynonymous SNPs (T280M and 249I) and AMD, yielding inconsistent results. The first few reports on the association of the T280M and V249I CX3CR1 variants in AMD suggested a 2- to 3-fold increased risk of AMD among people carrying the minor alleles at each locus.9,10,14 More recently, however, Zerbib and colleagues19 recruited 1093 patients with neovascular AMD from 4 retinal centers in France along with a group of 396 controls with normal retinal examination findings and found no association of 280M with AMD (odds ratio, 0.9; 95% CI, 0.6-1.3 for 280T/M; OR, 0.6; 95% CI, 0.3-1.4 for 280M/M). Similarly, Brión and colleagues44 reported no association with T280M or 4 tag SNPs in CX3CR1 in a study of 385 cases of AMD (225 with atrophic AMD, 57 with neovascular AMD, and 71 with mixed AMD) and 282 age-matched controls. Finally, a small study of copy number variation in CX3CR1 in relation to AMD demonstrated a mildly protective effect that was diminished after adjustment for age.45
To our knowledge, there have been no prior studies of rs2853707, which lies within the CX3CR1 promoter region. Because of its position, we used MatInspector (http://www.genomatix.de/) to explore the possibility that this SNP may have functional relevance and found that the minor allele is predicted to create a binding site for Myb-like transcriptional regulators. The Myb gene family encodes a number of nuclear transcriptional proteins including c-Myb, a DNA-binding transcription factor that functions in apoptosis, proliferation, and differentiation. Alterations in c-Myb activity can alter the balance of inflammatory activity in the context of tissue injury or vasculoproliferative disease, and increased c-Myb activity increases survival rates of certain cell types.46 Given the fact that fractalkine/CX3CR1 has been implicated in these same biological pathways,39 it seems plausible that the present findings of significant associations between rs2853707 and AMD may be related to functionally relevant variation within the CX3CR1 promoter region.
Because the genes involved in AMD have pleiotropic effects throughout the body, variants in AMD-associated genes could also alter the clinical course or survival of individuals who carry certain alleles. Particularly when the alleles are common, such effects could introduce selection bias when prevalent rather than incident cases are studied.36 This is potentially quite important for studies of CX3CR1, since people with the 280M and 249I CX3CR1 variants have been shown to have a reduced risk of cardiovascular disease. At the same time, although evidence is more limited, 280M and/or 249I have also been associated with reduced risk of asthma,47 as well as modestly increased risks of metabolic syndrome, diabetes, higher waist circumference, and obesity.48 Other evidence links the CX3CL1/CX3CR1 axis with Alzheimer disease (reduced risk in CX3CR1-deficient mice),49 polymyositis and dermatomyositis (patients have increased serum fractalkine levels),50 rheumatoid arthritis, and other conditions.51 The present study, using a validated prospective nested case-control method should therefore help clarify associations of common variants of CX3CR1 with risk of AMD, since the population that gives rise to the cases is clearly established, rates of loss to follow-up are extremely low in all the study populations, and the control selection and analysis methods inherently account for censoring due to death or loss to follow-up.
The findings of this investigation also point to an additional level of complexity in understanding the possible role of CX3CR1 in AMD. Prior epidemiological studies have revealed that risk of AMD is affected by a combination of environmental effects plus strong effects of variants within several genes, especially CFH, ARMS2, and C3, and there is a growing body of evidence suggesting that these genetic and nongenetic risk factors interact with each other in a variety of ways to determine individual AMD risk.2,3,52,53 Our data suggesting possible interactions between common variants in CX3CR1 and ω-3 fatty acid intake, obesity, and 3 strongly AMD-associated variants (CFH Y402H, ARMS2 A69S, and C3 R102G) provide further details regarding the interplay of common AMD-associated variants and suggest that more work is needed to fully understand the intricacies of the genetic and nongenetic contributors to this blinding disease.
We identified possible interactions of CX3CR1 SNPs and obesity for neovascular AMD, and there is evidence showing associations between variation at CX3CR1 and obesity.48,54 Together such observations are consistent with the idea that the impact of obesity on risk of AMD may be different depending on an individual’s genetic underpinnings. We also observed possible interactions between 3 genetic variants in CX3CR1 and dietary intake of ω-3 fatty acids, which has been associated with risk of AMD in a number of epidemiological studies, and with slowed progression of retinal lesions in a Ccl2(−/−)/Cx3Cr1(−/−) murine double knockout model.55 The present study also points to possible interactions between variants in CX3CR1 and other common strongly AMD-associated variants. These include suggested interactions between the rs2853707 promoter region SNP and ARMS2 A69S as well as rs11715522 and CFH Y402H; between rs2669845 and CFH Y402; and a number of interactions with C3 R102G, including with rs2669845, rs2853707, T280M, and V249I.
In summary, this prospective study provides new information on the potential association between common variation within CX3CR1 and risk of AMD that fails to confirm prior findings of associations between the 280M or 249I alleles with AMD. The data suggest the possibility of a more minor role for CX3CR1 (as compared, eg, with CFH, ARMS2, and C3) that may include an intricate relationship between common variants in this gene; common variants in CFH, ARMS2, and C3; obesity; and dietary intake of ω-3 fatty acids with risk of AMD. The findings are consistent with a protective association of the 280M allele within subgroups of the population defined by ARMS2 and C3 genotypes and protection from AMD associated with the promoter SNP rs2853707, though these observations require further confirmation. If replicated in other large populations, such observations suggest that mechanisms other than those previously demonstrated in studies of the CX3CR1 T280M variant could be involved in some cases of AMD.
Corresponding Author: Debra A. Schaumberg, ScD, OD, MPH, Moran Center for Translational Medicine, 65 N Mario Capecchi Dr, Salt Lake City, UT 84132 (email@example.com).
Submitted for Publication: August 29, 2012; final revision received April 25, 2013; accepted June 6, 2013.
Published Online: November 28, 2013. doi:10.1001/jamaophthalmol.2013.5506.
Author Contributions: Dr Schaumberg had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Schaumberg, Semba, Hageman.
Acquisition of data: Schaumberg, Chasman.
Analysis and interpretation of data: Schaumberg, Rose, DeAngelis, Hageman, Chasman.
Drafting of the manuscript: Schaumberg.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Schaumberg, Rose, Chasman.
Obtained funding: Schaumberg, Hageman.
Administrative, technical, or material support: Schaumberg, DeAngelis, Semba, Hageman.
Study supervision: Schaumberg, Chasman.
Conflict of Interest Disclosures: None reported.
Funding/Support: This work was supported by National Institutes of Health grants EY017362, EY013834, EY009611, EY014458, CA87969, CA49449, HL35464, CA34944, CA40360, HL26490, HL34595, CA47988, HL43851, and HL46959.
Role of the Sponsor: The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.