Molecular Vision 2005; 11:941-949 <http://www.molvis.org/molvis/v11/a113/> Received 19 November 2004 | Accepted 21 October 2005 | Published 4 November 2005

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Joint effects of smoking history and APOE genotypes in age-related macular degeneration

Silke Schmidt,¹ Jonathan L. Haines,² Eric A. Postel,³ Anita Agarwal,⁴ Shu Ying Kwan,¹ John R. Gilbert,¹ Margaret A. Pericak-Vance,¹ William K. Scott¹
 
 

¹Center for Human Genetics and the ³Duke Eye Center, Duke University Medical Center, Durham, NC; ²Center for Human Genetics Research and the ⁴Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN

Correspondence to: Silke Schmidt, PhD, Center for Human Genetics, Duke University Medical Center, Box 3445, Durham, NC, 27710; Phone: (919) 684-0624; FAX: (919) 684-0925; email: silke.schmidt@duke.edu

Abstract

Purpose: Age-related macular degeneration (AMD) is a leading cause of severe visual impairment in older adults worldwide. Cigarette smoking is one of the most consistently identified environmental risk factors for the disease. Several studies have implicated the apolipoprotein E (APOE) gene as modulating AMD risk. The purpose of this study was to investigate whether APOE genotypes modify the smoking-associated risk of AMD.

Methods: Patients with early- and late-stage AMD (n=377) and a group of unrelated ethnically matched controls of similar age (n=198) were ascertained at two sites in the southeastern United States. Smoking history and APOE genotype distribution in cases and controls were compared by multivariable logistic regression.

Results: All measures of smoking history showed a highly significant association with AMD, and odds ratio estimates were consistently higher when only patients with exudative AMD were compared to controls. Main effects of APOE genotypes in the overall analysis did not reach statistical significance. The analysis of exudative AMD patients suggested that the risk increase due to smoking was greatest in carriers of the APOE-2 allele, with genotype-specific odds ratios increasing from 1.9 for APOE-4 carriers (p=0.11) to 2.2 for APOE-3/3 homozygotes (p=0.007) to 4.6 (p=0.001) for APOE-2 carriers, compared to nonsmoking APOE-3/3 individuals. Measures of statistical interaction indicated more than additive, and possibly more than multiplicative, joint effects of APOE and smoking history, however, the interaction was not statistically significant on either scale.

Conclusions: We hypothesize that a history of smoking is a stronger risk factor for exudative AMD in carriers of the APOE-2 allele, compared to carriers of APOE-4 and the most common APOE-3/3 genotype. To further clarify the association of AMD with APOE and smoking history, future studies should consider both factors simultaneously.

Introduction

Age-related macular degeneration (AMD) is a disease of the central region of the retina (macula), which leads to impairment and ultimately loss of central vision, and therefore has a substantial impact on an individual's quality of life. Since the incidence and prevalence of AMD increase strongly with age and life expectancy in developed countries has also been increasing, the prevalence of AMD is expected to rise sharply in the near future. AMD is a clinically heterogeneous disorder with a poorly understood etiology. Population-based longitudinal studies [1-3] have established that the presence of extracellular protein/lipid deposits (drusen) between the basal lamina of the retinal pigmented epithelium (RPE) and the inner layer of Bruch's membrane is associated with an increased risk of progressing to an advanced form of AMD, either geographic atrophy or exudative disease. The presence of large and indistinct (soft) drusen is considered an early form of the disorder and is often referred to as age-related maculopathy (ARM).

Epidemiologically, AMD is a complex disorder with contributions of environmental factors, lifestyle factors, and genetic susceptibility. The first identified AMD susceptibility allele is the Y402H variant in the complement factor H (CFH) gene (OMIM 134370), whose substantial effect on AMD risk has been replicated by multiple studies [4-8]. Other polymorphisms that have been suggested but not yet replicated include the D299G variant in the toll-like receptor 4 (TLR4) gene (OMIM 603030) [9], and the T280M variant in the CX3CR1 gene (OMIM 601470) [10]. Due to the substantial public health burden posed by AMD, the interaction of genetic and potentially modifiable environmental factors in modulating an individual's disease risk is a research question of particular interest. Next to age and family history, the most consistently identified lifestyle risk factor for AMD is smoking [11]. Cigarette smoking has been positively associated with ARM, geographic atrophy, and exudative AMD [12]. In addition to smoking, AMD is believed to share other risk factors, such as high blood pressure, dietary fat consumption, and obesity, with cardiovascular disease [13]. Interestingly, a gene known to influence the risk of cardiovascular disease, the apolipoprotein E (APOE) gene (OMIM 107741), has also been associated with AMD. The apoE protein coded by this gene is involved in cholesterol and lipoprotein metabolism and also plays an important, albeit incompletely understood, role in neurodegenerative processes, as evidenced by its strong effect on the risk of Alzheimer disease (AD) [14]. The APOE gene has three alleles (ε2, ε3, ε4), which code for three protein isoforms with different biochemical properties. The APOE-3 allele is the most common one in all human populations; however, the exact frequencies of the three alleles vary greatly across different ethnic groups [15]. In contrast to the well-established increased risk of AD [14] and cardiovascular disease [16] conferred by the APOE-4 allele, a number of studies have reported an opposite effect of this allele on the risk of AMD [17-23]. Only one study of Caucasian [24] and one of Chinese [25] individuals failed to replicate this finding. The underlying mechanism for the putative protective effect of APOE-4 is currently unknown. Some studies reported an increased risk of AMD due to the APOE-2 allele [17,22], and one study suggested that this effect may be more pronounced in males compared to females [21]. Since the APOE-2 allele is the least common of the three alleles, a greater sample size is required for sufficient statistical power to detect its effect, which may explain the inconsistent findings in different studies. An alternative explanation is that the disparities are due to uncontrolled confounding or effect modification by another risk factor. Since evidence for a modifying effect of APOE genotypes on smoking-associated risks exists for other diseases [26], the goal of our study was to investigate this possibility for AMD.

Methods

Study population

As part of an ongoing large-scale study of genetic and environmental risk factors for AMD, we have ascertained AMD patients, their affected and unaffected family members, and a group of unrelated controls of similar age and ethnic background at two sites in the southeastern United States: Duke University Medical Center (DUMC) and Vanderbilt University Medical Center (VUMC). Using color fundus photography, enrolled individuals were assigned (by EAP and AA) one of five different grades of macular findings, as described previously [19,27] and summarized in Table 1. Our AMD classification is a modification of the AREDS grading system, using Wisconsin grading system example slides [28] and the International Classification System [29] as guides. The more severely affected eye was used to classify individuals. Unrelated controls were enrolled via (i) study advertisement in DUMC and VUMC affiliated newsletters; (ii) recruitment presentations by study coordinators at local retirement communities, which were likely to obtain health care at DUMC or VUMC, respectively; and (iii) AMD-related seminars for the general public sponsored by DUMC or VUMC ophthalmology clinics. Spouses of AMD patients were asked to participate as controls. Controls eligible for enrollment were offered a free comprehensive eye exam including fundus photography to ensure that the same methodology was used to assign AMD grades as for cases and their relatives ascertained in clinic. All cases and controls included in this study were white and at least 55 years of age. The study protocol was approved by the respective Institutional Review Boards at DUMC and VUMC, the research adhered to the tenets of the Declaration of Helsinki, and informed consent was obtained from all study participants. The study population for the analysis presented here included 377 AMD patients with early (grade 3) or advanced (grades 4 and 5) AMD, and 198 unrelated controls without AMD (grades 1 and 2).

Measures of smoking history

Following the clinical assessment, participants were asked to complete a self-administered questionnaire to elicit information on demographics (including a lifetime occupational history), lifestyle factors (such as cigarette smoking, dietary supplement use, and reproductive history) and a semi-quantitative food frequency questionnaire [30]. The questionnaire was formatted to maximize readability for individuals with low vision; however, if participants indicated that they could not complete the form, a project coordinator offered to assist the participants in filling out the questionnaire. Regular cigarette smoking was assessed by two questions: (1) "Have you smoked at least 100 cigarettes in your lifetime?", and (2) "Did you ever smoke cigarettes at least once per week?" Individuals answering "yes" to both questions were asked the average number of cigarettes they smoked per day, the year that they started smoking, whether they had quit smoking, and if so, what year. Measures of cigarette smoking were then constructed from the responses to these questions. The most general measurement of smoking history was constructed as an "ever/never" variable based on a participant's response to question (1) above. The more detailed measures of smoking were calculated for all individuals who provided information about the year in which they started smoking (92% of "ever" smokers). Since all individuals who provided information on start year of smoking had started well before the likely onset of the disease process leading to AMD, we felt that our "ever/never" classification was appropriate even for those individuals who did not provide more detailed information. The onset of visual symptoms may change an individual's smoking behavior, and in particular, may cause cases to stop smoking prior to their date of diagnosis. Given that the exact onset of symptoms is difficult to capture for a progressive disease like AMD, changing the reference year for calculating smoking status to five or ten years prior to their study examination date may reduce this potential bias. However, this did not affect the statistical significance of case-control differences in the smoking measures we used (data not shown), and we chose to present results for the definitions described below, where smoking history up to the age at examination was considered.

The "smoking history" (current, past, never) was defined in the following way. Individuals who smoked at least 100 cigarettes in their lifetime, smoked at least weekly, and gave information on start year of smoking were classified as current or past smokers depending on if and when they quit smoking. Two indicator variables compared current and past smoking to a referent group of never smokers.

The total number of years of smoking ("duration of smoking"), based on start and stop year of smoking. Two indicator variables were constructed for individuals smoking more or less than the median number of years calculated on the combined population of cases and controls. The two exposure levels were compared to a referent level of never smoking.

The average number of "cigarettes smoked per day" was based on start and stop year of smoking. Two indicator variables were constructed by dividing the sample at the median number of cigarettes per day and comparing the two levels to never-smokers.

The "pack-years of smoking" was defined in the following way. To examine the multiplicative effect of duration and dosage, the commonly used "pack-years" measure (pack-years=[cigarettes per day times years smoked]/20 cigarettes per pack) was used. Two indicator variables were constructed by dividing the sample at the median number of pack-years and comparing the two levels to never-smokers.

APOE genotyping

Following genomic DNA extraction from whole blood with the Puregene system (Gentra Systems, Minneapolis, MN), APOE alleles were determined by genotyping two single-nucleotide polymorphisms (SNPs) in exon 4 of the gene with a TaqMan allelic discrimination assay on an ABI7900 platform (Applied Biosystems, Foster City, CA). The two SNPs correspond to amino acid substitutions at codons 112 (cysteine->arginine) and 158 (arginine->cysteine). Of the four theoretically possible allelic combinations (haplotypes) of these two SNPs, only three are observed in human DNA. Genotyping was performed blinded to AMD affection status. To ensure consistent allele calling, duplicated quality control (QC) samples were distributed within and across 96 well plates and a perfect match of allele calls was required to pass QC checks. Smoking and genotype data were stored in the PEDIGENE database [31].

Statistical analysis

To assess the association between cigarette smoking and risk of AMD, we used logistic regression models incorporating the primary exposure (measures of cigarette smoking, APOE genotype) and relevant covariates (age, sex). The outcome variable was affection status, comparing individuals diagnosed with AMD ("cases") to unaffected, unrelated controls. Individuals were classified by APOE genotype into APOE-2 and APOE-4 carriers, with the APOE-3/3 genotype as the referent group. Individuals with the APOE-2/4 genotype were included in both the APOE-2 and APOE-4 exposure groups. Age at examination was included in the analysis as a continuous variable and sex was included as a dichotomous variable with female as the referent level. Unconditional logistic regression models were constructed for all variables, controlling for confounding by age and sex (SAS version 8.1, SAS Institute, Cary, NC). Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each model, and Wald χ² p values less than or equal to 0.05 were considered of nominal statistical significance.

To examine the pattern of smoking effects across APOE genotypes with respect to a common reference group, we computed genotype-specific ORs in nonsmokers and smokers by using an "additive" coding scheme in our logistic regression model [32], with continued adjustment for age and sex. Specifically, separate indicator variables were constructed for individuals who smoked and had the APOE-3/3 genotype, and for smoking and nonsmoking carriers of APOE-2 and APOE-4, respectively. This allowed for the simultaneous estimation of five ORs and their associated 95% CIs and p values, using nonsmoking APOE-3/3 individuals as the common reference group.

To assess statistical interaction as a departure from joint multiplicative effects, we compared the joint odds ratio for smoking and carrying the APOE-2 allele to the product of the individual odds ratios. To assess interaction as a departure from joint additive effects, we computed an approximation to Rothman's synergy index and its 95% CI based on model coefficients from the above logistic regression [32-34]. This is an approximation since the exact validity of the formula requires absence of other covariates (confounders) in the model. As discussed previously [34], the computation of a synergy index after adjustment for confounders may lead to biased estimates of the strength of interaction on an additive scale.

To investigate whether the effects of smoking and APOE genotypes on exudative AMD were different from their effects on the combined AMD phenotype (early AMD, geographic atrophy, and exudative AMD), we performed separate analyses comparing only patients with exudative AMD to the same control group. Our sample size was insufficient for a separate analysis of geographic atrophy. Since we viewed our analysis as hypothesis generating in terms of a potential genotype-mediated difference in the effect of smoking on AMD risk, we did not correct for multiple testing.

Results

The distribution of AMD grades and some basic characteristics for our study population are shown in Table 1. The proportion of females was very similar in AMD patients (63.7%) and controls (62.1%, p=0.72), but patients had a significantly older average age at examination (75.9 years) than controls (66.8 years, p<0.0001). All case-control comparisons of smoking-related variables and APOE genotypes were adjusted for confounding effects of age and sex. Almost 70% of patients were affected with exudative AMD, while atrophic AMD made up only 10.9% of cases, and the remainder (20.2%) were cases with an early stage of AMD. The mean age at exam of patients with exudative and atrophic AMD was very similar (76.5 and 77.9 years, respectively, p=0.24). The majority of controls (68.7%) were assigned grade 1. Table 2 summarizes APOE genotype and allele distribution and measures of smoking history for cases and controls. APOE genotypes were in Hardy-Weinberg equilibrium in both cases (p=0.15) and controls (p=0.92). Consistent with previous studies, the APOE-2 allele frequency was higher in cases than controls (10.0% compared to 6.1%) and the APOE-4 allele frequency was lower in cases than controls (9.9% compared to 13.6%), without adjustment for age and sex. A much higher proportion of AMD cases than controls had smoked at least 100 cigarettes during their lifetime and were thus considered ever-smokers (61.8% compared to 48.5%).

As shown in Table 3, both the ever/never smoking classification and the more detailed measures of smoking history had a highly significant effect on AMD risk. When the subgroup of exudative patients (n=260) was compared to the same control group, all point estimates for smoking-related variables were noticeably greater. The OR for ever-smoking increased from 2.1 to 2.8, with a very strong effect (OR 9.3) of current smoking and a reduced but still significant effect of past smoking (OR 2.0). A higher cumulative dose of smoking, as measured by pack-years above the median in the study sample, was associated with a 5 fold increase in risk. Odds ratio patterns for APOE-2 and APOE-4 carriers were consistent with previously reported effects, but did not reach statistical significance.

Table 4 illustrates the pattern of smoking effects across APOE genotypes with respect to a common reference group. The OR for smoking increased in a genotype-dependent manner from 1.6 for APOE-4 carriers to 1.8 for APOE-3/3 genotypes to 3.0 for APOE-2 carriers, compared to nonsmoking APOE-3/3 individuals. The effect of smoking was only statistically significant for APOE-3/3 (p=0.02) and APOE-2 carriers (p=0.01). The joint effects of APOE and smoking were consistent with a multiplicative model (3.0/[(1.4)(1.8)]=1.2), as confirmed by a nonsignificant multiplicative interaction term (p=0.49) in a logistic regression model. The data suggested greater than additive joint effects of APOE-2 and smoking, with a synergy index of 1.7=([3.0-1]/[1.4+1.8-2]). However, interaction on an additive scale was not statistically significant based on the 95% CI of the synergy index (0.2-15.4). The pattern of odds ratios was very similar when grade 2 controls were excluded from the analysis (smoking-associated OR for APOE-3/3 individuals 2.1, p=0.02; smoking-associated OR for APOE-2 carriers 3.6, p=0.02).

The genotype-dependent risk increase due to smoking was even more apparent in the subgroup of exudative AMD cases (Table 5). Here, the risk increased from 1.9 in APOE-4 carriers (p=0.11) to 2.2 in APOE-3/3 genotypes (p=0.007) to 4.6 in APOE-2 carriers (p=0.001), compared to nonsmoking APOE-3/3 individuals. There was a suggestion of greater than multiplicative joint effects of APOE and smoking (4.6/[(1.0)(2.2)]=2.1), although a multiplicative interaction term in the standard logistic regression model did not reach statistical significance (p=0.20). The synergy index was 3.0 with a wide 95% CI (0.3-28.5), indicating lack of statistically significant interaction on an additive scale. When only grade 1 controls were compared to patients with exudative AMD, the point estimate for the smoking-associated odds ratio for APOE-2 carriers was even greater, but with a wider 95% CI and of similar statistical significance (OR 5.8, 95% CI 1.9-17.6, p=0.002). Higher smoking-associated odds ratios for APOE-2 carriers, compared to APOE-3/3 genotypes, were found consistently in samples stratified by age at examination (age<70 years [46 cases, 127 controls]: smoking-associated OR for APOE-3/3 individuals 3.4, p=0.01; smoking-associated OR for APOE-2 carriers 7.3, p=0.004; age >=70 years [214 cases, 71 controls]: smoking-associated OR for APOE-3/3 individuals 1.8, p=0.14; smoking-associated OR for APOE-2 carriers 3.2, p=0.07).

Discussion

We have, for the first time, detected suggestive evidence for a modifying effect of APOE genotypes on the smoking-associated risk of AMD, particularly the exudative form of the disease. Our results support the hypothesis that the effect of smoking is most harmful in carriers of the APOE-2 allele, compared to APOE-4 carriers and the most common APOE-3/3 reference genotype. While other measures of smoking history confirmed this trend (data not shown), the results were strongest when ever-smokers were compared to never-smokers. The failure to incorporate smoking history information in previous studies may explain the inconsistent results reported for an APOE-2 effect, which may partially be due to variable proportions of smokers and nonsmokers in the respective study populations. Similarly, the report of a potential interaction of APOE and sex on the multiplicative scale, suggesting that only male but not female carriers of APOE-2 were at increased risk of AMD [21], may be due to confounding by smoking history, since a higher proportion of males than females in the current at-risk population are known to have smoked. Most of the evidence for an APOE-2 associated increased risk in our data set was contributed by patients with exudative AMD who reported a lifetime history of smoking; however, our sample size of patients with atrophic AMD did not provide sufficient statistical power for a separate analysis and we cannot rule out that a similar effect may exist for this subgroup of patients.

The analysis of this study population did not support a statistically significant inverse association of the APOE-4 allele and AMD, in contrast to several earlier studies [17-23]. While there is overlap in the AMD patients analyzed here and in our earlier reports [19,21], the current study includes only fully examined and graded controls, whereas the majority of controls analyzed in the earlier reports merely reported an absence of significant visual impairment. In the current study, we observed a general trend towards a smaller proportion of APOE-4 carriers in AMD cases than controls. The confidence interval for the APOE-4 effect overlaps with previously reported odds ratio estimates on the order of 0.5-0.6. Further support for a protective effect of the APOE-4 allele in AMD was provided by recent reports of a greatly increased APOE-4 allele frequency in the island population of Rapanui, compared to whites, and an almost complete absence of AMD in this population [35]. We believe that the most likely explanation for the lack of statistical significance of the protective APOE-4 effect in our current data set is type 2 error.

Evidence for a modifying effect of APOE genotypes on smoking-associated risks has also been reported for cardiovascular disease [26]. For AMD, two biologically plausible hypotheses that may explain our findings have been suggested by previous research. The first involves cholesterol levels. The retina is the site of the body's second highest apoE production, after the liver [36]. Therefore, apoE likely plays an important role in maintaining normal retinal function, as supported by several experimental studies [37-39]. Cholesterol is an important constituent of drusen, contributes to the pathogenesis of atherosclerosis, and is known to accumulate in the retina with increasing age [40]. Smokers are known to have higher serum cholesterol and low-density lipoprotein (LDL) levels [41]. This may contribute to their increased AMD risk, consistent with reports of higher dietary cholesterol levels in exudative AMD patients compared to age-matched controls [42], and a possible, though disputed, protective effect of lipid-lowering drugs, such as statins, on AMD risk or progression [43,44]. Due to differential LDL receptor binding properties [45], the apoE2 isoform may be less efficient in removing LDL particles from RPE tissue and Bruch's membrane, which may contribute to the accumulation of extracellular debris and drusen formation. A potential role of the apoE protein in retinal abnormalities associated with high dietary cholesterol levels is supported by experimental studies [46].

The second hypothesis involves nitric oxide (NO) production. NO is a free radical and an important messenger molecule with diverse functions throughout the body. It has been proposed that apoE isoforms may modulate NO production in the brain by regulating the intracellular availability of arginine, the only substrate for NO synthesis [47-49]. In particular, apoE4 was reported to increase NO synthesis, relative to apoE2 and apoE3. Smoking is known to lead to endothelial dysfunction and is associated with decreased endothelial NO production [50]. Thus, the presence of the apoE2 protein in individuals who smoke may greatly reduce endothelial NO levels in various cell tissues. If the normal function of NO in the retina is to neutralize circulating oxidized lipids [51], its decreased availability may promote oxidative damage to the RPE cells. Interestingly, data from our group suggested that polymorphisms in the endothelial nitric oxide synthase (NOS3, eNOS) gene may be associated with an increased AMD risk in smokers, but not in nonsmokers [52].

If confirmed in larger and, ideally, prospective studies, our finding that the smoking-associated increase in the risk of exudative AMD may be greatest in carriers of the APOE-2 allele would be an example of the kind of gene-environment interaction that is believed to play a crucial role in many complex disorders. While the sample size of our study was too small to demonstrate statistically significant interaction on the additive or multiplicative scale, our analysis generated a very interesting hypothesis and suggests that future studies of the APOE gene in large samples of AMD patients and carefully examined controls should incorporate smoking history information whenever possible. This is underscored further by the newly reported, already widely replicated association of the Y402H variant in the CFH gene with AMD risk [4-8], which supports an important role for innate immunity in the etiology of AMD. Since plasma levels of CFH are known to decrease with smoking [53], studies of the joint effect of APOE, CFH, and smoking are a logical next step for the AMD research community.

Acknowledgements

This study was supported by grants U10EY012118 (to MAP-V) and R03EY015216 (to SS) from the National Institutes of Health (NIH), National Eye Institute, and by grant P60AG011268 from the NIH, National Institute on Aging (to Harvey Cohen, MD). Some of the data in this paper were presented in abstract form (Scott WK, Schmidt S, Fan YT, Postel EA, Agarwal A, Gass JDM, Gilbert JR, Haines JL, Pericak-Vance MA. Cigarette smoking and APOE genotype interaction in age-related macular degeneration. ARVO Annual Meeting; April 25-29, 2004; Fort Lauderdale (FL)). We would like to express our appreciation to all of the AMD patients, their relatives and the control individuals who generously participated in the study. We thank Jennifer Caldwell, Ruth Domurath, Molly Klein, and Katie Haynes for their tireless efforts in ascertaining many of the individuals used in this study, and Jason Galloway, Maureen Shaw, and Valerie Mitchell for assistance in data management. We also thank the following clinics and clinicians for referring individuals to the study: Southern Retina, LLC (Charles Harris, MD); Vitreo-Retinal Surgeons (Michael E. Duan, MD and Christopher J. Devine, MD); Georgia Retina, PC; and The Retina Group of Washington.

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