December 2010
Volume 51, Issue 12
Free
Biochemistry and Molecular Biology  |   December 2010
Joint Effect of Cigarette Smoking and CFH and LOC387715/HTRA1 Polymorphisms on Polypoidal Choroidal Vasculopathy
Author Affiliations & Notes
  • Hideo Nakanishi
    From the Department of Ophthalmology and Visual Sciences and
    the Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan;
  • Kenji Yamashiro
    From the Department of Ophthalmology and Visual Sciences and
  • Ryo Yamada
    the Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan;
  • Norimoto Gotoh
    From the Department of Ophthalmology and Visual Sciences and
    the Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan;
  • Hisako Hayashi
    From the Department of Ophthalmology and Visual Sciences and
    the Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan;
  • Isao Nakata
    From the Department of Ophthalmology and Visual Sciences and
    the Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan;
  • Masaaki Saito
    the Department of Ophthalmology, Fukushima Medical University, Fukushima, Japan;
  • Tomohiro Iida
    the Department of Ophthalmology, Fukushima Medical University, Fukushima, Japan;
  • Akio Oishi
    the Kobe City Medical Center General Hospital, Kobe, Japan; and
  • Yasuo Kurimoto
    the Kobe City Medical Center General Hospital, Kobe, Japan; and
  • Keitaro Matsuo
    the Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.
  • Kazuo Tajima
    the Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan.
  • Fumihiko Matsuda
    the Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan;
  • Nagahisa Yoshimura
    From the Department of Ophthalmology and Visual Sciences and
  • Corresponding author: Hideo Nakanishi, Department of Ophthalmology, Kyoto University Graduate School of Medicine, Shogoin Kawahara-cho 54, Sakyo-ku, Kyoto 606-8507, Japan; hideon@kuhp.kyoto-u.ac.jp
Investigative Ophthalmology & Visual Science December 2010, Vol.51, 6183-6187. doi:10.1167/iovs.09-4948
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      Hideo Nakanishi, Kenji Yamashiro, Ryo Yamada, Norimoto Gotoh, Hisako Hayashi, Isao Nakata, Masaaki Saito, Tomohiro Iida, Akio Oishi, Yasuo Kurimoto, Keitaro Matsuo, Kazuo Tajima, Fumihiko Matsuda, Nagahisa Yoshimura; Joint Effect of Cigarette Smoking and CFH and LOC387715/HTRA1 Polymorphisms on Polypoidal Choroidal Vasculopathy. Invest. Ophthalmol. Vis. Sci. 2010;51(12):6183-6187. doi: 10.1167/iovs.09-4948.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: To investigate whether the major genetic and environmental risk factors of age-related macular degeneration (AMD)—CFH Y402H and LOC387715 A69S and cigarette smoking—are also associated with polypoidal choroidal vasculopathy (PCV) and whether the associations of CFH Y402H and LOC387715 A69S with PCV are modified by smoking.

Methods.: Three hundred seventy-five Japanese patients with PCV and 847 Japanese who served as population-based control subjects, all ≥55 years of age, were studied. CFH Y402H (rs1061170) and LOC387715 A69S (rs10490924) were genotyped with a single-nucleotide polymorphism (SNP) assay. An unconditional logistic regression model was used to analyze the association between age, sex, smoking status, CFH Y402H, LOC387715 A69S, and PCV. The synergy index (SI) was measured to assess gene–smoking and gene–gene interaction as a departure from additivity.

Results.: CFH Y402H, LOC3387715 A69S, and cigarette smoking status were all significantly associated with PCV; for CFH Y402H, the adjusted odds ratio (OR) for the number of copies of the allele was 1.63 (95% confidence interval [CI], 1.12–2.36; P < 0.05); for LOC387715 A69S, the adjusted OR was 2.26 (95% CI, 1.83–2.78; P < 0.0001); and for smoking status (ever versus never smoked), the adjusted OR was 1.45 (95% CI, 1.00–2.10; P < 0.05). The joint effect of CFH Y402H and smoking was significantly greater than the additive scale, with an SI of 2.41 (95% CI, 1.14–5.10).

Conclusions.: CFH Y402H and LOC387715 A69S are both significantly associated with PCV. Cigarette smoking is an environmental risk factor for PCV. The findings suggest interactions between CFH 402H and cigarette smoking in PCV.

Polypoidal choroidal vasculopathy (PCV) was first characterized by multiple, recurrent, serosanguineous detachments of the retinal pigment epithelium and neurosensory retina. 1 3 The characteristic lesion of PCV is an inner choroidal vascular network of vessels ending in aneurysmal bulges or outward projections, which were visible as reddish-orange polyplike structures in the peripapillary and macular areas. 4 PCV often presents with clinical manifestations similar to those of neovascular age-related macular degeneration (AMD), 4 and it is usually clinically categorized as a subtype of neovascular AMD. 5 Individuals of African American or Asian descent, both pigmented individuals, are at a greater risk of PCV. 6 In Japan, approximately half of patients with neovascular AMD also have PCV. 7 Thus, PCV is an important macular disease, especially in pigmented individuals. Because PCV often presents with clinical manifestations similar to those of neovascular AMD, we hypothesized that PCV and AMD have an overlap in pathophysiology. 
AMD is a complex disease that is caused by a combination of genetic and environmental factors. 8,9 Genetic factors have been thought to make a strong contribution to AMD. 10,11 Among the genetic factors in AMD that have been investigated, a single-nucleotide polymorphism (SNP), rs1061170, also known as Y402H, of the complement factor H (CFH) gene on the long arm of chromosome 1, region 32, has been shown to be a major AMD-associated polymorphism. 12 14 More recently, two SNPs in the LOC387715 (age-related maculopathy susceptibility 2, ARMS2)/HtrA serine peptidase 1 (HTRA1) region on 10q26, that is, rs10490924 (also known as A69S) and rs11200638, were found in several studies to be strongly associated with AMD. 15 18 In the Japanese, these two SNPs, rs11200638 and rs10490924, were shown to be in almost complete linkage disequilibrium (LD). 19,20 Of note, the results of several studies have shown a positive association of PCV with LOC387715 A69S and/or HTRA1 rs11200638. 19,21 23 However, an association between CFH Y402H and PCV has not been reported. 21,24  
Epidemiologic studies have suggested several environmental risk factors for AMD. Among the modifiable environmental factors, cigarette smoking is a major risk factor that has been repeatedly validated. 25,26 However, an association between PCV and cigarette smoking has not been assessed. 
Thus, the purpose of this study was to conduct a hospital-based, case–control study to determine whether major genetic risk factors for AMD, CFH Y402H and LOC387715 A69S, and cigarette smoking, an environmental risk factor for AMD, are also associated with PCV. We also investigated whether the associations of CFH Y402H and LOC387715 A69S with PCV are modified by cigarette smoking. 
Materials and Methods
All procedures used in this study adhered to the tenets of the Declaration of Helsinki. The institutional review board and the ethics committee of each institute approved the protocols of the study. All the patients were fully informed of the purpose and procedures of the study, and a signed, written consent was received from each patient. 
Patients and Control Subjects
Three hundred seventy-five unrelated Japanese patients with PCV who were ≥55 years-of-age were selected from the Center for Macular Diseases of Kyoto University Hospital, Fukushima Medical University Hospital, and Kobe City Medical Center General Hospital. All the patients underwent a comprehensive ophthalmic examination, including dilated indirect and contact lens slit lamp biomicroscopy, color fundus photography, optical coherence tomography (OCT), fluorescein angiography (FA), and indocyanine green angiography (IGA). The diagnosis of PCV was based on IGA, which showed the typical polypoidal lesions connecting to the branching vascular network. The polypoidal lesion could be a single polyp or a cluster of polyps. In most cases, reddish-orange nodules that had been seen by ophthalmoscopic examination corresponded to the polypoidal lesions detected by IGA. The IGA images of the patients were evaluated by two independent macular specialists experienced in IGA interpretation, and the diagnoses of PCV were confirmed. In case of discrepancy, a third observer was involved to arbitrate. When no polypoidal swellings were visible on the IGA images, the case was excluded. 
For a general population control, 847 healthy unrelated Japanese individuals who were ≥55 years of age were recruited from the Aichi Cancer Center Research Institute. 
Genotyping
We genotyped the two major AMD-associated SNPs: rs1061170 (Y402H) of CFH and rs10490924 (A69S) of LOC387715. Genomic DNAs were prepared from the leukocytes of the peripheral blood. The dbSNP database, build 128 (www.ncbi.nlm.nih.gov/projects/SNP; provided in the public domain by the National Center for Biotechnology Information, Bethesda, MD), was used to extract the genotyping information for the SNPs. Both SNPs were genotyped with SNP (Taqman assays performed on ABI Prism 7700; Applied Biosystems, Foster City, CA), according to the manufacturer's instructions. 
Smoking Status
Information on smoking status was obtained by self-reported questionnaire in the three categories of never, former, and current smokers. The never smokers were those who had smoked fewer than 100 cigarettes in the past, current smokers were those who had smoked in the past year, and former smokers were those who had quit smoking more than 1 year earlier. Because we believed that the effect of smoking was important in the period preceding the diagnosis of PCV, and because current smokers had likely smoked in the past, we grouped the current smokers and former smokers into an ever smokers group and compared their data with information on those who were classified as never smokers, to evaluate the effect of smoking on the development of PCV. Smoking intensity was evaluated as pack years of smoking (the number of cigarettes smoked per day times the number of years smoked/20 cigarettes per pack). Then two indicator categories were constructed by dividing the ever smokers at the median number of pack years. 
Statistical Analyses
The Hardy-Weinberg equilibrium (HWE) for the genotypic distribution was evaluated by using the HWE-exact test for each group. Differences in the demographic features between the PCV group and the control group were tested for statistical significance by the χ2 test for dichotomous data and by the unpaired t-test for continuous data. Differences in the observed genotypic distribution between the PCV group and the control group were tested by the exact test for trend. 
The unconditional logistic regression model was used to analyze the association of age, sex, smoking status, CFH Y402H, LOC387715 A69S with PCV. CFH Y402H and LOC387715 A69S were entered into the logistic model as a count (0, 1, or 2) corresponding to the number of risk alleles the patient or control carried. Each odds ratio (OR) was estimated and the 95% confidence intervals (CIs) were calculated. Interactions between the two polymorphisms and smoking status on PCV were tested using product terms (polymorphism*smoking or polymorphism*polymorphism) in logistic regression models. Additional analysis to assess the possible gene-smoking/gene–gene interaction as departure from additivity was performed using the synergy index (SI) proposed by Rothman. 27 When SI is greater than 1, the joint effect of two risk factors on the disease is greater than the sum of independent effect of the two factors, which suggests the presence of an interaction. Because the present study was a hospital-based case–control study, we used the OR instead of relative risk (RR) to calculate the SI. 28 The level of statistical significance was set at P < 0.05. The statistical analyses were performed with the software R (http://www.r-project.org/). The calculation of the SI was performed with the software R package gmvalid (http://cran.r-project.org/web/packages/gmvalid/index.html). 
Results
The demographics of the study population and the results of the univariate analysis that was conducted to detect the differences between the PCV group and the control group are shown in Table 1. The PCV group was significantly older (P < 0.0001) and had a higher male-to-female ratio (P < 0.0001) than the control group. The proportion of ever smokers was significantly higher in the PCV group than in the control group (P < 0.0001). The information on smoking intensity was obtained from 366 (97.6%) PCV cases and 840 (99.2%) controls. A subgroup analysis on the ever smokers showed that a higher cumulative dose of smoking, as indicated by pack years above the median of the ever smokers, was associated with PCV (P < 0.01). There were significant differences in the genotypic distribution for the two AMD-associated SNPs between the PCV group and the control group; P < 0.0005 for rs1061170 (CFH Y402H) and P < 0.0001 for rs10490924 (LOC387715 A69S). 
Table 1.
 
Characteristics of the Study Population and Results of the Statistical Analysis
Table 1.
 
Characteristics of the Study Population and Results of the Statistical Analysis
PCV (n = 375) Control (n = 847) Univariate P Unconditional Logistic Regression*
P OR (95% CI)
Age, mean ± SD 73.10 ± 7.04 65.47 ± 6.64 <2.0 × 10−16 <2.0 × 10−16 1.17 (1.15–1.20)
Sex
    Men 269 418 3.5 × 10−13 5.2 × 10−4 1.99 (1.35–2.93)
    Women 106 429
Smoking status
    Ever 225 348 9.9 × 10−10 0.049 1.45 (1.00–2.10)
    Never 150 499
Pack-years
    >Median (37.5) 123 154 0.0067‡
    ≤Median (37.5) 93 187
    Missing data 9 7
CFH Y402H
    CC 1 5 3.4 × 10−4 § 0.010 1.63 (1.12–2.36)‖
    CT 78 100
    TT 296 742
LOC387715 A69S
    TT 133 113 4.4 × 10−16 § 1.6 × 10−14 2.26 (1.83–2.78)‖
    GT 152 401
    GG 90 333
The unconditional logistic regression analysis with the five variables (age, sex [male/female], smoking status [ever/never], CFH Y402H, and LOC387715 A69S) revealed that these five factors were all significantly associated with PCV after adjustment for the other variables; for smoking status (ever versus never smoker), adjusted OR = 1.45 (95% confidence interval [CI], 1.00–2.10; P < 0.05); for CFH Y402H, adjusted OR = 1.63 (95% CI, 1.12–2.36; P < 0.05); and for LOC387715 A69S, adjusted OR = 2.26 (95% CI, 1.83–2.78; P < 0.0001; Table 1). 
Although logistic regression analysis with the product term did not show significant interaction of smoking*CFH Y402H, smoking*LOC387715 A69S, or CFH Y402H*LOC387715 A69S (data not shown), the assessment of the gene-smoking interaction according to Rothman's SI showed highly suggestive results (Table 2). The joint effect of CFH Y402H and smoking was significantly greater than the additive scale with an SI of 2.41 (95% CI, 1.14–5.10). The joint effect of LOC387715 A69S and smoking was greater than the additive scale with an SI of 1.57; however, the interaction was not significant based on the 95% CI of the SI (0.94–2.63). 
Table 2.
 
Interaction between Cigarette Smoking and CFH Y402H, LOC387715 A69S in PCV
Table 2.
 
Interaction between Cigarette Smoking and CFH Y402H, LOC387715 A69S in PCV
Genotype Smoking Cases, n Controls, n OR (95% CI) P Adjusted OR* Adjusted P
CFH Y402H, Smoking†
    TT Never 119 429 1.00 (reference) 1.00 (reference)
    CT+CC Never 31 70 1.60 (1.00–2.55) 0.051 1.11 (0.64–1.93) 0.71
    TT Ever 177 313 2.04 (1.55–2.68) <0.0001 1.28 (0.86–1.91) 0.22
    CT+CC Ever 48 35 4.94 (3.06–7.99) <0.0001 3.30 (1.77–6.16) 0.0002
LOC387715 A69S, Smoking‡
    GG Never 37 198 1.00 (reference) 1.00 (reference)
    GT+TT Never 113 301 2.01 (1.33–3.03) 0.0009 1.92 (1.20–3.09) 0.007
    GG Ever 53 135 2.10 (1.31–3.37) 0.0021 1.30 (0.61–2.77) 0.49
    GT+TT Ever 172 213 4.32 (2.88–6.48) <0.0001 3.67 (2.03–6.64) <0.0001
We also assessed the interaction between CFH Y402H and LOC387715 A69S polymorphisms in the same way. The results showed no evidence of interaction between the two SNPs, with an SI of 0.94 (95% CI, 0.47–1.90). 
Discussion
The results of this study showed that CFH Y402H and LOC387715 A69S were both significantly associated with PCV. The average age of the population-based control group was significantly younger than that in the PCV group, which means that some of these young control subjects may develop PCV in the future. The case–control association analyses of these subjects tend to be statistically conservative, and our statistically significant positive results are acceptable. Although the association between LOC387715 A69S is consistent with the results of earlier studies, 19,21 23 the positive association between PCV and CFH Y402H polymorphism has not been reported and is not consistent with the results of earlier studies on PCV and CFH polymorphisms in Asian populations (Chinese 21 and Japanese 24 ). 
Although multiple factors could contribute to our success in detecting a risk of CFH Y402H, the fact that our sample size (375 cases and 847 control subjects) was larger than that of the other studies (72 cases and 93 control subjects 21 or 130 cases and 173 control subjects 24 ) appeared to be one of the reasons. Because the risk allele frequency of CFH Y402H is relatively low in the Asian populations (6.5% in our controls), the sample size in the studies appear to be more critical for the power to detect the risk. For example, our sample size had an 80% probability of detecting the association of a risk allele with an OR as low as 1.65 in a population with allele frequency of 0.05 in the HWE. When we performed subgroup analyses dividing cases and controls into 55 to 65, 65 to 75, and ≥75 years, the unconditional logistic regression analysis showed that the associated of LOC387715 A69S with PCV was statistically significant after the adjustment for the other factors, whereas the association of CFH Y402H with PCV was not statistically significant (data not shown). This result may be due to a reduction in sample size. Our positive finding could be validated by accumulating data from replication studies and combining them by meta-analysis. 
The ORs of CFH Y402H and LOC387715 A69S observed in this study were relatively lower than those reported in earlier studies with neovascular AMD. 10,11 We used the unconditional logistic regression mode, and the estimated ORs presented were those after adjustment for the other factors, including smoking status. In most of the earlier studies of neovascular AMD, no adjustment for smoking status or other SNPs was performed—perhaps an explanation for the difference. Another possible reason was the difference in ethnicity. All our cases and controls were Japanese. Another reason may be a genetic difference between PCV and exudative AMD; however, we include only typical PCV cases (see the Materials and Methods section), and we could not assess the difference between PCV and typical neovascular AMD. 
Our hospital-based study also showed for the first time that cigarette smoking was an environmental risk factor in PCV. The ever smokers had 1.45-fold higher odds of developing PCV than did the never smokers. PCV is clinically categorized as a subtype of AMD, and previous studies have repeatedly shown that smoking is a major risk factor for development and progression of AMD. 25,26 Several mechanisms have been suggested for the relationship between smoking and AMD—for example, promoting oxidative damage, 29 reducing choroidal blood flow, 30 and reducing macular pigments. 31 Although it is still unclear how smoking elevates the risk of PCV, our results suggest that AMD and PCV have a common pathway of development that can be promoted by cigarette smoking. 
Our results also suggest that the associations of PCV with CFH Y402H and LOC387715 were modified by cigarette smoking. Rothman's SI 27 indicated that the joint effect of CFH Y402H and smoking on PCV was significantly greater than the additive scale. These results suggest the presence of statistically significant interactions between CFH polymorphism and smoking on PCV. 27,28 The joint effect of LOC387715 A69S and smoking was also greater than the additive scale, with marginal significance. On the other hand, our evaluations did not support an interaction between CFH Y402H and LOC387715 A69S, which indicated that CFH Y402H and LOC387715 A69S are associated with PCV independently. A few studies showed significant interaction between CFH Y402H and cigarette smoking on AMD, 32,33 and biological studies supported the possibility of biological interaction between them. 34 37 Interactions between LOC387715/HTRA1 polymorphism and smoking and between CFH and LOC387715/HTRA1 polymorphisms on AMD have also been reported 33,38,39 ; however, all the interactions are still controversial. 15,16,40 51 Whether there are interactions between CFH polymorphism and cigarette smoking and between LOC387715/HTRA1 polymorphism and smoking on PCV is inconclusive. However, our results suggest that smokers have a higher risk of developing PCV than do nonsmokers, and the risk of smokers with the risk allele of CFH and/or LOC387715/HTRA1 is higher than that of smokers without them. 
Because our study was a hospital-based cross-sectional study and not a population-based longitudinal survey, there are some limitations. The selection bias due to case–control sampling is one of them. The self-reported questionnaire for smoking habit would have produced some selection and recall biases. Another limitation is the lack of information on the chronological relationship between smoking and the development of the disease. A long-term prospective study in large-scale genome cohorts for PCV with environmental surveys along with molecular confirming assays would be necessary for better understanding of their genetic–environmental etiology. 
In summary, we have shown that smoking status and CFH Y402H and LOC387715 A69S polymorphisms are all significantly associated with PCV in the Japanese population with a hospital-based, cross-sectional, case–control association study. The joint effect of smoking and CFH Y402H on PCV was significantly greater than the additive scale, which indicates an interaction of cigarette smoking and CFH polymorphism on PCV. 
Footnotes
 Supported in part by Grants-in-Aid for Scientific Research 19390442 and 27091294 from the Japan Society for the Promotion of Science, Tokyo, Japan, and by the Japanese National Society for the Prevention of Blindness.
Footnotes
 Disclosure: H. Nakanishi, None; K. Yamashiro, None; R. Yamada, None; N. Gotoh, None; H. Hayashi, None; I. Nakata, None; M. Saito, None; T. Iida, None; A. Oishi, None; Y. Kurimoto, None; K. Matsuo, None; K. Tajima, None; F. Matsuda, None; N. Yoshimura, None
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Table 1.
 
Characteristics of the Study Population and Results of the Statistical Analysis
Table 1.
 
Characteristics of the Study Population and Results of the Statistical Analysis
PCV (n = 375) Control (n = 847) Univariate P Unconditional Logistic Regression*
P OR (95% CI)
Age, mean ± SD 73.10 ± 7.04 65.47 ± 6.64 <2.0 × 10−16 <2.0 × 10−16 1.17 (1.15–1.20)
Sex
    Men 269 418 3.5 × 10−13 5.2 × 10−4 1.99 (1.35–2.93)
    Women 106 429
Smoking status
    Ever 225 348 9.9 × 10−10 0.049 1.45 (1.00–2.10)
    Never 150 499
Pack-years
    >Median (37.5) 123 154 0.0067‡
    ≤Median (37.5) 93 187
    Missing data 9 7
CFH Y402H
    CC 1 5 3.4 × 10−4 § 0.010 1.63 (1.12–2.36)‖
    CT 78 100
    TT 296 742
LOC387715 A69S
    TT 133 113 4.4 × 10−16 § 1.6 × 10−14 2.26 (1.83–2.78)‖
    GT 152 401
    GG 90 333
Table 2.
 
Interaction between Cigarette Smoking and CFH Y402H, LOC387715 A69S in PCV
Table 2.
 
Interaction between Cigarette Smoking and CFH Y402H, LOC387715 A69S in PCV
Genotype Smoking Cases, n Controls, n OR (95% CI) P Adjusted OR* Adjusted P
CFH Y402H, Smoking†
    TT Never 119 429 1.00 (reference) 1.00 (reference)
    CT+CC Never 31 70 1.60 (1.00–2.55) 0.051 1.11 (0.64–1.93) 0.71
    TT Ever 177 313 2.04 (1.55–2.68) <0.0001 1.28 (0.86–1.91) 0.22
    CT+CC Ever 48 35 4.94 (3.06–7.99) <0.0001 3.30 (1.77–6.16) 0.0002
LOC387715 A69S, Smoking‡
    GG Never 37 198 1.00 (reference) 1.00 (reference)
    GT+TT Never 113 301 2.01 (1.33–3.03) 0.0009 1.92 (1.20–3.09) 0.007
    GG Ever 53 135 2.10 (1.31–3.37) 0.0021 1.30 (0.61–2.77) 0.49
    GT+TT Ever 172 213 4.32 (2.88–6.48) <0.0001 3.67 (2.03–6.64) <0.0001
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