February 2017
Volume 58, Issue 2
Open Access
Genetics  |   February 2017
Identification of ANGPT2 as a New Gene for Neovascular Age-Related Macular Degeneration and Polypoidal Choroidal Vasculopathy in the Chinese and Japanese Populations
Author Affiliations & Notes
  • Li Ma
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
  • Marten E. Brelen
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
  • Motokazu Tsujikawa
    Department of Ophthalmology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
  • Haoyu Chen
    Shantou University/The Chinese University of Hong Kong Joint Shantou International Eye Center, Shantou, China
  • Wai Kit Chu
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
  • Timothy Y. Y. Lai
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
  • Danny S. C. Ng
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
  • Kaori Sayanagi
    Department of Ophthalmology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
  • Chicako Hara
    Department of Ophthalmology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
  • Noriyasu Hashida
    Department of Ophthalmology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
  • Vesta C. K. Chan
    Prince of Wales Hospital Eye Centre, Hong Kong, China
  • Pancy O. S. Tam
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
  • Alvin L. Young
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
    Prince of Wales Hospital Eye Centre, Hong Kong, China
  • Weiqi Chen
    Shantou University/The Chinese University of Hong Kong Joint Shantou International Eye Center, Shantou, China
  • Kohji Nishida
    Department of Ophthalmology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
  • Chi Pui Pang
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
    Shantou University/The Chinese University of Hong Kong Joint Shantou International Eye Center, Shantou, China
  • Li Jia Chen
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
    Shantou University/The Chinese University of Hong Kong Joint Shantou International Eye Center, Shantou, China
    Prince of Wales Hospital Eye Centre, Hong Kong, China
  • Correspondence: Li Jia Chen, Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon, Hong Kong, China; lijia_chen@cuhk.edu.hk
  • Footnotes
     LM, MEB, MT, and HC contributed equally to the work presented here and should therefore be regarded as equivalent authors.
Investigative Ophthalmology & Visual Science February 2017, Vol.58, 1076-1083. doi:10.1167/iovs.16-20575
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      Li Ma, Marten E. Brelen, Motokazu Tsujikawa, Haoyu Chen, Wai Kit Chu, Timothy Y. Y. Lai, Danny S. C. Ng, Kaori Sayanagi, Chicako Hara, Noriyasu Hashida, Vesta C. K. Chan, Pancy O. S. Tam, Alvin L. Young, Weiqi Chen, Kohji Nishida, Chi Pui Pang, Li Jia Chen; Identification of ANGPT2 as a New Gene for Neovascular Age-Related Macular Degeneration and Polypoidal Choroidal Vasculopathy in the Chinese and Japanese Populations. Invest. Ophthalmol. Vis. Sci. 2017;58(2):1076-1083. doi: 10.1167/iovs.16-20575.

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

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Abstract

Purpose: We determine the angiopoietin 2 (ANGPT2) gene as a new susceptibility gene for neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV).

Methods: A total of 34 haplotype-tagging single-nucleotide polymorphisms (SNPs) were first genotyped in an exploratory Hong Kong Chinese cohort. Suggestive SNPs were replicated in a Shantou Chinese cohort and an Osaka Japanese cohort, with a total of 2343 subjects. The SNP rs800292 in the complement factor H (CFH) gene was genotyped in all the subjects. Genetic association and gene–gene interaction were analyzed.

Results: In the Hong Kong cohort, four SNPs in ANGPT2 (rs13255574, rs4455855, rs13269021, and rs11775442) were nominally associated with nAMD and PCV. The four ANGPT2 SNPs showed the same trends of association in the Shantou and Osaka cohorts. Combining the data from the 3 study cohorts revealed that SNPs rs4455855 and rs13269021 achieved study-wise significance (P < 0.0016), conferring an approximately 1.3-fold of increased risk for nAMD and PCV. Interaction analysis revealed the CFH SNP rs800292 has a highly significant interaction with the ANGPT2 SNP rs13269021 in nAMD and PCV in the combined analysis. Subsequent stratification analysis confirmed the interaction.

Conclusions: This study reveals ANGPT2 as a new susceptibility gene for nAMD and PCV, and it may affect disease susceptibility in association with CFH. Thus, this report provides new insights into the genetic architecture of nAMD and PCV.

Age-related macular degeneration (AMD) is a leading cause of irreversible central vision loss in the elderly, especially in developed countries. Neovascular AMD (nAMD), a major form of advanced AMD characterized by choroidal neovascularization (CNV), accounts for the majority of severe visual loss in AMD patients. Polypoidal choroidal vasculopathy (PCV) is a macular disease characterized by polyp-like lesions in the choroidal vessels, which are best seen in indocyanine green angiography (ICGA).1 Polypoidal choroidal vasculopathy and nAMD have similarities in clinical manifestations. For example, they can cause submacular hemorrhage, exudation, and scarring, leading to central vision loss. Interestingly, CNV and PCV can present concurrently in approximately 3.23% of patients,2 suggesting that they may have a shared mechanism. However, while the prevalence of nAMD (approximately 0.46%) is similar between Caucasian and Asian populations,3 the prevalence of PCV is approximately 3-fold higher in Asians than in Caucasians,4 suggesting an ethnic background is related to the occurrence of PCV. Moreover, nAMD and PCV respond differently to anti-VEGF therapy,5 suggesting differences in their underlying pathophysiology. 
Both AMD and PCV are complex diseases resulting from the interaction of multiple genetic and environmental risk factors. Recent genome-wide association studies (GWAS) identified multiple polymorphisms in 34 genetic loci associated with AMD, including the complement factor H (CFH) and age-related maculopathy susceptibility 2 (ARMS2) genes.6,7 The majority of these genes also were associated with PCV. However, the effect sizes of some genes, for example ARMS2, varied between PCV and AMD.8 A recent exome sequencing study revealed association of the FGD6 gene with PCV but not nAMD.9 Thus, there are similarities and differences in the genetic components of AMD and PCV.610 
The angiopoietin/angiopoietin receptors cascade is an important signaling pathway in regulating angiogenesis.11 The ligand, angiopoietin 2 (Ang2), activates integrin β1 and leads to endothelial destabilization in vitro and in vivo.12 In addition, Ang2 is a competitive antagonist for Tie2 (TEK tyrosine kinase, endothelial) and enhances abnormal angiogenesis and destabilizes blood vessels.13 Moreover, impaired postnatal retinal angiogenesis was detected in the Ang-2–deficient mice, characterized by an incomplete and chaotic vascular plexus.14 Therefore, ANGPT2 appears as an excellent candidate gene for nAMD and PCV, which have abnormal angiogenesis in the choroid. Currently, however, the association of ANGPT2 with AMD and PCV is not known. Therefore, in the present study, we performed a haplotype-tagging SNP association analysis and gene–gene interaction analysis to determine the role of the ANGPT2 gene, individually and interactively, in the genetic architecture of nAMD and PCV. 
Materials and Methods
Study Participants
This study involved 2343 unrelated participants from 3 independent East Asian cohorts, including a Hong Kong Chinese cohort of 214 nAMD and 236 PCV patients, and 433 controls; a Shantou Chinese cohort of 189 nAMD and 187 PCV patients, and 531 controls; and an Osaka Japanese cohort of 192 nAMD and 204 PCV patients, and 157 controls. All Chinese participants are Han Chinese, recruited from the eye clinics of the Prince of Wales Hospital, the Hong Kong Eye Hospital, Hong Kong, and the Joint Shantou International Eye Center, Shantou, China. The Osaka Japanese cohort was recruited from the Department of Ophthalmology, Osaka University Graduate School of Medicine, Osaka, Japan. The study protocol was approved by the institutional Ethics Committee at the respective collaborating institutions. Written informed consent was obtained from each participant. The study procedures were performed in accordance with the tenets of the Declaration of Helsinki. 
All patients underwent complete ophthalmic examinations, including best-corrected visual acuity (BCVA) measurement, ocular tonometry, slit-lamp biomicroscopy, fundus photographs, fluorescein angiography (FA) and ICGA. Clinical diagnosis and classification of AMD followed the standardized Age-Related Eye Disease Study criteria.15 All AMD patients had nAMD in at least one eye. Polypoidal choroidal vasculopathy was diagnosed based on the presence of nodular polypoidal lesions as shown by ICGA.1618 Diagnosis of nAMD and PCV was distinguished by FA and ICGA. Patients with other causes of CNV, such as myopic CNV, or with CNV and PCV in the same or fellow eye, were excluded. 
Control subjects were recruited from patients seen in the ophthalmology clinics for unrelated eye condition. All control subjects also underwent complete ophthalmic investigations. They had no sign of macular degeneration. Also, they did not have any other major eye diseases, except for mild senile cataract or mild refractive errors. 
Single-Nucleotide Polymorphisms (SNPs) Selection and Genotyping
Haplotype-tagging SNPs in the ANGPT2 gene were selected from the HapMap Beijing Han Chinese (CHB) population, using the HapMap Genome Browser release #27 dataset (available in the public domain at http://hapmap.ncbi.nlm.nih.gov/). The tagger-pairwise method was applied, with an R square (r2) cutoff of 0.8 and a minor allele frequency (MAF) cutoff of 0.15. Totally, 34 SNPs were selected in ANGPT2. These tagging SNPs also covered the gene referring to the 1000 genomes reference panel (available in the public domain at http://browser.1000genomes.org/, accessed on December 3, 2016), except rs17553089. 
Genomic DNA from peripheral blood was extracted using a QIAamp Blood Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol. In this study, we adopted a two-stage strategy. In the first stage, all of the 34 SNPs were genotyped in the Hong Kong cohort, using TaqMan genotyping assays (Applied Biosystems, Foster City, CA, USA) with a Roche LightCycle 480 Real-Time PCR System (Roche Diagnostics; Basel, Switzerland), according to the manufacturer's instructions. In the second stage, six SNPs in ANGPT2 (rs2515487, rs2922869, rs13255574, rs4455855, rs13269021, and rs11775442) that showed a suggestive disease-association (P < 0.05) and a CFH SNP rs800292 that showed significant interaction with ANGPT2 in the Hong Kong cohort (see below) were genotyped in the Shantou and Osaka cohorts, using the same genotyping method. 
Statistical Analysis
Hardy-Weinberg equilibrium (HWE) of each SNP in the controls was assessed using the χ2 test in PLINK (v1.07; available in the public domain at http://pngu.mgh.harvard.edu/purcell/plink/).19 Allelic and genotypic distributions were compared by the χ2 test between cases and controls among different study cohorts. The odds ratio (OR) and 95% confidence intervals (CI) for each SNP were calculated. Logistic regression analysis was used to evaluate the genetic effects of the SNPs adjusted for age and sex. In this study, the SNP associations were first assessed in nAMD and PCV separately, and then in combined nAMD and PCV as we found no significant difference in the association profiles between nAMD and PCV. 
Pairwise gene–gene interaction analysis was performed using the epistasis option in PLINK between the 6 associated SNPs in ANGPT2 and our previously-reported AMD and PCV-associated SNPs, including CFH rs800292,20,21 ARMS2-HTRA1 rs11200638,22 SKIV2L rs429608,17 CETP rs3764261,18 ABCG1 rs57137919,18 C3 rs17030,23 and PGF rs2268615.24 A P value less than 0.0012 (0.05/42, where 42 is the pairs of interaction) defined a significantly statistical interaction. After identifying a significant interaction between ANGPT2 rs13269021 and CFH rs800292, the study subjects were stratified by using dominant and recessive models of the risk G allele of ANGPT2 rs13269021. We then performed the association analyses of CFH rs800292 with nAMD and PCV in different genotypic strata of ANGPT2 rs13269021 (i.e., [GG+TG] and TT; GG and [TG+TT]). The homogeneity of the ORs for CFH rs800292 in different strata of ANGPT2 rs13269021 was assessed using the Breslow-Day test. 
To combine the data from the 3 study cohorts, we adopted the Mantel-Haenszel χ2 test to obtain the combined ORs and 95% CIs for the 6 SNPs (rs2515487, rs2922869, rs13255574, rs4455855, rs13269021, and rs11775442) and the gene–gene interaction between ANGPT2 rs13269021 and CFH rs800292, using the fixed-effect (I2 ≤ 50%) or random-effect (I2 > 50%) model based on heterogeneity test results.25 The test was performed using Review Manager (RevMan, version 5.2; The Cochrane Collaboration, Copenhagen, Denmark). In this study, we adopted the Bonferroni method to correct the P values in multiple testing. A final P value of less than 0.0016 (0.05/31, where 31 was the number of SNPs included in data analysis) would be required to conclude a significant disease association. 
Results
Individual SNP Association and SNP*SNP Interaction in the Hong Kong Cohort
Supplementary Table S1 shows the characteristics of the participants in the 3 study cohorts. In the Hong Kong exploratory cohort, the genotype call rates of all SNPs were 97.5%. Three SNPs (rs4478599, rs2442604, and rs17077317) in ANGPT2 showed deviation from HWE in controls and were excluded from further analysis. In the remaining 31 SNPs (Supplementary Table S2), four SNPs, rs13255574 (nAMD: P = 3.9 × 10–3; OR = 1.53; 95% CI, 1.15–2.04; PCV: P = 4.7 × 10–4; OR = 1.69; 95% CI, 1.26–2.28), rs4455855 (nAMD: P = 0.020; OR = 1.34; 95% CI, 1.05–1.72; PCV: P = 4.3 × 10–3; OR = 1.43; 95% CI, 1.12–1.82), rs13269021 (nAMD: P = 0.020; OR = 1.32; 95% CI, 1.05–1.66; PCV: P = 2.6 × 10–3; OR = 1.43; 95% CI, 1.13–1.81), and rs11775442 (nAMD: P = 0.016; OR = 1.43; 95% CI, 1.0–1.92; PCV: P = 0.044; OR = 1.34; 95% CI, 1.01–1.79) were associated with nAMD and PCV, while rs2515487 (P = 4.6 × 10–3; OR = 1.45; 95% CI, 1.12–1.88) and rs2922869 (P = 5.4 × 10–3; OR = 1.43; 95% CI, 1.11–1.85) were associated with PCV only (Table 1). Moreover, these 6 SNPs were associated with combined nAMD and PCV (Table 1). Among them, rs13255574 (P = 1 × 10–4; OR = 1.59; 95% CI, 1.26–2.01) and rs13269021 (P = 1.2 × 10–3; OR = 1.37; 95% CI, 1.13–1.66) had the strongest association, which could withstand Bonferroni correction (P < 0.0016). 
Table 1
 
Associated SNPs in ANGPT2 and CFH in nAMD and PCV Adjusted for Age and Sex
Table 1
 
Associated SNPs in ANGPT2 and CFH in nAMD and PCV Adjusted for Age and Sex
In epistatic analysis, a significant interaction was detected between ANGPT2 rs13269021 and CFH rs800292 in nAMD (P = 7.3 × 10–4). No significant interaction was detected for the remaining SNPs in ANGPT2, ARMS2-HTRA1 rs11200638, SKIV2L rs429608, CETP rs3764261, ABCG1 rs57137919, C3 rs17030, and PGF rs2268615. 
Replication Study and Combined Analysis
The 6 ANGPT2 SNPs, rs2515487, rs2922869, rs13255574, rs4455855, rs13269021, and rs11775442, followed HWE in the control groups of the Shantou Chinese and Osaka Japanese cohorts. In the Shantou cohort, the ORs of the 6 SNPs for nAMD, PCV, and combined nAMD and PCV were toward the same trends as in the Hong Kong cohort, although the associations did not reach statistical significance (Table 1). In the Osaka cohort, SNP rs13269021 showed a nominal association with nAMD (P = 0.025; OR = 1.59; 95% CI, 1.06–2.37; Table 1). 
In the combined analysis of the Hong Kong, Shantou, and Osaka samples by Mantel-Haenszel χ2 test, two SNPs, rs4455855 (nAMD: P = 1.15 × 10–3; OR = 1.31; 95% CI, 1.11–1.55; I2 = 0; PCV: P = 1.24 × 10–3; OR = 1.30; 95% CI, 1.11–1.53; I2 = 0; combined nAMD and PCV: P = 1.28 × 10–4; OR = 1.30; 95% CI, 1.14–1.49; I2 = 0), and rs13269021 (nAMD: P = 6.74 × 10–4; OR = 1.31; 95% CI, 1.12–1.53; I2 = 0; PCV: P = 1.15 × 10–3; OR = 1.30; 95% CI, 1.11–1.52; I2 = 0; combined nAMD and PCV: P = 8.49 × 10–5; OR = 1.29; 95% CI, 1.14–1.47; I2 = 0), showed a statistically significant association with nAMD, PCV, and combined nAMD and PCV (P < 0.0016; Table 2; Supplementary Figs. S1, S2). 
Table 2
 
Combined Analysis of Associated ANGPT2 SNPs in nAMD and PCV Adjusted for Age and Sex
Table 2
 
Combined Analysis of Associated ANGPT2 SNPs in nAMD and PCV Adjusted for Age and Sex
Gene–Gene Interaction and Combined Analysis
In the Hong Kong cohort, a significant SNP–SNP interaction was detected between ANGPT2 rs13269021 and CFH rs800292 in nAMD (P = 7.3 × 10–4). However, this interaction was not significant in the Shantou or Osaka cohort alone by using logistic regression analysis. We then performed stratification analyses to elaborate the statistical interaction. We first assessed the associations of CFH rs800292 with nAMD and PCV in subjects who carried at least one risk allele (i.e., the GG or TG genotype) of ANGPT2 rs13269021 versus subjects who carried only the nonrisk TT genotype (i.e., in a dominant model of ANGPT2 rs13269021). In subjects carrying the rs13269021 GG/TG genotypes, the CFH rs800292 conferred a significantly increased risk to nAMD and PCV in the allelic (nAMD: P = 5.2 × 10–5; OR = 1.80; 95% CI, 1.35–2.40; PCV: P = 2.2 × 10–5; OR = 1.81; 95% CI, 1.38–2.39), dominant (nAMD: P = 1.05 × 10–4; OR = 4.14; 95% CI, 1.92–8.91; PCV: P = 4.5 × 10–5, OR = 4.14; 95% CI, 2.00–8.59), and recessive (nAMD: P = 4 × 10–3; OR = 1.73; 95% CI, 1.19–2.50; PCV: P = 2 × 10–3; OR = 1.74; 95% CI, 1.22–2.49; Table 3) models. In contrast, in subjects with the rs13269021 wild-type (TT) genotype, no significant association of CFH rs800292 with nAMD or PCV was detected (Table 3). Moreover, the ORs for the CFH rs800292 in the allelic (nAMD, P = 5.0 × 10–4; PCV, 1.2 × 10–5; Breslow-Day test), dominant (nAMD, P = 0.015; PCV, P = 1.1 × 10–4), and recessive (nAMD, P = 2 × 10–3; PCV, 5.9 × 10–4) models were significantly different between the ANGPT2 rs13269021 GG/TG and TT genotypic strata (Table 3). Thus, results of the stratification analyses confirmed the gene–gene interaction identified by logistic regression. 
Table 3
 
Associations of CFH rs800292 With nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
Table 3
 
Associations of CFH rs800292 With nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
The CFH rs800292 was significantly associated with nAMD and PCV in all 3 study cohorts (Table 1). In stratification analysis of the Shantou and Osaka cohorts, the CFH rs800292 G allele was associated with nAMD and PCV in subjects carrying the ANGPT2 rs13269021 GG/TG genotypes but not in those with the TT genotypes. This was consistent in all 3 study cohorts (Table 3). In the combined analysis, the CFH rs800292, in the allelic, dominant, and recessive models, showed significant associations with nAMD and PCV in the ANGPT2 rs13269021 GG/TG genotypes but not in the TT genotype (Table 4; Supplementary Figs. S3, S4). 
Table 4
 
Combined Analysis of CFH rs800292 in nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
Table 4
 
Combined Analysis of CFH rs800292 in nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
When stratified by the dominant model of CFH rs800292, the associations of ANGPT2 rs13269021 with nAMD and PCV appeared inconsistent among different cohorts (Supplementary Table S3), likely due to the small sample sizes in certain strata. However, the combined analysis of Hong Kong, Shantou, and Osaka data revealed that the G allele of ANGPT2 rs13269021 was significantly associated with nAMD (P = 4.31 × 10–5; OR = 1.38) and PCV (P = 1 × 10–3; OR = 1.29) in subjects carrying the CFH rs800292 GG/AG genotypes, but not in those with the AA genotype (P = 0.25; OR = 0.53 for nAMD and P = 0.49; OR = 0.87 for PCV; Supplementary Table S4). 
We then assessed the associations of CFH rs800292 with nAMD and PCV in subjects who carried only the risk allele (i.e., the GG genotype) of ANGPT2 rs13269021 versus subjects who carried the GT or TT genotype (i.e., in a recessive model of ANGPT2 rs13269021). The ORs were variable across different study cohorts (Supplementary Table S5), likely due to small sample effect. However, in the combined analysis of the 3 cohorts, the ORs for CFH rs800292 (in any genetic models) in the stratum of ANGPT2 rs13269021-GG were consistently higher than the ORs in the ANGPT2 rs13269021-(TT+TG) stratum (Supplementary Table S6). Similarly, when stratified by CFH rs800292 in the recessive model, the association patterns of ANGPT2 rs13269021 with nAMD and PCV were variable across different cohorts (Supplementary Table S7). However, again, in the combined analysis the ORs for ANGPT2 rs13269021 (in any genetic models) in the stratum of CFH rs800292-GG were consistently higher than the ORs in the CFH rs800292-(AA+AG) stratum (Supplementary Table S8). 
In addition, we performed stratification analyses in additive effect models in the three cohorts. However, no consistent association pattern was observed in individual cohorts or the combined analysis, likely due to the small sample sizes after stratification (data not shown). 
Discussion
In this study, we identified 2 haplotype-tagging SNPs, rs4455855 and rs13269021, in the ANGPT2 gene to be significantly associated with nAMD and PCV in a combined group of subjects from China and Japan. We also confirmed the association of CFH rs800292 with nAMD and PCV. In addition, we identified a significant interaction between ANGPT2 rs13269021 and CFH rs800292 in nAMD and PCV. In stratification analysis, CFH rs800292 was associated with nAMD and PCV in subjects carrying the ANGPT2 rs13269021 GG/TG genotypes but not in those with the TT genotypes. These findings have not been reported before to our knowledge. Thus, our study indicates ANGPT2 to be a new susceptibility gene for nAMD and PCV, and it may affect disease susceptibility in association with CFH
In a previous study, a tagging SNP rs2442598 of the ANGPT2 gene was associated with psoriasis vulgaris.26 Another SNP rs3739391 in the ANGPT2 promoter region had been associated with elevated angiopoietin-2 levels in the blood circulation.27 In this present study, neither rs2442598 nor rs3739391 was associated with nAMD or PCV. Instead, two tagging SNPs, rs4455855 and rs13269021, located in intron 1 of ANGPT2, conferred an increased risk for nAMD and PCV. These two associated SNPs also are located in intronic regions of the MCPH1 gene. Disorganized and degenerated retinal layers had been found in MCPH1 knock-out mice,28 suggesting a role of the MCPH1 in normal structuring of the retina. These SNPs could be correlated with the expression level of Ang2, having a regulatory role, or in linkage disequilibrium with exonic variants. Whether the SNPs found in our study are correlated with the expression levels of Ang2 remains to be investigated. 
The ANGPT2 gene, spanning a 63.61 kb region on chromosome 8, encodes the angiopoietin 2 (Ang2) protein, which is an antagonist of angiopoietin 1.13 It is a key regulator in angiogenesis and vascular maturation.29 Angiopoietin 2 usually is not expressed in healthy adult tissues and its secretion is induced at sites of inflammation and vascular remodeling.30 Moreover, the mRNA levels of Ang2 are regulated by multiple factors, including VEGF, hypoxia, and TNFα.29 Angiopoietin 2 is immunodetectable in the choroidal neovascular membranes and highly expressed in the vascular enrichment areas where VEGF is colocalized.31 Angiopoietin 2 also is expressed in surgically excised CNV membranes from neovascular AMD patients.31,32 Therefore, the Ang2 protein could have a role in the pathogenesis of nAMD and PCV. Recently, in a whole exome sequencing study, by using a gene-based mutational load analysis, we and coworkers found that ANGPT2 was nominally associated with AMD (P = 9.85 × 10−3) in the East Asian populations.33 Our current finding that the ANGPT2 gene is associated with nAMD and PCV provides further evidence to support the pathogenic role of Ang2. 
The expression of Ang2 in the vitreous was significantly increased in nAMD patients versus controls.34 Therefore, an overexpression of ANGPT2 is likely implicated in the neovascularization of AMD. Anti-VEGF therapy is a current treatment for nAMD and PCV. However, approximately 10% of nAMD patients are resistant to anti-VEGF treatment.35,36 New and effective therapeutic agents are needed. Angiopoietin 2, which has a role in angiogenesis, appears to be an excellent new treatment target. Recently, AMG386, a selective Ang1/2 neutralizing peptibody, was found to inhibit the neovascular processes in laser-induced CNV in monkeys.37 A two-in-one VEGF/Ang2 antibody with dual action Fab (DAF) was developed as a potential treatment for nAMD, which enhanced the efficacy compared to monospecific antibody.38 Therefore, while anti-Ang2 is likely to become a new treatment modality for human nAMD and PCV, the use of combined anti-VEGF and anti-Ang2 therapy would be expected to provide better efficacy. The ANGPT2 gene could be a biomarker for pharmacogenetics studies on treatment responses in patients with different genotypes. 
In this study, we have, for the first time to our knowledge, identified a significant interaction between ANGPT2 rs13269021 and CFH rs800292 in nAMD and PCV. In stratification analysis, the CFH rs800292 G allele was associated with nAMD and PCV in subjects carrying the ANGPT2 rs13269021 GG/TG genotypes but not in those with the TT genotypes. Notably, elevated Ang2 plasma levels have been found to correlate with the activation of the complement pathway in severe trauma patients, particularly in the alternative cascade.39 An elevated placental C5a level also has been found to be positively associated with Ang2.40 In addition, TNF-α, an inflammatory mediator, increased the mRNA and protein levels of Ang2 in cultured choroidal endothelial cells from surgically excised CNV membranes.41 There is a bispecific antibody simultaneously targeting TNF-α and Ang2 available, which reduced the clinical symptoms and histologic scores in a murine inflammatory arthritis model.42 On the other hand, Ang2 overexpression specifically in endothelial cells promoted inflammation responses, such as leukocyte infiltration in multiple organs, including liver, kidney, lung, and intestine.43 Thus, our finding of the statistical interaction between ANGPT2 and CFH suggested that genes in the angiopoietin pathway and complement cascade are interactive in the pathogenesis of nAMD and PCV. The exact mechanism of how these two pathways interact at the protein level remains to be elucidated. 
In this study, we identified a new putative gene, ANGPT2, for nAMD and PCV by a candidate gene approach. In the exploratory stage, there were 6 SNPs in ANGPT2 showing a suggestive association with P values < 0.05 and were subjected to replication. However, only the P values for SNP rs13255574 in PCV (P = 4.7 × 10−4), and SNPs rs13255574 (P = 1 × 10−4) and rs13269021 (P = 1.2 × 10−3) in combined nAMD and PCV could withstand the Bonferroni correction (P < 0.0016). In the replication study, two SNPs (rs4455855 and rs13269021) showed the same trend of effect in 2 independent replication cohorts from Shantou and Osaka, while in the combined analysis their P values achieved the study-wise significance level for nAMD, PCV, and combined nAMD and PCV (all P < 0.0016), with no intercohort heterogeneities (I2 = 0). Therefore, the results of this study are robust. In this study, we included one Japanese cohort recruited in Osaka. The SNP rs13269021 showed a nominal association with nAMD (P = 0.025; OR = 1.59). In PCV, it showed the same trend of effect (OR = 1.21) though the P value was not statistically significant. Therefore, despite there was very low intercohort heterogeneity in the combined analysis (I2 = 0), further independent replication in the Japanese population should be warranted. Of note, ANGPT2 has not been reported in previous GWAS but in a whole exome sequencing study as mentioned above. Therefore, whether the association of ANGPT2 with AMD and PCV is population-specific should be evaluated in further replication studies in other ethnic groups. 
After the identification of the significant interaction between ANGPT2 rs13269021 and CFH rs800292, we performed stratification analyses to evaluate the effects of each of these two SNPs in different genotypic strata (dominant and recessive models) of the other SNP. The ORs and P values appeared variable in individual cohorts. This is likely due to the loss of statistical power after stratification. Interestingly, however, when we combined the data from the 3 cohorts using meta-analysis, we found that the ORs for AMD and PCV were consistently higher in the upper strata (i.e., subjects who carry at least one risk allele of either the ANGPT2 rs13269021 or CFH rs800292 SNP; Table 4; Supplementary Tables S4, S6, S8). This indicated that subjects carrying the risk alleles of ANGPT2 rs13269021 and CFH rs800292 could have a higher risk of AMD and PCV development. Further replications in large samples are warranted to confirm the interaction between ANGPT2 and CFH
In conclusion, we identified 2 haplotype-tagging SNPs rs4455855 and rs13269021 in ANGPT2 as new susceptibility markers for nAMD and PCV. We also identified an interaction between ANGPT2 rs13269021 and CFH rs800292 in nAMD and PCV, indicating that ANGPT2 may have a role in the genetic mechanism of nAMD and PCV in association with CFH. This report provided new insights into the genetic architecture of nAMD and PCV. 
Acknowledgments
Supported in part by the National Natural Science Foundation of China (81500764 [LJC]), a research grant from the General Research Fund, Hong Kong (14120516 [LJC]), and the Direct Grants of the Chinese University of Hong Kong, Hong Kong (4054281 [LJC] and 4054119 [CPP]). 
Disclosure: L. Ma, None; M.E. Brelen, None; M. Tsujikawa, None; H. Chen, None; W.K. Chu, None; T.Y.Y. Lai, None; D.S.C. Ng, None; K. Sayanagi, None; C. Hara, None; N. Hashida, None; V.C.K. Chan, None; P.O.S. Tam, None; A.L. Young, None; W. Chen, None; K. Nishida, None; C.P. Pang, None; L.J. Chen, None 
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Table 1
 
Associated SNPs in ANGPT2 and CFH in nAMD and PCV Adjusted for Age and Sex
Table 1
 
Associated SNPs in ANGPT2 and CFH in nAMD and PCV Adjusted for Age and Sex
Table 2
 
Combined Analysis of Associated ANGPT2 SNPs in nAMD and PCV Adjusted for Age and Sex
Table 2
 
Combined Analysis of Associated ANGPT2 SNPs in nAMD and PCV Adjusted for Age and Sex
Table 3
 
Associations of CFH rs800292 With nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
Table 3
 
Associations of CFH rs800292 With nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
Table 4
 
Combined Analysis of CFH rs800292 in nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
Table 4
 
Combined Analysis of CFH rs800292 in nAMD and PCV Stratified by ANGPT2 rs13269021 in the Dominant Model
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