May 2011
Volume 52, Issue 6
Free
Genetics  |   May 2011
Copy Number Variations in Candidate Genes in Neovascular Age-Related Macular Degeneration
Author Affiliations & Notes
  • Melissa M. Liu
    From the Laboratory of Immunology and
    the Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Elvira Agrón
    the Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland; and
  • Emily Chew
    the Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland; and
  • Catherine Meyerle
    the Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland; and
  • Frederick L. Ferris, III
    the Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland; and
  • Chi-Chao Chan
    From the Laboratory of Immunology and
  • Jingsheng Tuo
    From the Laboratory of Immunology and
  • Corresponding author: Jingsheng Tuo, 10/10N103, 10 Center Drive, Bethesda, MD 20892-1857; tuoj@nei.nih.gov
Investigative Ophthalmology & Visual Science May 2011, Vol.52, 3129-3135. doi:10.1167/iovs.10-6735
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Melissa M. Liu, Elvira Agrón, Emily Chew, Catherine Meyerle, Frederick L. Ferris, Chi-Chao Chan, Jingsheng Tuo; Copy Number Variations in Candidate Genes in Neovascular Age-Related Macular Degeneration. Invest. Ophthalmol. Vis. Sci. 2011;52(6):3129-3135. doi: 10.1167/iovs.10-6735.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose.: The pathogenesis of age-related macular degeneration (AMD) is strongly influenced by genetic factors, and single nucleotide polymorphisms have been consistently linked to AMD. Copy number variation (CNV), or variation in the number of copies of a particular segment of DNA, may also contribute to AMD pathogenesis. This study evaluated CNVs in candidate genes that have been reported to be linked to AMD.

Methods.: Study participants were 131 patients with neovascular AMD and 103 elderly persons without AMD who were evaluated by retinal specialists at the National Eye Institute. DNA was collected from peripheral whole blood, and duplex RT-PCR based copy number (CN) assays were performed for the genes CCR3, CFH, CX3CR1, ERCC6, HTRA1, and VEGF. Quantitative CNs (CN = 0, 1, 2, or 3+) were determined.

Results.: Novel CNVs were discovered in CCR3, CX3CR1, and ERCC6. The unadjusted data suggested that CN = 3+ for CX3CR1 might be mildly protective against AMD, but this trend did not persist after adjustment for age. AMD patients appeared to have an elevated mean CFH CN relative to controls (2.13 [95% confidence interval (CI), 2.05–2.21] vs. 2.01 [95% CI, 1.92–2.09 copies]; P = 0.05). No significant associations between CNV and AMD were observed for the remaining genes.

Conclusions.: The methods described are suitable for quantitative characterization of CNV in candidate genes. The authors identified CNVs in AMD-associated genes but did not find strong evidence for a link with neovascular AMD.

Age-related macular degeneration (AMD) is the leading cause of blindness among the elderly in the developed world. 1 AMD is characterized by the formation of drusen in Bruch's membrane, the degeneration of photoreceptors and the underlying retinal pigment epithelium in the macula, geographic atrophy, and choroidal neovascularization. It is widely accepted that there is a complex involvement of both genetic and environmental factors in the pathogenesis of AMD. Studies have identified myriad AMD-associated genes in mechanistic pathways related to complement system activation, inflammation, microglial recruitment, DNA repair, extracellular matrix function, and neovascularization. 2  
Much of the previous work on genetic factors influencing AMD has focused on single nucleotide polymorphisms (SNPs). Although highly significant statistical associations have been discovered between various SNPs and AMD, they do not account for the entire genetic component of the disease. Moreover, it remains to be elucidated whether the identified SNPs are causally linked to aberrant gene function or whether they are simply genetic markers. Copy number variation (CNV) is another type of genetic structural variation that has been recognized as a substantial source of phenotypic variation in human populations. 3  
CNVs include deletions, duplications, and tandem repeats of segments of genomic DNA that are at least 1 kilobase long. 3 Population-based studies have identified thousands of CNV loci throughout the human genome. 4,5 There are a number of proposed mechanisms, including gene dosage, gene interruption, gene fusion, and positional effects, potentially linking CNV to aberrant gene function or regulation and subsequently disease. 6 In fact, CNVs in specific genes have been linked to a variety of diseases, including systemic lupus erythematosus, Crohn's disease, and several neuropsychiatric disorders. 7 CNVs in two glutathione S-transferases, GSTM1 and GSTT1, have also been linked to cancer susceptibility, asthma, and cataract. 8,9  
Although CNV contributes to human genetic diversity, its role in AMD pathogenesis has only been superficially evaluated. A recently reported genome-wide association study of CNV in AMD identified no significant CNV loci associated with AMD risk. 10 It has been reported, however, that deletions in CFH-related proteins 1 and 3 (CFHR1 and CFHR3) are protective against AMD. 11 13 Nevertheless, the role of CNV is unknown for the most highly associated AMD genes. There is precedence for discovering that a CNV is causally linked to disease after having first identified an associated SNP in the same gene, as has been demonstrated for the α-synuclein gene and Parkinson's disease. 14,15 There is also evidence for linkage disequilibrium between CNVs and SNPs in the human genome. 16 To characterize the role of CNV as a potential contributor to the genetic component of AMD, this study performed quantitative copy number genotyping for highly associated AMD genes in patients with neovascular AMD and elderly controls. Novel CNVs were discovered in three genes, but no definitive associations between CNVs in the selected genes and AMD were observed. 
Materials and Methods
This research adhered to the tenets of the Declaration of Helsinki. Each participant provided signed informed consent in accordance with protocols for human subject recruitment and clinical evaluation approved by the Institutional Review and Ethics Boards of the National Eye Institute. 
Study Population
Study participants were 131 patients with neovascular AMD and 103 controls from the greater Washington, DC, area. All participants were self-identified as Caucasians of non-Hispanic descent (Table 1). All participants were clinically evaluated by retinal specialists at the National Eye Institute. AMD status was determined by independent grading of funduscopic photographs using the AREDS scoring criteria. 17 All control subjects had either no drusen or fewer than 15 small (<63 μm) drusen, no significant extramacular drusen, and no evidence of AMD-related pigment abnormalities. Subjects with significant signs of any other retinal diseases involving the photoreceptors or outer retinal layers other than AMD—including high myopia, retinal dystrophies, central serous retinopathy, vein occlusion, diabetic retinopathy, and uveitis, or similar outer retinal diseases—were excluded from the control group. All patients with neovascular AMD had choroidal neovascularization characterized by edema, blood, or fibrovascular or fibrous tissue beneath the retinal pigment epithelium or sensory retina. The diagnosis of neovascular AMD was often confirmed by fluorescein angiography and optical coherence tomography. Patients were also assessed by indocyanine green angiography to exclude polypoidal choroidal vasculopathy. Subjects with non-AMD retinal diseases that developed before the age of 50 were excluded from the neovascular AMD group. 
Table 1.
 
Demographic and Clinical Information for Study Participants
Table 1.
 
Demographic and Clinical Information for Study Participants
Control (n = 103) Neovascular AMD (n = 131) P
Age, y 69.6 ± 9.8 79.4 ± 8.3 <0.0001*
Female 61 (59.22) 63 (48.09) 0.09
Past smoker 52 (50.49) 67 (51.15) 0.92
Current smoker 3 (2.91) 10 (7.63) 0.12
Cataract 41 (39.81) 88 (67.18) <0.0001*
Ocular inflammation 2 (1.94) 0 (0) 0.11
Glaucoma 5 (4.85) 8 (6.11) 0.68
Corneal disease 2 (1.94) 1 (0.76) 0.43
Optic nerve disease 2 (1.94) 3 (2.29) 0.85
Non-AMD retinal disease 0 (0) 10 (7.63) 0.0042*
Cardiovascular disease 45 (43.69) 93 (70.99) <0.0001*
Alzheimer's disease 0 (0) 2 (1.53) 0.21
Genomic DNA Preparation
Peripheral whole blood was collected from all study participants for genomic DNA extraction (QIAamp DNA Blood Maxi Kit; Qiagen, Valencia, CA). DNA was quantified first by UV absorption (Beckman DU 640 Spectrophotometer; Beckman Coulter, Brea, CA) and then by RT-PCR amplification of RNase P RNA component H1 (RNase P), with standard DNA as a calibrator, using reagents (TaqMan RNase P Detection; Applied Biosystems, Foster City, CA). DNA concentrations were equalized before copy number genotyping of candidate genes. 
Copy Number Genotyping
Copy number genotyping was performed using duplex RT-PCR–based copy number analysis (TaqMan Copy Number Assays; Applied Biosystems) for six AMD-associated genes (Table 2): chemokine (C-C) motif receptor 3 (CCR3), complement factor H (CFH), chemokine (C-X3-C) receptor 1 (CX3CR1), excision repair cross-complementing rodent repair deficiency, complementation group 6 (ERCC6), HtrA serine peptidase 1 (HTRA1), and vascular endothelial growth factor (VEGF) (Applied Biosystems). Standard curves were generated using twofold serial dilutions of genomic DNA to determine the RT-PCR amplification efficiency for each assay. Efficiency (E) was calculated using the equation E = 10(−1/m) − 1, where m is the slope of the standard curve, plotting cycle threshold (Ct) against DNA quantity (log concentration). Copy number analysis (TaqMan Copy Number Assays; Applied Biosystems) was also performed for GSTM1 and GSTT1, two genes for which CNVs have been well documented. Analyses were initially performed on a subset of 88 cases and 80 controls before determining whether further characterization using all study samples was merited. Unadjusted statistical analyses comparing CNV frequencies in cases and controls showed no significant differences for any of the genes except CX3CR1, which showed a borderline association. As a result, CNV genotyping was performed using all 131 patients and 103 controls for CX3CR1 only. Copy number analysis (TaqMan Copy Number Assays; Applied Biosystems) was also performed for AR (androgen receptor), an X-linked gene, on a subset of 25 patients as well. For each 10-μL single-well reaction using 10 ng genomic DNA and 1× TaqMan Universal PCR Master Mix without AmpErase UNG, a 1× TaqMan Copy Number Assay, which contained forward primer, reverse primer, and FAM dye-labeled MGB probe specific for the gene of interest, was run simultaneously with a 1× TaqMan Copy Number Reference Assay, which contained forward primer, reverse primer, and a VIC dye-labeled TAMRA probe specific for RNase P according to the manufacturer's instructions. Primers and probes were selected for each gene of interest (ABI GeneAssist Copy Number Assay Workflow Builder; Applied Biosystems). 18 When possible, assays targeting regions of previously reported CNV were selected. 
Table 2.
 
Copy Number Assay Information
Table 2.
 
Copy Number Assay Information
Gene Assay ID* Assay Location (NCBI build 37) Assay Cytoband Assay Gene Location
CCR3 Hs00751151_cn chr3:46283769 3p21.31h Exon 1
CFH Hs00116895_cn chr1:196621254 1q31.3c Exon 1
CX3CR1 Hs02139194_cn chr3:39305135 3p26.3c Exon 5
ERCC6 Hs01920803_cn chr10:50681068 10q11.23a Intron 14-Exon 15
HTRA1 Hs03730183_cn chr10:124264488 10q26.13b Intron 3
VEGF Hs00609007_cn chr6:43738068 6p21.1d Exon 1
GSTM1 Hs00273142_cn chr1:110230461 1p13.3b Exon 1
GSTT1 Hs00767125_cn chr22:24376147 22q11.23b Exon 5
AR Custom design† Xq11.2 Exon 1
PCR was performed in 96-well plates using a PCR system (7500 Real-Time PCR System; Applied Biosystems). Thermal cycling conditions were as described in the manufacturer's instructions. Data were collected (Absolute Quantification Method, 7500 System SDS Software version 1.3.1; Applied Biosystems), and samples were assayed using triplicate wells for each gene of interest. Copy numbers were estimated (CopyCaller Software version 1.0; Applied Biosystems) using the ΔΔCt relative quantification method. A maximum likelihood algorithm was used to estimate the mean ΔCt expected for copy number 1 (CN = 1) based on the probability density distribution across all samples, and this parameter was used in subsequent copy number calculations for each given gene. This analytical method was used to calculate the relative copy number of a target gene normalized to RNase P, a reference of known copy number (CN = 2), without the use of a calibrator sample for each target gene. The copy number assays were repeated on a subset of samples for each gene to determine reproducibility. In the event of a discrepancy in the copy number call between two duplicate assays, the call with the higher calculated statistical confidence was used for data analysis. 
Statistical Analysis
Logistic regression, without adjustment for any confounding factors, and t-test were used to compare the frequencies of each copy number category (CN = 0, 1, 2, or 3+) and the mean number of copies of each gene, respectively, between patients with neovascular AMD and controls. Age-adjusted logistic regression and analysis of covariance were also performed to evaluate the same parameters. All statistical analyses were performed using statistical software (SAS version 9.2; SAS Institute Inc., Cary, NC). Logistic regression compared the odds of AMD among the various copy number levels. Analysis of covariance performed comparisons of the mean copy numbers while taking into account both categorical and continuous covariates. All tests were performed as two-tailed analyses, and statistical significance was nominally set at P = 0.05, recognizing that there was no adjustment for multiple comparisons. 
Results
Evaluation of Quantitative Copy Number Determination Methods
Standard curves for the candidate gene-specific copy number assays (TaqMan; Applied Biosystems) showed that the RT-PCR amplification efficiencies were similar between each gene of interest and the internal control RNase P, a gene of known copy number (Fig. 1). Amplification efficiencies were calculated to be between 96% and 105% for all genes, and the differences between the slopes of the standard curves for each gene and RNase P were <7% for all assays. Consistent amplification of the internal control RNase P (VIC-labeled) confirmed that equal amounts of genomic DNA were being introduced in each assay, and differences in the amplification of the gene of interest (FAM-labeled) relative to RNase P were able to discriminate quantitative copy numbers (Fig. 2). Copy number assays, which included triplicate single-well analyses, were repeated on 7% of samples for each gene to determine reproducibility. The copy number calls were consistent in >97% of patients. Copy number assays for AR were also performed as an additional evaluation of the methodology for a subset of patients. With 100% accuracy, male and female subjects were determined to have CN = 1 and CN = 2, respectively (Fig. 3). 
Figure 1.
 
RT-PCR amplification efficiency of copy number assays. Standard curves for the RT-PCR amplification efficiency of each assay were generated by plotting Ct against DNA quantity (log concentration) for the gene of interest and the RNase P internal control. (A) CCR3; (B) ERCC6; (C) CFH; (D) HTRA1; (E) CX3CR1; (F) VEGF. Five twofold serial dilutions were performed in duplicate for each gene. Calculated efficiencies were close to 100% and were similar between each gene of interest and RNase P.
Figure 1.
 
RT-PCR amplification efficiency of copy number assays. Standard curves for the RT-PCR amplification efficiency of each assay were generated by plotting Ct against DNA quantity (log concentration) for the gene of interest and the RNase P internal control. (A) CCR3; (B) ERCC6; (C) CFH; (D) HTRA1; (E) CX3CR1; (F) VEGF. Five twofold serial dilutions were performed in duplicate for each gene. Calculated efficiencies were close to 100% and were similar between each gene of interest and RNase P.
Figure 2.
 
Representative amplification plots for quantitative copy number determination. Quantitative copy numbers were determined using differences in the amplification of the gene of interest (FAM-labeled) relative to the RNase P internal control of known copy number (VIC-labeled). Representative data show amplification plots for participants of CN = 1, CN = 2, and CN = 3 for CX3CR1.
Figure 2.
 
Representative amplification plots for quantitative copy number determination. Quantitative copy numbers were determined using differences in the amplification of the gene of interest (FAM-labeled) relative to the RNase P internal control of known copy number (VIC-labeled). Representative data show amplification plots for participants of CN = 1, CN = 2, and CN = 3 for CX3CR1.
Figure 3.
 
Quantitative copy number genotyping for AR. Calculated AR copy number is plotted for each of 25 participants, with range bars indicating the minimum and maximum copy numbers calculated in the triplicate analysis. M, male; F, female.
Figure 3.
 
Quantitative copy number genotyping for AR. Calculated AR copy number is plotted for each of 25 participants, with range bars indicating the minimum and maximum copy numbers calculated in the triplicate analysis. M, male; F, female.
CNVs in Candidate Genes
Quantitative copy numbers (CN = 0, 1, 2, or 3+) were determined for GSTM1, GSTT1, and the six AMD-associated genes of interest in each sample (Table 3). CNVs were present in both AMD and control sample populations. For most genes, however, CN = 2 was the predominant copy number genotype. Excluding GSTM1 and GSTT1, genes for which prevalent deletion polymorphisms have been reported, the rates of carriers with CN = 2 were 73.3% to 98.9% for controls and 82.3% to 100.0% for AMD across the six AMD-associated genes. Novel CNVs were observed within CCR3, CX3CR1, and ERCC6 in both groups. 
Table 3.
 
Copy Number Frequencies in AMD Patients and Controls
Table 3.
 
Copy Number Frequencies in AMD Patients and Controls
Gene CN Control n (%) AMD n (%) Unadjusted Age-Adjusted
OR (95% CI) P OR (95% CI) P
CCR3 0 1 (1.3) 1 (1.1) 0.93 (0.06–15.21) 0.96 0.35 (0.01–9.15) 0.53
1 3 (3.8) 5 (5.7) 1.56 (0.36–6.75) 0.56 1.03 (0.17–6.32) 0.98
2 70 (88.6) 75 (86.2) 1.0 1.0
3+ 5 (6.3) 6 (6.9) 1.12 (0.33–3.83) 0.86 1.81 (0.38–8.62) 0.45
Total 79 87
CFH 0 0 (0) 0 (0)
1 4 (5.1) 1 (1.1) 0.22 (0.02–2.05) 0.19 0.10 (0.01–1.40) 0.09
2 68 (86.1) 76 (87.4) 1.0 1.0
3+ 7 (8.9) 10 (11.5) 1.28 (0.46–3.54) 0.64 2.10 (0.57–7.71) 0.26
Total 79 87
CX3CR1 0 0 (0) 0 (0)
1 2 (2.0) 4 (3.1) 1.36 (0.24–7.64) 0.72 1.41 (0.23–8.62) 0.71
2 73 (73.0) 107 (82.3) 1.0 1.0
3+ 25 (25.0) 19 (14.6) 0.52 (0.27–1.01) 0.05* 0.55 (0.25–1.21) 0.14
Total 100 130
ERCC6 0 0 (0) 0 (0)
1 1 (1.3) 2 (2.3) 1.81 (0.16,20.40) 0.63 1.94 (0.08,44.87 0.68
2 78 (98.7) 86 (97.7) 1.0 1.0
3+ 0 (0) 0 (0)
Total 79 88
HTRA1 0 0 (0) 0 (0)
1 0 (0) 0 (0)
2 74 (92.5) 82 (93.2) 1.0 1.0
3+ 6 (7.5) 6 (6.8) 0.90 (0.28–2.92) 0.86 1.98 (0.46–8.52) 0.36
Total 80 88
VEGF 0 0 (0) 0 (0)
1 0 (0) 0 (0)
2 77 (96.3) 88 (100.0) 1.0 1.0
3+ 3 (3.8) 0 (0)
Total 80 88
GSTM1 0 47 (58.8) 48 (54.5) 0.89 (0.46–1.72) 0.72 0.87 (0.40–1.91) 0.74
1 0 (0) 2 (2.3)
2 26 (32.5) 30 (34.1) 1.0 1.0
3+ 7 (8.8) 8 (9.1) 0.99 (0.32–3.10) 0.99 1.11 (0.29–4.33) 0.88
Total 80 88
GSTT1 0 17 (21.3) 15 (17.4) 0.75 (0.31–1.83) 0.53 0.51 (0.18–1.45) 0.20
1 39 (48.8) 38 (44.2) 0.83 (0.41–1.69) 0.61 0.82 (0.35–1.91) 0.64
2 23 (28.8) 27 (31.4) 1.0 1.0
3+ 1 (1.3) 6 (7.0) 5.11 (0.57–45.57) 0.14 2.05 (0.18–23.94) 0.57
Total 80 86
Associations between CNVs in Candidate Genes and AMD
The frequencies of each copy number category were compared relative to the CN = 2 category. CN = 2 was selected as the reference for statistical analysis because humans (diploids) are expected to have two copies of most genes. Comparisons of the CN frequencies between AMD patients and control subjects were performed using unadjusted and then age-adjusted logistic regression. The unadjusted association of CN = 3+ for CX3CR1 was in the protection for AMD (odds ratio [OR] = 0.52; 95% confidence interval [CI], 0.27–1.0; P = 0.05), but this trend did not persist after adjustment for age (P = 0.14). There were no significant differences in the copy number category frequencies for any of the other genes. 
To determine whether there was a general trend toward increased or decreased copy number at the population level, the mean number of copies of each gene was also calculated (Table 4). Comparisons between AMD patients and controls were performed using t-test and age-adjusted analysis of covariance. The unadjusted data suggested a decrease in the mean number of copies of CX3CR1 in AMD patients relative to controls (2.12 ± 0.41 vs. 2.23 ± 0.47 copies; P = 0.05). This difference was not observed after adjusting for age (P = 0.10). Although the unadjusted association of the mean CFH CN between AMD patients and controls was not statistically significant (2.10 ± 0.34 vs. 2.04 ± 0.37 copies; P = 0.24), the difference became nominally statistically significant (unadjusted for multiple comparisons) after adjusting for age (2.13 [95% CI, 2.05–2.21] vs. 2.01 [95% CI, 1.92–2.09] copies; P = 0.05). 
Table 4.
 
Mean Copy Numbers in AMD Patients and Controls
Table 4.
 
Mean Copy Numbers in AMD Patients and Controls
Genes Unadjusted Age-Adjusted
Control AMD P Control AMD P
CCR3 2.00 ± 0.39 1.99 ± 0.42 0.86 1.96 (1.87–2.06) 2.02 (1.93–2.11) 0.42
CFH 2.04 ± 0.37 2.10 ± 0.34 0.24 2.01 (1.92–2.09) 2.13 (2.05–2.21) 0.05*
CX3CR1 2.23 ± 0.47 2.12 ± 0.41 0.05* 2.23 (2.13–2.32) 2.12 (2.04–2.20) 0.10
ERCC6 1.99 ± 0.11 1.98 ± 0.15 0.63 1.99 (1.95–2.02) 1.98 (1.95–2.01) 0.75
HTRA1 2.08 ± 0.27 2.07 ± 0.25 0.86 2.05 (1.99–2.11) 2.09 (2.03–2.15) 0.36
VEGF 2.04 ± 0.19 2.00 ± 0.00 0.07 2.02 (1.99–2.05) 2.01 (1.98–2.04) 0.69
GSTM1 0.91 ± 1.13 0.98 ± 1.12 0.71 0.89 (0.62–1.16) 1.00 (0.74–1.26) 0.60
GSTT1 1.10 ± 0.74 1.28 ± 0.84 0.15 1.10 (0.90–1.29) 1.28 (1.10–1.47) 0.20
Discussion
This study investigated CNVs in candidate genes related to a variety of pathways implicated in AMD pathogenesis. Activation of the complement cascade plays a pivotal role in AMD pathogenesis, and genetic polymorphisms in a variety of complement pathway-related genes, including CFH, complement factor B (CFB), complement components 2 and 3 (C2 and C3), CFHR1, and CFHR3, have been strongly linked to AMD. 19 Two loss-of-function SNPs in CX3CR1, a chemokine receptor that plays a critical role in microglial migration, have also been associated with elevated AMD risk, 20 22 providing further support for an immunologic basis to AMD pathogenesis. A polymorphism in ERCC6, which plays a role in DNA repair, has also been weakly linked to AMD. 23 Another important AMD susceptibility locus lies on chromosome 10q26 and includes two genes that are in strong linkage disequilibrium—age-related maculopathy susceptibility 2 (ARMS2) and HTRA1. ARMS2 may play roles in mitochondrial and extracellular matrix function, and numerous polymorphisms in ARMS2 have been linked to AMD. 24 26 A well-characterized SNP in the promoter region of HTRA1 has been associated specifically with neovascular AMD, 27,28 potentially by facilitating choroidal neovascularization through enhanced degradation of extracellular matrix. 2 The chemokine receptor CCR3 29 and SNPs in VEGF 30 have also been linked to neovascular AMD. Epidemiologic and molecular studies that have linked each of these genes to AMD provide a strong mechanistic rationale for selecting them as candidate genes for evaluating additional types of genetic variations, including CNVs, which may modulate their associations with AMD. 
The duplex RT-PCR based copy number assay methods used in this study have been demonstrated to be a reliable and accurate strategy to precisely determine quantitative copy numbers for specific candidate genes in both disease and control samples. Genomic DNA concentrations were rigorously quantified and controlled before copy number genotyping using two independent methods, UV absorbance and RT-PCR amplification of RNase P. This exactitude and same-well amplification of RNase P protected against artificial variations caused by differences in DNA loading or erroneous detection of the null genotype (CN = 0) caused by PCR failure or pipette error. 
RT-PCR amplification efficiencies for each tested assay were calculated to be near 100%. Differences in the amplification efficiencies for each gene of interest and RNase P were <7%. This ensured the validity of the ΔΔCt method, which was used to calculate quantitative copy numbers. 31 Although the efficiencies for GSTM1 and GSTT1 were not determined in this study, copy number assays (TaqMan; Applied Biosystems) for both these genes have been evaluated in the literature. 32 The efficiencies were reported to be consistently between 92% and 100% and approximately equal to that of RNase P. 32 Other groups have also used these assays reliably for GSTM1 and GSTT1 copy number genotyping. 9,33  
Quantitative copy numbers were determined using these methods with high reproducibly and accuracy. More than 97% of duplicated assays resulted in the same copy number call, and the number of copies of AR, known to exist with CN = 1 in men and CN = 2 in women, was correctly determined with 100% accuracy in a subset of samples. The copy number distributions determined for GSTM1 and GSTT1 in this study were in agreement with previously published results. The null deletion (CN = 0) was observed in 57.2% and 19.3% of all subjects for GSTM1 and GSTT1, respectively. CNVs in these genes are well documented, and previous studies have found the frequencies of CN = 0 to be approximately 50% for GSTM1 and 20% for GSTT1 in European populations. 32,33  
All these lines of evidence suggested that the methods used in this study were sufficient to quantitatively characterize CNVs in candidate genes. To our knowledge, local and direct investigation of CNV has not been documented for the six AMD-associated genes selected for this study. We report the discovery of three novel CNVs within CCR3, CX3CR1, and ERCC6 in both control and AMD sample populations. CNVs at these sites have not been reported in the Database of Genomic Variants, a centralized summary of structural variations in the human genome. 34  
After adjustment for age, an increase in CFH copy number appeared to be a risk factor for AMD. CFH is a regulator of the complement cascade, and it has been consistently demonstrated as a protective factor against AMD pathogenesis. 19 The functional consequences of CFH copy number and its impact on AMD require further evaluation. There were trends in the unadjusted data that suggested CX3CR1 might also be a gene of interest. However, the effect did not persist after adjustment for age. It has been previously reported that two loss-of-function SNPs in CX3CR1, V249I and T280M, are associated with increased AMD risk and that CX3CR1 levels are lower in the maculae of AMD patients. 21,35  
Current sample sizes might have offered insufficient power because of heavy stratification by copy number category. However, a significant increase in the sample size would not have changed the penetrance of CFH or CX3CR1 CNVs at the onset of disease. Another limitation might have been the statistically significant difference between the ages of the AMD patient and control groups. As a result, statistical adjustments for age might have been incomplete. Nevertheless, further adjustments would dilute the significance of the associations, and they would not alter the conclusions of the study. 
The levels of CX3CR1 and CFH in the eyes of healthy persons with known gene copy numbers were not determined in this study. As a result, it is not possible to draw conclusions regarding the mechanistic impact of CNVs in either of these genes. Previous reports have demonstrated that increases in gene copy number can lead to either increases or decreases in gene expression. 36 Functional studies may be able to directly determine whether CNV in CX3CR1 or CFH can modulate AMD risk or contribute to AMD pathogenesis through gene dosage effects. 
In summary, a duplex RT-PCR copy number genotyping approach was used to investigate quantitative CNVs in highly associated AMD candidate genes. Three novel CNVs were discovered in CCR3, CX3CR1, and ERCC6, but no definitive associations between CNVs in the selected genes and AMD were observed. Nevertheless, the rationale still remains for further evaluation of the role of CNV in AMD pathogenesis without a limitation on previously reported AMD-associated genes. 
Footnotes
 Supported by the National Eye Institute Intramural Research Program and American Health Assistance Foundation Grant M2007037.
Footnotes
 Disclosure: M.M. Liu, None; E. Agrón, None; E. Chew, None; C. Meyerle, None; F.L. Ferris III, None; C.-C. Chan, None; J. Tuo, None
References
Bressler NM Bressler SB Congdon NG . Potential public health impact of Age-Related Eye Disease Study results: AREDS report no. 11. Arch Ophthalmol. 2003;121:1621–1624. [CrossRef] [PubMed]
Ding X Patel M Chan CC . Molecular pathology of age-related macular degeneration. Prog Retinal Eye Res. 2009;28:1–18. [CrossRef]
Conrad DF Pinto D Redon R . Origins and functional impact of copy number variation in the human genome. Nature. 2009;464:704–712. [CrossRef] [PubMed]
de Smith AJ Walters RG Froguel P Blakemore AI . Human genes involved in copy number variation: mechanisms of origin, functional effects and implications for disease. Cytogenet Genome Res. 2008;123:17–26. [CrossRef] [PubMed]
Redon R Ishikawa S Fitch KR . Global variation in copy number in the human genome. Nature. 2006;444:444–454. [CrossRef] [PubMed]
Zhang F Gu W Hurles ME Lupski JR . Copy number variation in human health, disease, and evolution. Ann Rev Genomics Hum Genet. 2009;10:451–481. [CrossRef]
Fanciulli M Petretto E Aitman TJ . Gene copy number variation and common human disease. Clin Genet. 2010;77:201–213. [CrossRef] [PubMed]
Rose-Zerilli MJ Barton SJ Henderson AJ Shaheen SO Holloway JW . Copy-number variation genotyping of GSTT1 and GSTM1 gene deletions by real-time PCR. Clin Chem. 2009;55:1680–1685. [CrossRef] [PubMed]
Zhou J Hu J Guan H . The association between copy number variations in glutathione S-transferase M1 and T1 and age-related cataract in a Han Chinese population. Invest Ophthalmol Vis Sci. 2010;51:3924–3928. [CrossRef] [PubMed]
Meyer KJ Davis LK Schindler EI . Genome-wide analysis of copy number variants in age-related macular degeneration. Hum Genet. 2011;129:91–100. [CrossRef] [PubMed]
Hageman GS Hancox LS Taiber AJ . Extended haplotypes in the complement factor H (CFH) and CFH-related (CFHR) family of genes protect against age-related macular degeneration: characterization, ethnic distribution and evolutionary implications. Ann Med. 2006;38:592–604. [CrossRef] [PubMed]
Hughes AE Orr N Esfandiary H Diaz-Torres M Goodship T Chakravarthy U . A common CFH haplotype, with deletion of CFHR1 and CFHR3, is associated with lower risk of age-related macular degeneration. Nat Genet. 2006;38:1173–1177. [CrossRef] [PubMed]
Schmid-Kubista KE Tosakulwong N Wu Y . Contribution of copy number variation in the regulation of complement activation locus to development of age-related macular degeneration. Invest Ophthalmol Vis Sci. 2009;50:5070–5079. [CrossRef] [PubMed]
Polymeropoulos MH Lavedan C Leroy E . Mutation in the alpha-synuclein gene identified in families with Parkinson's disease. Science. 1997;276:2045–2047. [CrossRef] [PubMed]
Singleton AB Farrer M Johnson J . alpha-Synuclein locus triplication causes Parkinson's disease. Science. 2003;302:841. [CrossRef] [PubMed]
Hinds DA Kloek AP Jen M Chen X Frazer KA . Common deletions and SNPs are in linkage disequilibrium in the human genome. Nat Genet. 2006;38:82–85. [CrossRef] [PubMed]
The Age-Related Eye Disease Study (AREDS): design implications. AREDS report no. 1. Controlled Clin Trials. 1999;20:573–600. [CrossRef] [PubMed]
ABI GeneAssist Copy Number Assay Workflow Builder. http://www5.appliedbiosystems.com/tools/cnv/ . Accessed January 5, 2010.
Anderson DH Radeke MJ Gallo NB . The pivotal role of the complement system in aging and age-related macular degeneration: hypothesis re-visited. Prog Retinal Eye Res. 2010;29:95–112. [CrossRef]
Combadiere C Feumi C Raoul W . CX3CR1-dependent subretinal microglia cell accumulation is associated with cardinal features of age-related macular degeneration. J Clin Invest. 2007;117:2920–2928. [CrossRef] [PubMed]
Tuo J Smith BC Bojanowski CM . The involvement of sequence variation and expression of CX3CR1 in the pathogenesis of age-related macular degeneration. FASEB J. 2004;18:1297–1299. [PubMed]
Yang X Hu J Zhang J Guan H . Polymorphisms in CFH, HTRA1 and CX3CR1 confer risk to exudative age-related macular degeneration in Han Chinese. Br J Ophthalmol. 2010;94:1211–1214. [CrossRef] [PubMed]
Tuo J Ning B Bojanowski CM . Synergic effect of polymorphisms in ERCC6 5′ flanking region and complement factor H on age-related macular degeneration predisposition. Proc Natl Acad Sci U S A. 2006;103:9256–9261. [CrossRef] [PubMed]
Fritsche LG Loenhardt T Janssen A . Age-related macular degeneration is associated with an unstable ARMS2 (LOC387715) mRNA. Nat Genet. 2008;40:892–896. [CrossRef] [PubMed]
Kortvely E Hauck SM Duetsch G . ARMS2 is a constituent of the extracellular matrix providing a link between familial and sporadic age-related macular degenerations. Invest Ophthalmol Vis Sci. 2010;51:79–88. [CrossRef] [PubMed]
Ross RJ Bojanowski CM Wang JJ . The LOC387715 polymorphism and age-related macular degeneration: replication in three case-control samples. Invest Ophthalmol Vis Sci. 2007;48:1128–1132. [CrossRef] [PubMed]
Deangelis MM Ji F Adams S . Alleles in the HtrA serine peptidase 1 gene alter the risk of neovascular age-related macular degeneration. Ophthalmology. 2008;115:1209–1215, e1207. [CrossRef] [PubMed]
Dewan A Liu M Hartman S . HTRA1 promoter polymorphism in wet age-related macular degeneration. Science. 2006;314:989–992. [CrossRef] [PubMed]
Takeda A Baffi JZ Kleinman ME . CCR3 is a target for age-related macular degeneration diagnosis and therapy. Nature. 2009;460:225–230. [CrossRef] [PubMed]
Churchill AJ Carter JG Lovell HC . VEGF polymorphisms are associated with neovascular age-related macular degeneration. Hum Mol Genet. 2006;15:2955–2961. [CrossRef] [PubMed]
Livak KJ Schmittgen TD . Analysis of relative gene expression data using real-time quantitative PCR and the 2ΔΔCT method. Methods. 2001;25:402–408. [CrossRef] [PubMed]
Bediaga NG Alfonso-Sanchez MA de Renobales M Rocandio AM Arroyo M de Pancorbo MM . GSTT1 and GSTM1 gene copy number analysis in paraffin-embedded tissue using quantitative real-time PCR. Anal Biochem. 2008;378:221–223. [CrossRef] [PubMed]
Norskov MS Frikke-Schmidt R Loft S Tybjaerg-Hansen A . High-throughput genotyping of copy number variation in glutathione S-transferases M1 and T1 using real-time PCR in 20,687 individuals. Clinical Biochem. 2009;42:201–209. [CrossRef]
TCAG Database of Genomic Variants. http://projects.tcag.ca/variation/ . Accessed February 1, 2010.
Chan CC Tuo J Bojanowski CM Csaky KG Green WR . Detection of CX3CR1 single nucleotide polymorphism and expression on archived eyes with age-related macular degeneration. Histol Histopathol. 2005;20:857–863. [PubMed]
Stranger BE Forrest MS Dunning M . Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science. 2007;315:848–853. [CrossRef] [PubMed]
Figure 1.
 
RT-PCR amplification efficiency of copy number assays. Standard curves for the RT-PCR amplification efficiency of each assay were generated by plotting Ct against DNA quantity (log concentration) for the gene of interest and the RNase P internal control. (A) CCR3; (B) ERCC6; (C) CFH; (D) HTRA1; (E) CX3CR1; (F) VEGF. Five twofold serial dilutions were performed in duplicate for each gene. Calculated efficiencies were close to 100% and were similar between each gene of interest and RNase P.
Figure 1.
 
RT-PCR amplification efficiency of copy number assays. Standard curves for the RT-PCR amplification efficiency of each assay were generated by plotting Ct against DNA quantity (log concentration) for the gene of interest and the RNase P internal control. (A) CCR3; (B) ERCC6; (C) CFH; (D) HTRA1; (E) CX3CR1; (F) VEGF. Five twofold serial dilutions were performed in duplicate for each gene. Calculated efficiencies were close to 100% and were similar between each gene of interest and RNase P.
Figure 2.
 
Representative amplification plots for quantitative copy number determination. Quantitative copy numbers were determined using differences in the amplification of the gene of interest (FAM-labeled) relative to the RNase P internal control of known copy number (VIC-labeled). Representative data show amplification plots for participants of CN = 1, CN = 2, and CN = 3 for CX3CR1.
Figure 2.
 
Representative amplification plots for quantitative copy number determination. Quantitative copy numbers were determined using differences in the amplification of the gene of interest (FAM-labeled) relative to the RNase P internal control of known copy number (VIC-labeled). Representative data show amplification plots for participants of CN = 1, CN = 2, and CN = 3 for CX3CR1.
Figure 3.
 
Quantitative copy number genotyping for AR. Calculated AR copy number is plotted for each of 25 participants, with range bars indicating the minimum and maximum copy numbers calculated in the triplicate analysis. M, male; F, female.
Figure 3.
 
Quantitative copy number genotyping for AR. Calculated AR copy number is plotted for each of 25 participants, with range bars indicating the minimum and maximum copy numbers calculated in the triplicate analysis. M, male; F, female.
Table 1.
 
Demographic and Clinical Information for Study Participants
Table 1.
 
Demographic and Clinical Information for Study Participants
Control (n = 103) Neovascular AMD (n = 131) P
Age, y 69.6 ± 9.8 79.4 ± 8.3 <0.0001*
Female 61 (59.22) 63 (48.09) 0.09
Past smoker 52 (50.49) 67 (51.15) 0.92
Current smoker 3 (2.91) 10 (7.63) 0.12
Cataract 41 (39.81) 88 (67.18) <0.0001*
Ocular inflammation 2 (1.94) 0 (0) 0.11
Glaucoma 5 (4.85) 8 (6.11) 0.68
Corneal disease 2 (1.94) 1 (0.76) 0.43
Optic nerve disease 2 (1.94) 3 (2.29) 0.85
Non-AMD retinal disease 0 (0) 10 (7.63) 0.0042*
Cardiovascular disease 45 (43.69) 93 (70.99) <0.0001*
Alzheimer's disease 0 (0) 2 (1.53) 0.21
Table 2.
 
Copy Number Assay Information
Table 2.
 
Copy Number Assay Information
Gene Assay ID* Assay Location (NCBI build 37) Assay Cytoband Assay Gene Location
CCR3 Hs00751151_cn chr3:46283769 3p21.31h Exon 1
CFH Hs00116895_cn chr1:196621254 1q31.3c Exon 1
CX3CR1 Hs02139194_cn chr3:39305135 3p26.3c Exon 5
ERCC6 Hs01920803_cn chr10:50681068 10q11.23a Intron 14-Exon 15
HTRA1 Hs03730183_cn chr10:124264488 10q26.13b Intron 3
VEGF Hs00609007_cn chr6:43738068 6p21.1d Exon 1
GSTM1 Hs00273142_cn chr1:110230461 1p13.3b Exon 1
GSTT1 Hs00767125_cn chr22:24376147 22q11.23b Exon 5
AR Custom design† Xq11.2 Exon 1
Table 3.
 
Copy Number Frequencies in AMD Patients and Controls
Table 3.
 
Copy Number Frequencies in AMD Patients and Controls
Gene CN Control n (%) AMD n (%) Unadjusted Age-Adjusted
OR (95% CI) P OR (95% CI) P
CCR3 0 1 (1.3) 1 (1.1) 0.93 (0.06–15.21) 0.96 0.35 (0.01–9.15) 0.53
1 3 (3.8) 5 (5.7) 1.56 (0.36–6.75) 0.56 1.03 (0.17–6.32) 0.98
2 70 (88.6) 75 (86.2) 1.0 1.0
3+ 5 (6.3) 6 (6.9) 1.12 (0.33–3.83) 0.86 1.81 (0.38–8.62) 0.45
Total 79 87
CFH 0 0 (0) 0 (0)
1 4 (5.1) 1 (1.1) 0.22 (0.02–2.05) 0.19 0.10 (0.01–1.40) 0.09
2 68 (86.1) 76 (87.4) 1.0 1.0
3+ 7 (8.9) 10 (11.5) 1.28 (0.46–3.54) 0.64 2.10 (0.57–7.71) 0.26
Total 79 87
CX3CR1 0 0 (0) 0 (0)
1 2 (2.0) 4 (3.1) 1.36 (0.24–7.64) 0.72 1.41 (0.23–8.62) 0.71
2 73 (73.0) 107 (82.3) 1.0 1.0
3+ 25 (25.0) 19 (14.6) 0.52 (0.27–1.01) 0.05* 0.55 (0.25–1.21) 0.14
Total 100 130
ERCC6 0 0 (0) 0 (0)
1 1 (1.3) 2 (2.3) 1.81 (0.16,20.40) 0.63 1.94 (0.08,44.87 0.68
2 78 (98.7) 86 (97.7) 1.0 1.0
3+ 0 (0) 0 (0)
Total 79 88
HTRA1 0 0 (0) 0 (0)
1 0 (0) 0 (0)
2 74 (92.5) 82 (93.2) 1.0 1.0
3+ 6 (7.5) 6 (6.8) 0.90 (0.28–2.92) 0.86 1.98 (0.46–8.52) 0.36
Total 80 88
VEGF 0 0 (0) 0 (0)
1 0 (0) 0 (0)
2 77 (96.3) 88 (100.0) 1.0 1.0
3+ 3 (3.8) 0 (0)
Total 80 88
GSTM1 0 47 (58.8) 48 (54.5) 0.89 (0.46–1.72) 0.72 0.87 (0.40–1.91) 0.74
1 0 (0) 2 (2.3)
2 26 (32.5) 30 (34.1) 1.0 1.0
3+ 7 (8.8) 8 (9.1) 0.99 (0.32–3.10) 0.99 1.11 (0.29–4.33) 0.88
Total 80 88
GSTT1 0 17 (21.3) 15 (17.4) 0.75 (0.31–1.83) 0.53 0.51 (0.18–1.45) 0.20
1 39 (48.8) 38 (44.2) 0.83 (0.41–1.69) 0.61 0.82 (0.35–1.91) 0.64
2 23 (28.8) 27 (31.4) 1.0 1.0
3+ 1 (1.3) 6 (7.0) 5.11 (0.57–45.57) 0.14 2.05 (0.18–23.94) 0.57
Total 80 86
Table 4.
 
Mean Copy Numbers in AMD Patients and Controls
Table 4.
 
Mean Copy Numbers in AMD Patients and Controls
Genes Unadjusted Age-Adjusted
Control AMD P Control AMD P
CCR3 2.00 ± 0.39 1.99 ± 0.42 0.86 1.96 (1.87–2.06) 2.02 (1.93–2.11) 0.42
CFH 2.04 ± 0.37 2.10 ± 0.34 0.24 2.01 (1.92–2.09) 2.13 (2.05–2.21) 0.05*
CX3CR1 2.23 ± 0.47 2.12 ± 0.41 0.05* 2.23 (2.13–2.32) 2.12 (2.04–2.20) 0.10
ERCC6 1.99 ± 0.11 1.98 ± 0.15 0.63 1.99 (1.95–2.02) 1.98 (1.95–2.01) 0.75
HTRA1 2.08 ± 0.27 2.07 ± 0.25 0.86 2.05 (1.99–2.11) 2.09 (2.03–2.15) 0.36
VEGF 2.04 ± 0.19 2.00 ± 0.00 0.07 2.02 (1.99–2.05) 2.01 (1.98–2.04) 0.69
GSTM1 0.91 ± 1.13 0.98 ± 1.12 0.71 0.89 (0.62–1.16) 1.00 (0.74–1.26) 0.60
GSTT1 1.10 ± 0.74 1.28 ± 0.84 0.15 1.10 (0.90–1.29) 1.28 (1.10–1.47) 0.20
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×