Abstract
Myopia is the most common ocular disease worldwide. We investigated the association of high myopia with the common single nucleotide polymorphisms (SNPs) of five candidate genes – early growth response 1 (EGR1), v-fos FBJ murine osteosarcoma viral oncogene homolog (FOS), jun oncogene (JUN), vasoactive intestinal peptide (VIP), and vasoactive intestinal peptide receptor 2 (VIPR2). We recruited 1200 unrelated Chinese subjects with 600 cases (spherical equivalent ≤−8.00 diopters) and 600 controls (spherical equivalent within ±1.00 diopter). A discovery sample set was formed from 300 cases and 300 controls, and a replication sample set from the remaining samples. Tag SNPs were genotyped for the discovery sample set, and the most significant haplotypes and their constituent SNPs were followed up with the replication sample set. The allele and haplotype frequencies in cases and controls were compared by logistic regression adjusted for sex and age to give P a values, and multiple comparisons were corrected by permutation test to give P aemp values. Odd ratios (OR) were calculated accordingly. In the discovery phase, EGR1, JUN and VIP did not show any significant association while FOS and VIPR2 demonstrated significant haplotype association with high myopia. In the replication phase, the haplotype association for VIPR2 was successfully replicated, but not FOS. In analysis combining both sample sets, the most significant association signals of VIPR2 were the single marker rs2071625 (P a = 0.0008, P aemp = 0.0046 and OR = 0.75) and the 4-SNP haplotype window rs2071623-rs2071625-rs2730220-rs885863 (omnibus test, P a = 9.10e-10 and P aemp = 0.0001) with one protective haplotype (GGGG: P aemp = 0.0002 and OR = 0.52) and one high-risk haplotype (GAGA: P aemp = 0.0027 and OR = 4.68). This 4-SNP haplotype window was the most significant in all sample sets examined. This is the first study to suggest a role of VIPR2 in the genetic susceptibility to high myopia. EGR1, JUN, FOS and VIP are unlikely to be important in predisposing humans to high myopia.
Introduction
Myopia is the most common eye disorder worldwide and has reached epidemic prevalence in East Asia [1]. Myopia can be classified into different categories based on the clinical entity [2]. High myopia is defined as a refractive error equal to or worse than −6.00 diopters (D). It is the most concerned type because of its association with irreversible visual impairment such as retinal detachment, glaucoma and, in severe cases, blindness [3]. Although both environmental and genetic factors play important roles in the development of myopia [4], [5], the principal factor is still under debate. Cross-sectional studies have shown that environmental factors such as educational level and near work are associated with the development of myopia [1], [6]. Evidence pointing to the role of genetic factors in the etiology of myopia comes mainly from the identification of myopia loci/genes in linkage and/or association studies [7]–[15]. Myopia is a complex disease, and genetic variations can increase the susceptibility to environmental factors and cause an early onset and/or aggressive progression. As the age of myopia onset is decreasing [16], [17], the chance of developing high myopia increases. In order to control the progression of myopia, the underlying pathways leading to this condition must be understood.
Animal studies show that the development of myopia involves extracellular matrix (ECM) remodeling of the sclera [18], [19]. Therefore, candidate-gene association studies in myopia genetics have mainly focused on the genes expressed in the sclera [20]–[23]. However, it is well established that visual experience alters ocular growth and the changes are first mediated by local visual processing and signaling mechanisms [24]–[26]. We hypothesize that genes directly responsive to visual signals are the primary genes involved in the biological pathways. Activation of these genes may further activate other secondary genes in the pathways, and this in turn causes ECM remodeling of the sclera and ultimately leads to altered ocular growth. This study aims to investigate these primary genes for their potential role in the susceptibility to high myopia. Five functional candidate genes have been selected on the basis of this hypothesis: early growth response 1 (EGR1) located at chromosome 5q31.1, v-fos FBJ murine osteosarcoma viral oncogene homolog (FOS) at 14q24.3, jun oncogene (JUN) at 1p32-p31, vasoactive intestinal peptide (VIP) at 6q25, vasoactive intestinal peptide receptor 2 (VIPR2) at 7q36.3 (NCBI, http://www.ncbi.nlm.nih.gov/).
Consistent findings from different animal models demonstrate the participation of Egr-1 (also known as ZENK) in ocular growth [27]–[29]. The study of Egr-1 knockout mice has also provided convincing evidence for the involvement of Egr-1 in regulating ocular growth [30]. Egr-1 knockout mice had a myopic shift in refraction and tended to have eyes with a longer axial length. FOS encodes a protein that dimerizes with the protein encoded by JUN to form a transcription factor complex known as activating protein-1 (AP-1) [31]. Binding of AP-1 causes trans-activation of its target genes. AP-1 sites were found in the promoters of genes encoding matrix metalloproteinases (MMPs) and their inhibitors (tissue inhibitor of metalloproteinases or TIMPs) [32], [33]. In other words, AP-1 can regulate the expression of MMPs and TIMPs. MMPs are capable of degrading ECM proteins and are believed to be involved in ECM remodeling of the sclera. AP-1 can also repress the trans-activation of retinoid receptors [34], which have been shown to be critical for the regulation of eye growth [35]. The expression of VIP showed a positive correlation with the depth of the vitreous chamber [36] and this suggests that increased release of VIP may be responsible for ocular growth. VIPR2 is one of the VIP receptors and is located on chromosome 7q36, which is within the interval for a putative locus for autosomal dominant high-grade myopia (formerly called MYP4) [37], [38]. The expression of VIPR2 in the retina and the choroid was altered in chicks with form-deprivation myopia [39]. These findings suggest a potential role of VIPR2 in the development of myopia.
We conducted a case-control genetic association study to investigate the association between high myopia and the five selected candidate genes. Samples from a homogeneous population (southern Han Chinese) were used to minimize the possibility of false positive results due to population stratification. We also validated the initial positive findings with an independent sample set.
Materials and Methods
Recruitment of Subjects
We recruited unrelated Han Chinese aged between 18 and 45 years via the Optometry Clinic of The Hong Kong Polytechnic University as described previously [9]–[11]. Cases were subjects with refraction (spherical equivalent or SE) of −8.00 D or worse for both eyes while controls were subjects with SE within ±1.00 D for both eyes. Subjects with ocular disease or genetic disease associated with myopia were excluded from the study. The study was approved by the Human Subjects Ethics Sub-committee, The Hong Kong Polytechnic University, and adhered to the tenets of the Declaration of Helsinki. All participants gave written informed consent. Eye examination included retinoscopy, fundus examination, and measurement of refractive error, corneal power, lens thickness, anterior chamber depth, posterior chamber depth and axial length [9]–[11]. In total, we recruited 600 cases and 600 controls, and sequentially allocated them into two sample sets (the discovery sample set and the replication sample set). Each sample set consisted of 300 cases and 300 controls.
Selection and genotyping of single nucleotide polymorphisms (SNPs)
Genomic DNA was extracted from the subjects' blood samples [9]. Tag SNPs of the five candidate genes (Table S1) were identified from the HapMap database (release 23a/phase II March 08; http://hapmap.ncbi.nlm.nih.gov/) with the selection criteria of r2>0.8 and minor allele frequency (MAF)>0.10 for Han Chinese population by the Tagger software. The 3-kb regions upstream and downstream of the candidate genes were included for SNP selection [11], [23].
We genotyped the SNPs by restriction fragment length polymorphism, unlabelled probe melting curve analysis or primer extension reaction coupled with denaturing high-performance liquid chromatography [9]–[11], [23]. We used direct DNA sequencing of representative samples to confirm all observed genotypes. Details of the genotyping methods are described in Appendix S1. Tag SNPs and their genotyping methods are listed in Table S1 together with the respective restriction enzymes, primers, extension primer, and probes. Tag SNPs showing significant associations in single-marker or haplotype analyses using the discovery sample set were followed up with the replication sample set.
Statistical analysis
We used PLINK (ver. 1.07; http://pngu.mgh.harvard.edu/~purcell/plink/) as the software tool for association analysis [40]. Genotypes of the controls were tested for Hardy-Weinberg equilibrium (HWE) by exact test with a significance threshold set at P = 0.001 [41]. Single-marker (allelic test) and haplotype associations were tested using logistic regression adjusted for sex and age as covariates, and odds ratios (OR) and their 95% confidence intervals (CI) were also calculated accordingly. We performed haplotype analysis using an exhaustive sliding-window approach by testing all possible haplotypes made up of a variable number of constitutive SNPs. For each sliding window, we jointly assessed the significance of the haplotype effects by a single case-control omnibus test with (H – 1) degrees of freedom, where H is the number of haplotypes for the window concerned. For a particular window size with a given gene, we conducted the test for all possible windows of the same size, and shifted one SNP at a time to the 3′ end of the gene. Multiple testing was corrected by generating empirical P values based on 10 000 permutations across all SNPs or haplotype windows for a given sample set as appropriate. To increase the power of the study, the genotype data were also analyzed by combining the two sample sets with adjustment for sample set as another covariate in addition to sex and age. P values adjusted for the covariates are reported, and indicated as P a if not corrected for multiple comparisons or as P aemp if corrected for multiple comparisons. A P aemp<0.05 indicates significant association. Note that the minimum P aemp value achievable by 10 000 permutations is 0.0001. Linkage disequilibrium (LD) maps were constructed by Haploview using solid spine of LD as the definition of haplotype blocks [42].
Results
Subject demographics
Measurements for all traits were highly correlated between the right and the left eyes, particularly for SE (r = 0.97) and axial length (r = 0.96). Hence, only measurements for the right eye were used for analysis. The characteristics of the subjects in the discovery and the replication sample sets are presented in Table 1. The average SE values were 0.03 D for controls and −10.56 D for cases of the discovery sample set, and 0.10 D for controls and −10.06 D for cases of the replication sample set. Most control subjects had SE between −0.10 D and 0.10 D with about 2.2% of controls in the range of 0.12 D and 0.40 D. Most case subjects had SE between −8.00 D and −15.00 D with 4.8% of cases in the range of less than −15.00 D and −24.00 D. This skewed distribution arose as a result of the criteria used for subject recruitment.
Table 1. Characteristics of subjects in the discovery and the replication sample sets*.
| Discovery sample set | Replication sample set | |||
| Characteristics | Controls | Cases | Controls | Cases |
| Total number | 300 | 300 | 300 | 300 |
| Proportion of females, % | 55.60 | 73.33 | 59.33 | 69.67 |
| Age (mean ± SD), years† | 24.90±6.10 | 27.75±6.89 | 33.34±9.52 | 33.73±9.09 |
| SE (mean ± SD), D | 0.03±0.46 | −10.56±2.49 | 0.10±0.56 | −10.16±2.31 |
| AL (mean ± SD), mm | 23.85±0.82 | 27.77±1.15 | 23.72±0.83 | 27.55±1.15 |
| ACD (mean ± SD), mm | 3.62±0.35 | 3.72±0.32 | 3.18±0.41 | 3.34±0.39 |
| PCD (mean ± SD) , mm | 16.30±0.95 | 19.97±1.21 | 16.19±0.87 | 19.89±1.19 |
| LT (mean ± SD), mm | 3.94±0.55 | 4.02±0.55 | 4.34±0.58 | 4.29±0.51 |
| CP (mean ± SD), D | 43.86±1.61 | 44.91±1.42 | 44.19±1.50 | 44.93±1.48 |
The ocular measurements are based on the data of the right eyes.
The data of age are missing in 2 controls and 3 cases of the discovery sample set, and 2 controls and 1 case of the replication sample set.
Abbreviations: SD, standard deviation; SE, spherical equivalent; AL, axial length; ACD, anterior chamber depth; PCD, posterior chamber depth; LT, lens thickness; CP, corneal power; and D, diopter.
There were fewer females in the control group than in the case group for the discovery sample set (55.60% vs 73.33%; chi-squared test, P = 9.146×10−6) and for the replication sample set (59.33% vs 69.67%; chi-squared test, P = 0.0105). The subjects were younger in the control group than in the case group (mean age, 24.90 vs 27.75 years; unpaired t test, P = 3.02×10−7) for the discovery sample set. Although the mean age was similar in both the control and the case groups (33.34 vs 33.73 years; unpaired t test, P = 0.6118) of the replication sample set, we adjusted for sex and age in all subsequent association analyses for all sample sets to maintain consistency across the board.
Discovery sample set
In total, 26 tag SNPs were selected and genotyped for the discovery sample set: 1 from ERG1, 5 from FOS, 4 from JUN, 3 from VIP and 13 from VIPR2 (Table S1). Table 2 summarizes the genotype data. The control group was in HWE (P>0.001) for all 26 tag SNPs examined. Therefore, we included all SNPs for association analysis. In single-marker analysis, six SNPs showed significant nominal P values (P a<0.05): rs4645874 (S04) of FOS, rs1407267 (S01) of VIP, and rs3828963 (S03), rs6973238 (S06), rs3793227 (S07) and rs2071623 (S10) of VIPR2. However, none of them remained significant (P aemp<0.05) after correction for multiple comparisons across 26 SNPs by permutation test.
Table 2. Functional candidate genes: summary of genotype data and single-marker association analysis.
| Sequential | Alleles† | Genotype counts (11/12/22) | Minor allele freq | P value | P a | ||||
| Gene | SNP | No. * | (1/2) | Cases | Controls | Cases | Controls | (HWE for controls) | (allelic association) |
| Discovery sample set | |||||||||
| EGR1 | rs11741807 | (S01) | G/T | 183/107/10 | 188/100/12 | 0.2117 | 0.2067 | 0.9513 | 0.8602 |
| FOS | rs7101 | (S01) | C/T | 81/132/87 | 95/138/67 | 0.5100 | 0.4533 | 0.2464 | 0.0816 |
| rs1063169 | (S02) | G/T | 190/96/14 | 187/95/18 | 0.2067 | 0.2183 | 0.2667 | 0.5630 | |
| rs4645869 | (S03) | G/A | 221/71/8 | 207/86/7 | 0.1450 | 0.1667 | 0.7724 | 0.7302 | |
| rs4645874 | (S04) | C/T | 224/71/5 | 206/90/4 | 0.1350 | 0.1633 | 0.1324 | 0.0208 | |
| rs17103109 | (S05) | T/G | 149/127/24 | 149/130/21 | 0.2917 | 0.2867 | 0.3896 | 0.0801 | |
| JUN | rs2104259 | (S01) | C/G | 119/120/61 | 116/134/50 | 0.4033 | 0.3900 | 0.3325 | 0.5208 |
| rs2760501 | (S02) | T/G | 199/86/15 | 192/91/17 | 0.1933 | 0.2083 | 0.2146 | 0.5752 | |
| rs1323288 | (S03) | A/C | 117/139/44 | 106/142/52 | 0.3783 | 0.4100 | 0.7751 | 0.4260 | |
| rs997768 | (S04) | T/C | 71/174/55 | 81/153/66 | 0.4733 | 0.4750 | 0.8056 | 0.8680 | |
| VIP | rs1407267 | (S01) | G/T | 189/101/10 | 216/75/9 | 0.2017 | 0.1550 | 0.5332 | 0.0237 |
| rs12201030 | (S02) | A/G | 226/72/2 | 239/59/2 | 0.1267 | 0.1050 | 0.6791 | 0.4515 | |
| rs664355 | (S03) | C/T | 230/63/7 | 238/54/8 | 0.1283 | 0.1167 | 0.0649 | 0.3953 | |
| VIPR2 | rs3812311 | (S01) | A/G | 166/111/23 | 179/91/30 | 0.2617 | 0.2517 | 0.0015 | 0.9931 |
| rs464260 | (S02) | A/G | 176/118/6 | 182/112/6 | 0.2167 | 0.2067 | 0.0210 | 0.7257 | |
| rs3828963 | (S03) | A/T | 244/54/2 | 230/61/9 | 0.0967 | 0.1317 | 0.1175 | 0.0264 | |
| rs3793238 | (S04) | G/A | 228/65/7 | 233/60/7 | 0.1317 | 0.1233 | 0.2862 | 0.7567 | |
| rs399867 | (S05) | C/T | 150/117/33 | 167/101/32 | 0.3050 | 0.2750 | 0.0110 | 0.4522 | |
| rs6973238 | (S06) | T/C | 202/82/16 | 174/95/31 | 0.1900 | 0.2617 | 0.0032 | 0.0060 | |
| rs3793227 | (S07) | C/T | 240/56/4 | 220/68/12 | 0.1067 | 0.1533 | 0.0532 | 0.0152 | |
| rs2540352 | (S08) | G/A | 195/85/20 | 202/83/15 | 0.2083 | 0.1883 | 0.1424 | 0.1436 | |
| rs6950938 | (S09) | G/A | 178/92/30 | 184/98/18 | 0.2533 | 0.2233 | 0.3792 | 0.1786 | |
| rs2071623 | (S10) | G/A | 148/97/55 | 126/119/55 | 0.3450 | 0.3817 | 0.0077 | 0.0402 | |
| rs2071625 | (S11) | A/G | 158/117/25 | 135/120/45 | 0.2783 | 0.3500 | 0.0466 | 0.1585 | |
| rs2730220 | (S12) | G/A | 249/41/10 | 245/49/6 | 0.1017 | 0.1017 | 0.1357 | 0.0678 | |
| rs885863 | (S13) | G/A | 210/83/7 | 197/95/8 | 0.1617 | 0.1850 | 0.5261 | 0.1508 | |
| Replication sample set | |||||||||
| FOS | rs4645869 | (S03) | G/A | 214/77/9 | 213/75/9 § | 0.1583 | 0.1566 | 0.5072 | 0.9114 |
| rs4645874 | (S04) | C/T | 235/57/8 | 242/55/3 | 0.1217 | 0.1017 | 1.0000 | 0.2633 | |
| rs17103109 | (S05) | T/G | 168/114/18 | 158/117/25 | 0.2500 | 0.2783 | 0.6660 | 0.2295 | |
| VIPR2 | rs2071623 | (S10) | G/A | 132/137/31 | 125/130/45 | 0.3317 | 0.3667 | 0.2632 | 0.1506 |
| rs2071625 | (S11) | A/G | 145/131/24 | 124/134/42 | 0.2983 | 0.3633 | 0.5349 | 0.0169 | |
| rs2730220 | (S12) ‡ | G/A | 259/41/0 | 232/65/3 | 0.0683 | 0.1183 | 0.7804 | 0.0017 ‡ | |
| rs885863 | (S13) | G/A | 186/95/19 | 202/91/7 | 0.2217 | 0.1750 | 0.5470 | 0.0426 | |
| Combined sample set | |||||||||
| FOS | rs4645869 | (S03) | G/A | 435/148/17 | 420/161/16 § | 0.1517 | 0.1524 | 0.8802 | 0.7063 |
| rs4645874 | (S04) | C/T | 459/128/13 | 448/145/7 | 0.1283 | 0.1325 | 0.2848 | 0.9602 | |
| rs17103109 | (S05) | T/G | 317/241/42 | 307/247/46 | 0.2708 | 0.2825 | 0.7629 | 0.5998 | |
| VIPR2 | rs2071623 | (S10) | G/A | 280/234/86 | 251/249/100 | 0.3383 | 0.3742 | 0.0053 | 0.0799 |
| rs2071625 | (S11) ‡ | A/G | 303/248/49 | 259/254/87 | 0.2883 | 0.3567 | 0.0616 | 0.0008 ‡ | |
| rs2730220 | (S12) | G/A | 508/82/10 | 477/114/9 | 0.0850 | 0.1100 | 0.4095 | 0.0409 | |
| rs885863 | (S13) | G/A | 396/178/26 | 399/186/15 | 0.1917 | 0.1800 | 0.2683 | 0.4076 | |
The tag SNPs are listed sequentially from the 5′ end to the 3′ end of the sense strand of the respective gene, and are also designated in this order as S01, S02, …., etc for the sake of easy referencing.
Allele 1 is the major allele, and allele 2 the minor allele.
In single-marker analysis, these two SNPs were significant even after correction for multiple comparisons: rs2730220 (S12) (P a = 0.0017 and P aemp = 0.0110) in the replication sample set; and rs2071625 (S11) ((P a = 0.0008 and P aemp = 0.0046) in the combined sample set.
Three control samples failed to be genotyped for rs4645869 even after repeated trials.
For candidate genes with two or more tag SNPs examined, we constructed LD patterns with Haploview and defined LD blocks by solid spine of LD. In general, LD between SNPs was very weak with no LD block identified for any of the four genes (FOS, JUN, VIP and VIPR2) examined for LD patterns (Figures S1A, S1D and S1E; and Figure 1A). Therefore, we performed haplotype analysis using an exhaustive sliding-window approach (Table 3). Of all the 123 possible sliding windows, 2 windows of the FOS gene and 13 windows of the VIPR2 gene displayed significant association (P aemp<0.05) with high myopia even after correction for multiple comparisons (n = 123) by permutation test. For the FOS gene, the most significant haplotype window was the 3-SNP window S03…S05 consisting of rs4645869, rs4645874 and rs17103109 (P a = 6.43×10−5 and P aemp = 0.0016). For the VIPR2 gene, the most significant haplotype window was the 4-SNP window S10…S14 made up of rs2071623, rs2071625, rs2730220 and rs885863 (P a = 8.47×10−8 and P aemp = 0.0001). We, therefore, followed up these 7 SNPs by genotyping an independent sample set – the replication sample set (Table 1).
Figure 1. Linkage disequilibrium (LD) patterns for single nucleotide polymorphisms of the VIPR2 gene.
LD measures are indicated as r2 values for cases and controls together for (a) the discovery sample set, (B) the replication sample, and (C) the combined sample set. Note that, as defined by solid spine of LD, no LD bock is identified in any of the sample sets.
Table 3. Summary of exhaustive haplotype analyses based on omnibus tests for sliding windows of all possible sizes across separate sets of tag SNPs of the candidate genes*.
| Sliding Window (SW) | SW with significant omnibus test P aemp<0.05 | The most significant result | ||||||
| Gene | SNPs/SW | No. of SW | No. of SW | First SW | Last SW | SW† | P a | P aemp‡ |
| Discovery sample set | ||||||||
| EGR1 | 1 | 1 | 0 | – | – | S01…S01 | 0.0816 | 0.9477 |
| FOS | 1 | 5 | 0 | – | – | S03…S03 | 0.0816 | 0.9477 |
| 2 | 4 | 0 | – | – | S03…S04 | 0.0023 | 0.0750 | |
| 3 | 3 | 1 | S03…S05 | S03…S05 | S03…S05 | 6.43×10−5 | 0.0016 | |
| 4 | 2 | 1 | S02…S05 | S02…S05 | S02…S05 | 0.0003 | 0.0070 | |
| 5 | 1 | 0 | – | – | S01…S05 | 0.0111 | 0.3371 | |
| JUN | 1 | 4 | 0 | – | – | S03…S03 | 0.4260 | 1.0000 |
| 2 | 3 | 0 | – | – | S01…S02 | 0.0022 | 0.0722 | |
| 3 | 2 | 0 | – | – | S01…S03 | 0.0026 | 0.0845 | |
| 4 | 1 | 0 | – | – | S01…S04 | 0.0065 | 0.2124 | |
| VIP | 1 | 3 | 0 | – | – | S01…S01 | 0.0237 | 0.5833 |
| 2 | 2 | 0 | – | – | S01…S02 | 0.1110 | 0.9820 | |
| 3 | 1 | 0 | – | – | S01…S03 | 0.1720 | 0.9981 | |
| VIPR2 | 1 | 13 | 0 | – | – | S06…S06 | 0.0060 | 0.1950 |
| 2 | 12 | 1 | S10…S11 | S10…S11 | S10…S11 | 1.82×10−5 | 0.0005 | |
| 3 | 11 | 3 | S09…S11 | S11…S13 | S11…S13 | 5.93×10−7 | 0.0001 | |
| 4 | 10 | 2 | S09…S12 | S10…S13 | S10…S13 | 8.47×10−8 | 0.0001 | |
| 5 | 9 | 1 | S09…S13 | S09…S13 | S09…S13 | 3.10×10−6 | 0.0002 | |
| 6 | 8 | 1 | S08…S13 | S08…S13 | S08…S13 | 6.87×10−6 | 0.0003 | |
| 7 | 7 | 2† | S05…S11 | S07…S13 | S07…S13 | 9.45×10−6 | 0.0003 | |
| 8 | 6 | 2 | S05…S12 | S06…S13 | S06…S13 | 1.05×10−4 | 0.0030 | |
| 9 | 5 | 1 | S05…S13 | S05…S13 | S05…S13 | 0.0008 | 0.0256 | |
| 10 | 4 | 0 | – | – | S03…S12 | 0.0071 | 0.2277 | |
| 11 | 3 | 0 | – | – | S03…S13 | 0.0321 | 0.6881 | |
| 12 | 2 | 0 | – | – | S02…S13 | 0.0333 | 0.7015 | |
| 13 | 1 | 0 | – | – | S01…S13 | 0.0524 | 0.8463 | |
| Replication sample set | ||||||||
| FOS | 1 | 3 | 0 | – | – | S05…S05 | 0.2290 | 0.8805 |
| 2 | 2 | 0 | – | – | S04…S05 | 0.0315 | 0.2334 | |
| 3 | 1 | 0 | – | – | S03…S05 | 0.3800 | 0.9781 | |
| VIPR2 | 1 | 4 | 1 | S12…S12 | S12…S12 | S12…S12 | 0.0017 | 0.0141 |
| 2 | 3 | 2 | S11…S12 | S12…S13 | S11…S12 | 0.0010 | 0.0076 | |
| 3 | 2 | 1 | S11…S13 | S11…S13 | S11…S13 | 0.0032 | 0.0246 | |
| 4 | 1 | 1 | S10…S13 | S10…S13 | S10…S13 | 1.15×10−5 | 0.0002 | |
| Combined sample set | ||||||||
| FOS | 1 | 3 | 0 | – | – | S05…S05 | 0.6020 | 0.9998 |
| 2 | 2 | 0 | – | – | S03…S04 | 0.2660 | 0.9184 | |
| 3 | 1 | 0 | – | – | S03…S05 | 0.1420 | 0.7269 | |
| VIPR2 | 1 | 4 | 1 | S11…S11 | S11…S11 | S11…S11 | 0.0009 | 0.0095 |
| 2 | 3 | 2 | S10…S11 | S11…S12 | S10…S11 | 7.51×10−5 | 0.0005 | |
| 3 | 2 | 2 | S10…S12 | S11…S13 | S11…S13 | 6.51×10−5 | 0.0004 | |
| 4 | 1 | 1 | S10…S13 | S10…S13 | S10…S13 | 9.10×10−10 | 0.0001 | |
The SW is indicated as Sxx…Syy, where Sxx is the first SNP and the Syy the last SNP of the SW. For each candidate gene, the identity of the SNPs (rs numbers) can be found in Table 2. Every SW is assessed by omnibus test adjusted for sex and age to give the P a value. For each fixed-size SW, the most significant result is detailed in the last three columns. For the discovery sample set, there are a total of 123 SWs across 26 SNPs of the five genes, and multiple comparisons are corrected by running 10,000 permutations to obtain an empirical P value that is also adjusted form sex and age (P aemp). For the replication sample set and the combined sample set, there are in each sample set 16 SWs across 7 SNPs of the two genes tested, and multiple comparisons are corrected by running 10,000 permutations to obtain the P aemp values. Note that the minimum P aemp value achievable with 10,000 permutations is 0.0001.
The SW S06…S12 is between S05…S11 and S07…S13, and is not significant for the omnibus test (P aemp>0.05). Abbreviations: SW, sliding window; P a, P value adjusted for sex and age; and P aemp, empirical P value adjusted for sex and age.
Replication sample set
We examined seven SNPs with the replication sample set (Table 1) in light of the significant haplotype association obtained with the discovery sample set. We summarize the genotype data of the replication sample set in Table 2. The control group was in HWE for all seven SNPs.
We did not find any significant association in single-marker analysis of FOS SNPs, not even when we jointly analyzed both sample sets (hereafter called the combined sample set) (Table 2). However, single-marker analysis of the replication sample set revealed significant association of rs2730220 (S12) of VIPR2 with high myopia even after correction for multiple testing across seven SNPs (P a = 0.0017 and P aemp = 0.0110). The OR of its minor allele A was 0.51 (95% CI, 0.34–0.78) with reference to its major allele G. Interestingly, instead of rs2730220 (S12), rs2071625 (S11) of VIPR2 demonstrated significant association with high myopia for the combined sample sets (P a = 0.0008 and P aemp = 0.0046) with the OR of its minor allele G being 0.75 (95% CI, 0.63–0.89).
LD between SNPs was also very weak for FOS and VIPR2 in both the replication sample set and the combined sample set (Figures S1B and S1C; and Figures 1B and 1C). We also did not identify any LD block for these sample sets. Exhaustive sliding-window haplotype analysis failed to demonstrate any significant association for FOS for both sample sets (Table 3). However, we were able to replicate significant haplotype association (P aemp<0.05) of VIPR2 with high myopia: five significant haplotype windows for the replication sample set and six significant haplotype windows for the combined sample set (Table 3). Most importantly, the same most significant VIPR2 haplotype window was identified as in the discovery sample set: S10…S13 consisting of rs2071623, rs2071625, rs2730220 and rs885863 (P a = 1.15×10−5 and P aemp = 0.0002 for the replication sample set; and P a = 9.10×10−10 and P aemp = 0.0001 for the combined sample set).
The most significant VIPR2 haplotype window
The 4-SNP haplotype window S10…S13 (rs2071623-rs2071625-rs2730220-rs885863) of VIPR2 was the most significant haplotype sliding window in the discovery sample set, the replication sample set and the combined sample set (Table 3). The constituent haplotypes of this sliding window are shown in Table 4. We did not observe any haplotypes displaying opposite directions of association in the discovery and the replication sample sets although the GAGA haplotype was found in the replication sample set, but not in the discovery sample set. Therefore, the directions of association of these 4-SNP haplotypes were compatible between the discovery and the replication sample sets.
Table 4. The most significant VIPR2 haplotype window in all sample sets: S10…S13 (rs2071623- rs2071625-rs2730220-rs885863) and the constituent haplotypes*.
| Discovery Sample Set | Replication Sample Set | Combined Sample Set | |||||||||||||
| Haplotype frequency | Haplotype frequency | Haplotype frequency | |||||||||||||
| Haplotypes | Cases | Controls | OR | P a | P aemp | Cases | Controls | OR | P a | P aemp | Cases | Controls | OR | P a | P aemp |
| Omnibus | - | - | - | 8.47×10−8 | 0.0001 | - | - | - | 1.15×10−5 | 0.0002 | - | - | - | 9.10×10−10 | 0.0001 |
| GGGG (1211) | 0.0298 | 0.1097 | 0.18 | 1.85×10−6 | 0.0002 | 0.1764 | 0.2221 | 0.72 | 0.0383 | 0.0600 | 0.0982 | 0.1608 | 0.52 | 3.37×10−6 | 0.0002 |
| GAGA (1112) | - | - | - | - | - | 0.0733 | 0.0164 | 14.40 | 1.30×10−6 | 0.0001 | 0.0368 | 0.0145 | 4.68 | 0.0001 | 0.0027 |
| GAGG (1111) | 0.5510 | 0.4448 | 1.40 | 0.0032 | 0.4415 | 0.3812 | 0.3746 | 1.06 | 0.6250 | 1.0000 | 0.4707 | 0.4132 | 1.27 | 0.0049 | 0.1297 |
| AAGA (2112) | 0.0163 | 0.0641 | 0.14 | 7.15×10−5 | 0.0082 | 0.0734 | 0.0843 | 0.82 | 0.4290 | 1.0000 | 0.0475 | 0.0698 | 0.55 | 0.0055 | 0.1430 |
| GGGA (1212) | 0.0281 | 0.0299 | 1.00 | 0.9940 | 1.0000 | 0.0273 | 0.0050 | 82.50 | 0.0011 | 0.0251 | 0.0309 | 0.0164 | 2.54 | 0.0083 | 0.2048 |
| AGAG (2221) | 0.0352 | 0.0501 | 0.63 | 0.1600 | 1.0000 | 0.0085 | 0.0200 | 0.16 | 0.0271 | 0.4754 | 0.0238 | 0.0385 | 0.53 | 0.0272 | 0.4993 |
Only haplotypes with P a<0.05 in the combined sample set are listed here and in the order of increasing P a values. Haplotypes and their corresponding statistics are indicated in boldface if their P aemp values are <0.05 in the combined sample set. Note that the OR of a haplotype is calculated with reference to the remaining haplotypes. This means that the reference haplotypes are different for different haplotypes. In addition, PLINK calculates the OR of a given haplotype without providing the 95% confidence intervals. Abbreviations: OR, odds ratio; P a, P value adjusted for sex and age, and also for sample set for the combined sample set; P aemp, empirical P a value (corrected for multiple testing by permutation test); 1, major allele; and 2, minor allele.
In the combined sample set, GGGG (1211) was a protective haplotype with an OR of 0.52 (P a = 3.37×10−6 and P aemp = 0.0002) and GAGA (1112) a high-risk haplotype with an OR of 4.68 (P a = 0.0001 and P aemp = 0.0027). Note that the haplotypes are indicated in both the ACGT and the 1–2 (major-minor) formats. The GGGG (1211) haplotype had a frequency of 9.82% in cases and 16.08% in controls. The GAGA (1112) haplotype was much less common with a frequency of 3.68% in cases and 1.45% in controls.
Discussion
Previous studies indicate that genes responsive to visual signals are involved in the early part of the biological pathways concerned with altered ocular growth while genes responsible for ECM remodeling of the sclera participate in the later part of the pathways [29]–[31]. Therefore, we selected EGR1, FOS, JUN, VIP and VIPR2 as functional candidates and investigated their potential association with high myopia. We assumed a “common disease common variants” model [43] in this study and hence selected SNPs, the most abundant sequence variation in the human genome, as the genetic markers for the present genetic association study.
We performed haplotype analysis in addition to single-marker analysis. In the absence of LD block defined for the genes under study (Figures S1 and 1), we used the variable-sized sliding-window strategy to further explore possible association by comprehensively examining haplotype windows of all possible sizes. This strategy has been shown to be more powerful in detecting genetic association than single-marker analysis and LD-block-based haplotype analysis [44]. This is particularly true for genomic regions of low LD such as candidate loci evaluated in this study (Figures S1 and 1).
We did not find any evidence to support the role of ERG1, FOS, JUN and VIP in the genetic susceptibility to high myopia (Tables 2 and 3). We failed to confirm with the replication sample set the initial significant association of FOS haploypes with high myopia in the discovery sample set. Our EGR1 data complement a recent study that assumed a “common disease rare variants” model and did not find any pathological mutation in the EGR1 coding regions by DNA sequencing of 96 Chinese subjects with high myopia [45].
On the contrary, we first found the significant association of VIPR2 haplotypes with high myopia in the discovery sample set and then successfully replicated the significant association in the replication sample set (Tables 2 and 3). We found it reassuring that the haplotype window S10…S13 (rs2071623-rs2071625-rs2730220-rs885863) was the most significant sliding window among all possible haplotype windows examined in the discovery, the replication and the combined sample sets (Table 3). Although the haplotype GAGA (1112) of the S10…S13 window was significant in the replication sample set, it was not found in the discovery sample set (Table 4). Other than this, the directions of association were consistent for the haplotypes identified in the discovery and the replication sample sets. In the combined sample set, we identified one protective haplotype (GGGG or 1211, OR = 0.52) and one high-risk haplotype (GAGA or 1112, OR = 4.68). The high-risk haplotype GAGA was much less common particularly in the controls: 1.64% (∼20 chromosomes out of 1200 chromosomes) in the discovery sample set and 1.45% (∼17 chromosomes out of 1200 chromosomes) in the replication sample set. Note that analysis for this rare haplotype might be subject to random variation.
In the combined sample set, the four constituent SNPs of the VIPR2 S10…S13 window each contributed independent effects to the significant haplotype association as shown by conditional logistic regression: P = 5.37×10−8 for S10 (rs2071623), P = 4.31×10−7 for S11 (rs2071625), P = 0.0181 for S12 (rs2730220) and P = 1.09×10−8 for S13 (rs885863). We note that these four SNPs are located at the 3′ end of the VIPR2 gene (Figure S2). This region harbors a few sequence features that may be important in regulating the expression of VIPR2.
The importance of S11 (rs2071625) was highlighted by its significant association in single-marker analysis (Table 2) and its being a constituent SNP in all significant haplotype windows (Table 3) in the combined sample set. In the discovery sample set, S11 (rs2071625) was the only SNP included in all 13 significant haplotype windows (Table 3) even though it was not associated with high myopia as a single marker (Table 2). On the other hand, S12 (rs2730220) stood out in the replication sample set because of its significant association as a single marker. In both scenarios, association was statistically more significant with haplotype windows than with single markers. Therefore, we speculate that these SNPs or their haplotypes are more likely tagging some untyped causal variants that drive the genuine association with high myopia. Nevertheless, some databases (e.g., Patrocles, http://www.patrocles.org/Patrocles_targets.htm; and FuncPred, http://manticore.niehs.nih.gov/snpinfo/snpfunc.htm) predict that S12 (rs2730220) and S13 (rs885863) may affect the binding of certain microRNAs and hence influence the expression of VIPR2 accordingly. Despite these predictions, we doubt the involvement of these SNPs as causal variants in the genetic susceptibility to high myopia. Therefore, we recommend that future studies be aimed at identifying the causal variants. Since this is also the first study that has identified VIPR2 as a myopia susceptibility gene, our positive results should be replicated using samples from other populations, particularly those of different ethnicities.
VIPR2, also known as VPAC2, is located on chromosome 7q36 and lies within a putative locus for autosomal dominant high myopia (once called MYP4) [37], [38]. As a G-protein coupled receptor, VIPR2 is in fact a receptor for VIP. The expression of VIPR2 in the retina and the choroid was up-regulated in the treated eyes with reference to the fellow control eyes, but down-regulated with increasing axial length in chicks with form-deprivation myopia [39]. An unselective antagonist of VIP receptors (including VIPR2) could also suppress the development of form-deprivation myopia in chicks in a dose-dependent manner [46]. VIPR2 is also an input gene involved in circadian networks. Intriguingly, some studies have shown that transgenic mice over-expressing or lacking VIPR2 show deranged circadian rhythms [47]–[49]. Interestingly, growing eyes of chicks and monkeys display a diurnal rhythm in axial length, which is in anti-phase with the rhythm in choroidal thickness [50]. These phases are distorted in eyes that grow too fast or too slowly. Therefore, we speculate that VIPR2 may influence genetic susceptibility to myopia through its involvement in circadian rhythms. In light of the significant association between VIPR2 gene polymorphisms with high myopia, this hypothesis is worth exploring in future studies.
In summary, EGR1, JUN, FOS and VIP were not associated with high myopia. However, we identified VIPR2 as a novel myopia susceptibility gene. We obtained consistent results with sliding-window haplotype analysis and the S10…S13 haplotype window (rs2071623-rs2071625-rs2730220-rs885863) was the most significant sliding window in all sample sets. In combined sample set, S11 (rs2071625) also showed significant association with high myopia as a single marker.
Supporting Information
Linkage disequilibrium (LD) patterns for single nucleotide polymorphisms of FOS, JUN and VIP.
(PDF)
Sequence features at the 3′ end of the VIPR2 locus.
(PDF)
SNP genotyping: restriction enzymes, and sequences of primers, extension primer, and probes used.
(DOC)
Genotyping of single nucleotide polymorphisms (SNPs).
(DOC)
Acknowledgments
This work is a contribution from the Centre for Myopia Research of The Hong Kong Polytechnic University. We thank all the subjects participating in our myopia genetics study. The discovery study of this work was presented in the 13th International Myopia Conference in Tubingen, Germany, in 26–29 July 2010.
Funding Statement
This work is a contribution from the Centre for Myopia Research of The Hong Kong Polytechnic University, and was supported by grants from The Hong Kong Polytechnic University (RP3C, JBB7P, G-U730, 87TP and 1.55.xx.99NE). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1. Pan CW, Ramamurthy D, Saw SM (2012) Worldwide prevalence and risk factors for myopia. Ophthalmic Physiol Opt 32: 3–16. [DOI] [PubMed] [Google Scholar]
- 2.Amos JF (1987) Diagnosis and management in vision care. Boston: Butterworths. 729 p.
- 3. Saw SM, Gazzard G, Shih-Yen EC, Chua WH (2005) Myopia and associated pathological complications. Ophthalmic Physiol Opt 25: 381–391. [DOI] [PubMed] [Google Scholar]
- 4. Tang WC, Yap MK, Yip SP (2008) A review of current approaches to identifying human genes involved in myopia. Clin Exp Optom 91: 4–22. [DOI] [PubMed] [Google Scholar]
- 5. Wojciechowski R (2011) Nature and nurture: the complex genetics of myopia and refractive error. Clin Genet 79: 301–320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Low W, Dirani M, Gazzard G, Chan YH, Zhou HJ, et al. (2010) Family history, near work, outdoor activity, and myopia in Singapore Chinese preschool children. Br J Ophthalmol 94: 1012–1016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Young TL, Ronan SM, Alvear AB, Wildenberg SC, Oetting WS, et al. (1998) A second locus for familial high myopia maps to chromosome 12q. Am J Hum Genet 63: 1419–1424. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Young TL, Ronan SM, Drahozal LA, Wildenberg SC, Alvear AB, et al. (1998) Evidence that a locus for familial high myopia maps to chromosome 18p. Am J Hum Genet 63: 109–119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Zha Y, Leung KH, Lo KK, Fung WY, Ng PW, et al. (2009) TGFB1 as a susceptibility gene for high myopia: a replication study with new findings. Arch Ophthalmol 127: 541–548. [DOI] [PubMed] [Google Scholar]
- 10. Jiang B, Yap MK, Leung KH, Ng PW, Fung WY, et al. (2011) PAX6 haplotypes are associated with high myopia in Han Chinese. PLoS One 6: e19587. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Mak JY, Yap MK, Fung WY, Ng PW, Yip SP (2012) Association of IGF1 gene haplotypes with high myopia in Chinese adults. Arch Ophthalmol 130: 209–216. [DOI] [PubMed] [Google Scholar]
- 12. Hysi PG, Young TL, Mackey DA, Andrew T, Fernández-Medarde A, et al. (2010) A genome-wide association study for myopia and refractive error identifies a susceptibility locus at 15q25. Nat Genet 42: 902–905. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Solouki AM, Verhoeven VJ, van Duijn CM, Verkerk AJ, Ikram MK, et al. (2010) A genome-wide association study identifies a susceptibility locus for refractive errors and myopia at 15q14. Nat Genet 42: 897–901. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Li YJ, Goh L, Khor CC, Fan Q, Yu M, et al. (2011) Genome-wide association studies reveal genetic variants in CTNND2 for high myopia in Singapore Chinese. Ophthalmology 118: 368–375. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Fan Q, Barathi VA, Cheng CY, Zhou X, Meguro A, et al. (2012) Genetic variants on chromosome 1q41 influence ocular axial length and high myopia. PLoS Genet 8: e1002753. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Mayer DL, Hansen RM, Moore BD, Kim S, Fulton AB (2001) Cycloplegic refractions in healthy children aged 1 through 48 months. Arch Ophthalmol 119: 1625–1628. [DOI] [PubMed] [Google Scholar]
- 17. Matsumura H, Hirai H (1999) Prevalence of myopia and refractive changes in students from 3 to 17 years of age. Surv Ophthalmol 44 Suppl 1: S109–S115. [DOI] [PubMed] [Google Scholar]
- 18. McBrien NA, Gentle A (2003) Role of the sclera in the development and pathological complications of myopia. Prog Retin Eye Res 22: 307–338. [DOI] [PubMed] [Google Scholar]
- 19. Rada JA, Shelton S, Norton TT (2006) The sclera and myopia. Exp Eye Res 82: 185–200. [DOI] [PubMed] [Google Scholar]
- 20. Metlapally R, Li YJ, Tran-Viet KN, Abbott D, Czaja GR, et al. (2009) COL1A1 and COL2A1 genes and myopia susceptibility: evidence of association and suggestive linkage to the COL2A1 locus. Invest Ophthalmol Vis Sci 50: 4080–4086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Chen ZT, Wang IJ, Shih YF, Lin LL (2009) The association of haplotype at the lumican gene with high myopia susceptibility in Taiwanese patients. Ophthalmology 116: 1920–1927. [DOI] [PubMed] [Google Scholar]
- 22. Wojciechowski R, Bailey-Wilson JE, Stambolian D (2010) Association of matrix metalloproteinase gene polymorphisms with refractive error in Amish and Ashkenazi families. Invest Ophthalmol Vis Sci 51: 4989–4995. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Leung KH, Yiu WC, Yap MK, Ng PW, Fung WY, et al. (2011) Systematic investigation of the relationship between high myopia and polymorphisms of the MMP2, TIMP2, and TIMP3 genes by a DNA pooling approach. Invest Ophthalmol Vis Sci 52: 3893–3900. [DOI] [PubMed] [Google Scholar]
- 24. Raviola E, Wiesel TN (1985) An animal model of myopia. N Engl J Med 312: 1609–1615. [DOI] [PubMed] [Google Scholar]
- 25. Wallman J, Gottlieb MD, Rajaram V, Fugate-Wentzek LA (1987) Local retinal regions control local eye growth and myopia. Science 237: 73–77. [DOI] [PubMed] [Google Scholar]
- 26. Rymer J, Wildsoet CF (2005) The role of the retinal pigment epithelium in eye growth regulation and myopia: a review. Vis Neurosci 22: 251–261. [DOI] [PubMed] [Google Scholar]
- 27. Fischer AJ, McGuire JJ, Schaeffel F, Stell WK (1990) Light- and focus-dependent expression of the transcription factor ZENK in the chick retina. Nat Neurosci 2: 706–712. [DOI] [PubMed] [Google Scholar]
- 28. Bitzer M, Schaeffel F (2002) Defocus-induced changes in ZENK expression in the chicken retina. Invest Ophthalmol Vis Sci 43: 246–252. [PubMed] [Google Scholar]
- 29. Brand C, Burkhardt E, Schaeffel F, Choi JW, Feldkaemper MP (2005) Regulation of Egr-1, VIP, and Shh mRNA and Egr-1 protein in the mouse retina by light and image quality. Mol Vis 11: 309–320. [PubMed] [Google Scholar]
- 30. Schippert R, Burkhardt E, Feldkaemper M, Schaeffel F (2007) Relative axial myopia in Egr-1 (ZENK) knockout mice. Invest Ophthalmol Vis Sci 48: 11–17. [DOI] [PubMed] [Google Scholar]
- 31. Dragunow M, Faull R (1989) The use of c-fos as a metabolic marker in neuronal pathway tracing. J Neurosci Methods 29: 261–265. [DOI] [PubMed] [Google Scholar]
- 32. White LA, Brinckerhoff CE (1995) Two activator protein-1 elements in the matrix metalloproteinase-1 promoter have different effects on transcription and bind Jun D, c-Fos, and Fra-2. Matrix Biol 14: 715–725. [DOI] [PubMed] [Google Scholar]
- 33. Edwards DR, Rocheleau H, Sharma RR, Wills AJ, Cowie A, et al. (1992) Involvement of AP1 and PEA3 binding sites in the regulation of murine tissue inhibitor of metalloproteinases-1 (TIMP-1) transcription. Biochim Biophys Acta 1171: 41–55. [DOI] [PubMed] [Google Scholar]
- 34. Yang-Yen HF, Zhang XK, Graupner G, Tzukerman M, Sakamoto B, et al. (1991) Antagonism between retinoic acid receptors and AP-1: implications for tumor promotion and inflammation. New Biol 3: 1206–1219. [PubMed] [Google Scholar]
- 35. Mori M, Ghyselinck NB, Chambon P, Mark M (2001) Systematic immunolocalization of retinoid receptors in developing and adult mouse eyes. Invest Ophthalmol Vis Sci 42: 1312–1318. [PubMed] [Google Scholar]
- 36. Tkatchenko AV, Walsh PA, Tkatchenko TV, Gustincich S, Raviola E (2006) Form deprivation modulates retinal neurogenesis in primate experimental myopia. Proc Natl Acad Sci USA 103: 4681–4686. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Naiglin L, Gazagne C, Dallongeville F, Thalamas C, Idder A, et al. (2002) A genome wide scan for familial high myopia suggests a novel locus on chromosome 7q36. J Med Genet 39: 118–124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Li YJ, Guggenheim JA, Bulusu A, Metlapally R, Abbott D, et al. (2009) An international collaborative family-based whole-genome linkage scan for high-grade myopia. Invest Ophthalmol Vis Sci 50: 3116–3127. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Liu SZ, Wang H, Jiang JJ, Wang PB, Wu XY, et al. (2005) [Dynamic expression of VIPR2 in form deprivation myopia]. Zhong Nan Da Xue Xue Bao Yi Xue Ban 30: 456–459. [PubMed] [Google Scholar]
- 40. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81: 559–575. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Wigginton JE, Cutler DJ, Abecasis GR (2005) A note on exact tests of Hardy-Weinberg equilibrium. Am J Hum Genet 76: 887–893. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21: 263–265. [DOI] [PubMed] [Google Scholar]
- 43. Bodmer W, Bonilla C (2008) Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet 40: 695–701. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44. Guo Y, Li J, Bonham AJ, Wang Y, Deng H (2009) Gains in power for exhaustive analyses of haplotypes using variable-sized sliding window strategy: a comparison of association-mapping strategies. Eur J Hum Genet 17: 785–792. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Li T, Xiao X, Li S, Xing Y, Guo X, et al. (2008) Evaluation of EGR1 as a candidate gene for high myopia. Mol Vis 14: 1309–1312. [PMC free article] [PubMed] [Google Scholar]
- 46. Wang PB, Wang H, Liu SZ, Jiang JJ (2008) [Effect of vasoactive intestinal peptide receptor antagonist VIPhybrid on the development of form deprivation myopia in chicks]. Zhong Nan Da Xue Xue Bao Yi Xue Ban 33: 669–675. [PubMed] [Google Scholar]
- 47. Shen S, Spratt C, Sheward WJ, Kallo I, West K, et al. (2000) Overexpression of the human VPAC2 receptor in the suprachiasmatic nucleus alters the circadian phenotype of mice. Proc Natl Acad Sci USA 97: 11575–11580. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Hughes AT, Fahey B, Cutler DJ, Coogan AN, Piggins HD (2004) Aberrant gating of photic input to the suprachiasmatic circadian pacemaker of mice lacking the VPAC2 receptor. J Neurosci 24: 3522–3526. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Harmar AJ, Marston HM, Shen S, Spratt C, West KM, et al. (2000) The VPAC(2) receptor is essential for circadian function in the mouse suprachiasmatic nuclei. Cell 109: 497–508. [DOI] [PubMed] [Google Scholar]
- 50. Nickla DL (2013) Ocular diurnal rhythms and eye growth regulation: Where we are 50 years after Lauber. Exp Eye Res 2013 [Epub ahead of print] doi: 10.1016/j.exer.2012.12.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Linkage disequilibrium (LD) patterns for single nucleotide polymorphisms of FOS, JUN and VIP.
(PDF)
Sequence features at the 3′ end of the VIPR2 locus.
(PDF)
SNP genotyping: restriction enzymes, and sequences of primers, extension primer, and probes used.
(DOC)
Genotyping of single nucleotide polymorphisms (SNPs).
(DOC)