November 2014
Volume 55, Issue 11
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Genetics  |   November 2014
Comprehensive Replication of the Relationship Between Myopia-Related Genes and Refractive Errors in a Large Japanese Cohort
Author Affiliations & Notes
  • Munemitsu Yoshikawa
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Kenji Yamashiro
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Masahiro Miyake
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Maho Oishi
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Yumiko Akagi-Kurashige
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Kyoko Kumagai
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Isao Nakata
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Hideo Nakanishi
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Akio Oishi
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Norimoto Gotoh
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Ryo Yamada
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Fumihiko Matsuda
    Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Nagahisa Yoshimura
    Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Shogoin, Sakyo-ku, Kyoto, Japan
  • Correspondence: Kenji Yamashiro, Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan; yamashro@kuhp.kyoto-u.ac.jp
Investigative Ophthalmology & Visual Science November 2014, Vol.55, 7343-7354. doi:10.1167/iovs.14-15105
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      Munemitsu Yoshikawa, Kenji Yamashiro, Masahiro Miyake, Maho Oishi, Yumiko Akagi-Kurashige, Kyoko Kumagai, Isao Nakata, Hideo Nakanishi, Akio Oishi, Norimoto Gotoh, Ryo Yamada, Fumihiko Matsuda, Nagahisa Yoshimura, for the Nagahama Study Group; Comprehensive Replication of the Relationship Between Myopia-Related Genes and Refractive Errors in a Large Japanese Cohort. Invest. Ophthalmol. Vis. Sci. 2014;55(11):7343-7354. doi: 10.1167/iovs.14-15105.

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

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Abstract

Purpose.: We investigated the association between refractive error in a Japanese population and myopia-related genes identified in two recent large-scale genome-wide association studies.

Methods.: Single-nucleotide polymorphisms (SNPs) in 51 genes that were reported by the Consortium for Refractive Error and Myopia and/or the 23andMe database were genotyped in 3712 healthy Japanese volunteers from the Nagahama Study using HumanHap610K Quad, HumanOmni2.5M, and/or HumanExome Arrays. To evaluate the association between refractive error and recently identified myopia-related genes, we used three approaches to perform quantitative trait locus analyses of mean refractive error in both eyes of the participants: per-SNP, gene-based top-SNP, and gene-based all-SNP analyses. Association plots of successfully replicated genes also were investigated.

Results.: In our per-SNP analysis, eight myopia gene associations were replicated successfully: GJD2, RASGRF1, BICC1, KCNQ5, CD55, CYP26A1, LRRC4C, and B4GALNT2.Seven additional gene associations were replicated in our gene-based analyses: GRIA4, BMP2, QKI, BMP4, SFRP1, SH3GL2, and EHBP1L1. The signal strength of the reported SNPs and their tagging SNPs increased after considering different linkage disequilibrium patterns across ethnicities. Although two previous studies suggested strong associations between PRSS56, LAMA2, TOX, and RDH5 and myopia, we could not replicate these results.

Conclusions.: Our results confirmed the significance of the myopia-related genes reported previously and suggested that gene-based replication analyses are more effective than per-SNP analyses. Our comparison with two previous studies suggested that BMP3 SNPs cause myopia primarily in Caucasian populations, while they may exhibit protective effects in Asian populations.

Introduction
Myopia is one of the most common ocular disorders worldwide. Recent studies reported that the prevalence of myopia is much higher in East Asian populations (40%–70%) than in Caucasian populations (20%–42%).13 Additionally, the prevalence of high myopia, which could give rise to various ocular complications and lead to blindness, also is much higher in East Asian populations.48 However, the regional and/or ethnic differences in the genetic background of myopia between Asians and Caucasians have not been fully investigated. 
Previously, several candidate loci have been identified using family-based linkage analyses or twin studies; however, the mechanisms underlying myopia development have not been fully elucidated through these findings.9 Research on myopia-related genetic regions has progressed greatly after genome-wide association studies (GWASs) have been performed for myopia.10 To date, more than 10 GWASs have identified several genes associated with myopia or related phenotypes; two of these were 15q14 and 15q25, which showed potent and consistent associations beyond regional and racial variations.1120. Among them, the two largest GWASs, published in 2013 by the Consortium for Refractive Error and Myopia (CREAM) and the 23andMe database, identified as many as 51 genes that account for most of the myopia-related genes that have ever been reported by GWASs.19,20 
In the CREAM GWAS discovery stage, 21 single-nucleotide polymorphisms (SNPs) from the Caucasian dataset and eight SNPs from the combined datasets of Caucasians and Asians showed significant associations with refractive error. Although 23andMe performed GWASs for the age of myopia onset using only Caucasians, these two studies showed remarkable overlaps in the associated SNPs and even in their effect sizes.21 Further replication studies in different populations would narrow down the target genes and help elucidate variable genetic backgrounds in myopia across ethnicities. 
In this study, we analyzed myopia-related genes that were reported by these two GWASs as disease-susceptible polymorphisms related to refractive error in a relatively large Japanese cohort. We analyzed 51 genes, even ones with marginal significance or without successful replication in their dataset, so that the genes that contribute dominantly to Asian myopia would not be eliminated. In addition, three replication methods including gene-based approaches were performed to avoid excluding the genes by the heterogeneous distribution of SNP associations or different linkage disequilibrium (LD) patterns across ethnicities. 
Methods
All procedures used in this study adhered to the tenets of the Declaration of Helsinki. The institutional review board and ethics committee of Kyoto University Graduate School and the Faculty of Medicine Ethics Committee, the Ad Hoc Review Board of the Nagahama Cohort Project, and the Nagahama Municipal Review Board of Personal Information Protection approved the protocols of this study. All participants were fully informed of the purpose of and procedures involved in this study, and written informed consent was obtained from each participant. 
Study Populations
The individuals studied were healthy Japanese volunteers enrolled in the Nagahama Prospective Genome Cohort for the Comprehensive Human Bioscience dataset (The Nagahama Study, n = 9809). This community-based prospective multi-omics cohort study has been described in detail previously.22,23 This cohort was recruited from the general population living in Nagahama City, a large rural city of 125,000 inhabitants in the Shiga Prefecture, located in the center of Japan. All participants voluntarily joined the study, which resulted in the difference in the number of participants of each sex. All eligible participants were included in this study and underwent ophthalmic evaluations: automatic objective refractometry and corneal curvature calculation (Autorefractor ARK-530; Nidek, Tokyo, Japan), axial length (AL) measurement (IOL Master; Carl Zeiss, Jena, Germany), and fundus photography using a digital retinal camera (CR-DG10; Canon, Tokyo, Japan) in a darkened room.24 History of cataract surgery, ocular surgery other than cataract surgery, and ocular laser treatment including photocoagulation were obtained through a questionnaire. Anthropometric parameters and genomic information also were available. We excluded participants with history of any intraocular procedures that could distort the mean spherical equivalent (MSE). Only participants with analyzable spherical equivalent refraction in both eyes were included in this study. 
Genotyping and Imputation
The DNA samples were prepared and genotyped as described previously.25 Briefly, 3712 samples were genotyped using at least one of the three genotyping platforms, HumanHap610K Quad Arrays, HumanOmni2.5M Arrays, or HumanExome Arrays (Illumina, Inc., San Diego, CA, USA). To ensure high-quality genotype data, a series of quality control (QC) filters were applied to the data in each platform: sample success rate (>90% for HumanHap610K Arrays, >95% for HumanOmni2.5M Arrays, and >99% for HumanExome Arrays), individual call rate (>99%), minor allele frequency (MAF) cutoffs (>0.01), P value for the Hardy-Weinberg test of equilibrium (>1 × 10−6), and estimated relatedness (PI-HAT < 0.35). After these preliminary QC procedures were performed using PLINK (ver. 1.07; available in the public domain at http://pngu.mgh.harvard.edu/~purcell/plink/), SNP genotype imputation was conducted for these samples using the MaCH program (version 1.0.10; available in the public domain at http://www.sph.umich.edu/csg/abecasis/MACH/) with 500 Markov sampler rounds and 200 haplotype states.26 Genotypes of East Asian samples in the 1000 Genomes Project (release3) were set as reference sequences and standard QC was applied again to the postimputed dataset (sample success rate [>90%], individual call rate [>90%], MAF cutoffs [>0.01], and HWE P value [>1 × 10−7]). The SNPs with low imputation quality (r2 < 0.5) were excluded from the following association analysis. 
Myopia-Related Genes and SNPs and the Methods Used for Replication
From the previously reported results for myopia in the two largest GWASs, we included 51 genes that showed associations in at least one GWAS, even without successful replication in their dataset. These genes included 61 SNPs (henceforth referred to as “myopia-related genes and SNPs”). To replicate these myopia-related genes and SNPs, we conducted GWAS for MSE refraction of both eyes using our dataset. These association results were adapted to the replication analysis in three different approaches: one was SNP-based replication and the others involved gene-based replications. Each method is illustrated in Figure 1. For the per-SNP replication method, we directly examined myopia-related SNPs or SNPs with complete LD (r2 = 1) in our dataset. The LD between associated SNPs and SNPs from 1000 Genomes Pilot 1 of CHB/JPT was calculated using the SNAP software (available in the public domain at http://www.broadinstitute.org/mpg/snap/ldsearch.php). A P value of <0.05 was considered statistically significant. The SNPs were excluded from this analysis if neither the original SNP nor the SNP with complete LD was included in our dataset. For gene-based replications, we conducted two methods: one was gene-based top-SNP replication and the other was gene-based all-SNP replication reflecting association signals of all SNPs. For gene-based top-SNP replication, we selected SNPs that showed the strongest association for MSE within each genetic region ±50 kb of myopia-related genes. The P value was multiplied by the number of tagging SNPs and a corrected P value of <0.05 was considered statistically significant. All of the imputed SNP genotypes in our dataset were imported into Haploview 4.2 to obtain the r2- and D'-based LD plots for each genetic region. Haplotype blocks were defined by the confidential blocks and the number of tagging SNPs was manually counted from these LD plots.27 For gene-based all-SNP replication, we used the VEGAS software (available in the public domain at http://gump.qimr.edu.au/VEGAS/) that incorporated information from all SNPs within each genetic region ±50 kb.28 Gene associations with MSE were calculated from the list of SNPs and their P values in our dataset. This software provides powerful information on whether multiple risk variants exist within a gene.29,30 
Figure 1
 
Description and illustration of three replication methods used in our analysis, using BMP2 as an example. (A) Definitions of the three methods are summarized. (B, C) Association plots of the SNPs near BMP2 in our dataset, showing the target SNPs of per-SNP analysis (B) and gene-based top-SNP analysis (C). Genetic regions Image not available 200 kb are shown in each plot. (D) An LD plot within the genetic region Image not available 50 kb of BMP2, comprised of 240 SNPs in our dataset. Totals of 17 haplotype blocks and 19 SNPs were not included in any of the blocks. Thus, the number of tag-SNPs was counted to be 36 ( = 17 + 19). The top SNP of BMP2 that is shown in (C) should be corrected by the number of tag-SNPs and a P value of < 0.0014 ( = 0.05/36) would be significant for gene-based top-SNP analysis.
Figure 1
 
Description and illustration of three replication methods used in our analysis, using BMP2 as an example. (A) Definitions of the three methods are summarized. (B, C) Association plots of the SNPs near BMP2 in our dataset, showing the target SNPs of per-SNP analysis (B) and gene-based top-SNP analysis (C). Genetic regions Image not available 200 kb are shown in each plot. (D) An LD plot within the genetic region Image not available 50 kb of BMP2, comprised of 240 SNPs in our dataset. Totals of 17 haplotype blocks and 19 SNPs were not included in any of the blocks. Thus, the number of tag-SNPs was counted to be 36 ( = 17 + 19). The top SNP of BMP2 that is shown in (C) should be corrected by the number of tag-SNPs and a P value of < 0.0014 ( = 0.05/36) would be significant for gene-based top-SNP analysis.
Statistical Analysis
The associations between MSE and SNP genotypes were analyzed as a quantitative trait using linear regression analysis in PLINK, assuming additive regression models with adjustment for age, sex, and principal components. Statistical significance of each replication method was assessed as stated above. Deviations from the Hardy-Weinberg equilibrium (HWE) in genotype distributions were assessed using the HWE exact test. We further highlighted regional association signals near the replicated genes to visualize the effect of different LD across ethnicities using LocusZoom.31 
Results
A total of 3655 individuals passed a series of QC filters after genotyping, and 3082 individuals were analyzed, excluding those with conditions as stated above. The evaluated genomic variances were 6,746,251 SNPs after imputation and QC. The demographics of the study population are shown in Table 1. The age of the subjects ranged from 30 to 75 years, with spherical equivalent refraction ranging from −15.38 to +7.44 diopters (D) with an MSE of −1.69 ± 2.78 D. Subgroup analysis of MSE by age suggested that the refractive status could be shifted to a hyperopic state in older populations. In addition, female subgroups had significantly (P = 0.023) higher myopic refraction compared to male subgroups (Table 2), suggesting that the analysis should be performed with adjustment for age and sex in the linear regression analysis. The genomic inflation factor (λ) in our cohort was 1.055 after including the first two principal components as covariates, suggesting proper adjustment for population stratification. 
Table 1
 
Characteristics of the Study Population According to Age
Table 1
 
Characteristics of the Study Population According to Age
30–39 y 40–49 y 50–59 y 60–69 y 70–75 y Total
Patients, n 1047 367 518 874 276 3082
Age,* y 34.60 ± 2.76 44.24 ± 2.87 55.17 ± 2.88 64.4 ± 2.93 72.2 ± 1.57 51.02 ± 14.09 (30–5)
Sex, n (%)
 Male 294 (28.1) 124 (33.8) 152 (29.3) 338 (38.7) 121 (43.8) 1029 (33.4)
 Female 753 (71.9) 243 (66.2) 518 (70.7) 536 (61.3) 155 (56.2) 2053 (66.6)
MSE,* D (range) −2.63 ± 2.53 (−13.25–7.44) −2.75 ± 2.82 (−15.38–2.19) −1.84 ± 2.81 (−15.69–6.69) −0.75 ± 2.52 (−14.81–4.38) 0.20 ± 2.28 (−13.31–4.63) −1.72 ± 2.78 (−15.69–7.44)
 Right eyes −2.66 ± 2.58 −2.82 ± 2.90 −1.90 ± 2.89 −0.78 ± 2.60 0.18 ± 2.44 −1.76 ± 2.85
 Left eyes −2.59 ± 2.52 −2.68 ± 2.79 −1.78 ± 2.84 −0.71 ± 2.56 0.22 ± 2.40 −1.68 ± 2.80
AL,* mm (range) 24.51 ± 1.30 (20.47–28.92) 24.54 ± 1.40 (21.92–28.99) 23.98 ± 1.37 (21.03–29.80) 23.70 ± 1.19 (21.07–28.37) 23.41 ± 1.11 (21.29–28.83) 24.10 ± 1.34 (20.47–29.80)
 Right eyes 24.53 ± 1.32 24.57 ± 1.44 24.00 ± 1.38 23.72 ± 1.21 23.42 ± 1.14 24.12 ± 1.36
 Left eyes 24.48 ± 1.30 24.51 ± 1.37 23.96 ± 1.40 23.69 ± 1.20 23.39 ± 1.11 24.08 ± 1.35
Table 2
 
Characteristics of the Study Population According to Sex
Table 2
 
Characteristics of the Study Population According to Sex
Male Female P
Patients, n 1029 2053
Age,* y 53.02 ± 14.24 50.02 ± 13.91 <0.001
MSE,* D (range) −1.56 ± 2.68 (−14.75–7.44) −1.80 ± 2.82 (−15.69–6.69) 0.023
 Right eyes −1.59 ± 2.75 −1.85 ± 2.90 0.020
 Left eyes −1.53 ± 2.71 −1.75 ± 2.83 0.039
AL,* mm (range) 24.37 ± 1.32 (21.06–9.80) 23.96 ± 1.33 (20.47–8.99) <0.001
 Right eyes 24.39 ± 1.35 23.98 ± 1.35 <0.001
 Left eyes 24.34 ± 1.31 23.94 ± 1.34 <0.001
In the per-SNP replication of the 61 myopia-related SNPs, 16 SNPs were not available in our dataset. Of those, 13 (81%) showed extremely low MAF ( Display FormulaImage not available 0.0056) in JPT samples of the 1000 Genomes database build 37 (Supplementary Table S1). We analyzed 45 originally reported myopia-related SNPs and one SNP (rs4458448 in the BMP3 region) that showed complete LD (r2 = 1) to the original SNP (rs1960445 in the BMP3 region), and found that 11 SNPs in nine genetic regions showed P < 0.05 for the association with MSE (Table 3 and Supplementary Table S2). In the BMP3 region, rs4458448 did not show significant association with MSE, while rs5022942 had a significant P value of 0.0496. However, the association direction of rs5022942 was opposite to the original SNP results and we did not regard BMP3 as significantly replicated (Supplementary Table S3). In the gene-based top-SNP replication, 12 genetic regions showed P < 0.05 after Bonferroni correction by the number of tagging SNPs (Table 4). In the gene-based all-SNP replication study performed using VEGAS software, eight genes showed P < 0.05 (Table 5). A total of 15 genetic regions showed P < 0.05 in at least one of the three analyses and were considered to be myopia-associated genes in the Japanese (Table 6). Among these, genetic regions near KCNQ5, GJD2, RASGRF1, BICC, and CD55 showed P Display FormulaImage not available 0.05 in all analyses, and regions near BMP4, SH3GL2, and B4GALNT2 showed P < 0.05 in two of the three analyses. Our findings were compared to the results of two previous GWASs in Supplementary Table S4. Association plots of the eight genes that were replicated by per-SNP replication are shown in Figure 2. Three of them showed peak association signals with high LD in the originally reported SNPs (Fig. 2A), while the other five genes did not (Fig. 2B). Figure 3 shows association plots of seven genetic regions that were only replicated by gene-based analyses and failed to be replicated by per-SNP analysis. Peak association signals and the originally reported SNPs had separated chromosomal positions in our dataset. We further evaluated the effect of different LD structures on the association signals of the reported SNPs and their tagging SNPs. We plotted six SNPs of seven genes in Figure 3 (excluding EHBP1L1) using two LD patterns in the 1000 Genomes datasets of EUR and ASN, released in March 2012 (hg19), and found that the tagging SNPs of rs66913363 (BMP4) and rs235770 (BMP2) showed increased associations with MSE using LD patterns of Caucasians (Supplementary Table S1). Tagging-SNPs of the other four SNPs did not show remarkable changes regardless of the applied LD structures (data not shown).  
Figure 2. Continued
 
Association plots of the eight genes that were significantly replicated in our per-SNP analysis. Reported SNPs near BICC1, GJD2, and RASGRF1 showed strong associations with MSE and composed one of the peak signals in our dataset (A, A-C). In contrast, association signals of the reported SNPs of CD55, KCNQ5, CYP26A1, LRRC4C, and B4GALNT2 did not show the highest associations within each genetic region in our dataset (B, A-E). All plots are shown in chromosomal order.
Figure 2. Continued
 
Association plots of the eight genes that were significantly replicated in our per-SNP analysis. Reported SNPs near BICC1, GJD2, and RASGRF1 showed strong associations with MSE and composed one of the peak signals in our dataset (A, A-C). In contrast, association signals of the reported SNPs of CD55, KCNQ5, CYP26A1, LRRC4C, and B4GALNT2 did not show the highest associations within each genetic region in our dataset (B, A-E). All plots are shown in chromosomal order.
Figure 3
 
Association plots of the SNPs within seven genetic regions near QKI, SFRP1, SH3GL2, EHBP1L1, GRIA4, BMP4, and BMP2 that were replicated in our gene-based analyses but failed to be replicated in our per-SNP analysis. Reported SNPs are highlighted in purple and SNPs within high LD to the reported SNPs are colored according to the strength of LD. Reported SNP of EHBP1L1 was not available in our dataset and the top-SNP was shown instead (D). These LD were calculated using the 1000 Genomes dataset of ASN, reported in March 2012 (hg19) using the LocusZoom software. Association signals of the reported SNPs were relatively low and genetic positions of the original SNPs were apart from the peak signals in each association plot (AC, EF).
Figure 3
 
Association plots of the SNPs within seven genetic regions near QKI, SFRP1, SH3GL2, EHBP1L1, GRIA4, BMP4, and BMP2 that were replicated in our gene-based analyses but failed to be replicated in our per-SNP analysis. Reported SNPs are highlighted in purple and SNPs within high LD to the reported SNPs are colored according to the strength of LD. Reported SNP of EHBP1L1 was not available in our dataset and the top-SNP was shown instead (D). These LD were calculated using the 1000 Genomes dataset of ASN, reported in March 2012 (hg19) using the LocusZoom software. Association signals of the reported SNPs were relatively low and genetic positions of the original SNPs were apart from the peak signals in each association plot (AC, EF).
Table 3
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related SNPs by the per-SNP Replication Method
Table 3
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related SNPs by the per-SNP Replication Method
Gene Symbol SNP* CHR BP MAF A1/A2 β SE P
GPR25 rs6702767 1 200844547 0.26 G/A −0.05 0.08 0.54
CD55 rs1652333 1 207470460 0.44 G/A −0.14 0.07 0.043
PABPCP2 rs17412774 2 146773948 0.36 A/C −0.08 0.07 0.23
DLX1 rs17428076 2 172851936 0.03 G/C 0.21 0.21 0.31
PRSS56 rs1656404 2 233379941 0.02 A/G 0.05 0.19 0.78
PRSS56 rs1550094 2 233385396 0.09 G/A −0.05 0.11 0.67
CHRNG rs1881492 2 233406998 0.16 T/G −0.05 0.10 0.62
SETMAR rs1843303 3 4185124 0.46 T/C −0.01 0.07 0.94
LOC100506035 rs9307551 4 80530671 0.34 A/C 0.06 0.07 0.36
BMP3 rs1960445 (rs4458448) 4 81927206 0.03 T/C 0.24 0.18 0.20
BMP3 rs5022942 4 81959966 0.34 A/G 0.14 0.07 0.0496
KCNQ5 rs7744813 6 73643289 0.21 C/A 0.23 0.08 0.0026
QKI rs9365619 6 164251746 0.34 A/C −0.01 0.07 0.87
ZMAT4 rs7829127 8 40726394 0.07 G/A 0.17 0.13 0.20
SFRP1 rs2137277 8 40734662 0.04 G/A 0.14 0.16 0.39
TOX rs7837791 8 60179086 0.46 G/T 0.02 0.07 0.80
TOX rs72621438 8 60178580 0.47 G/C 0.03 0.07 0.65
CHD7 rs4237036 8 61701057 0.20 C/T 0.04 0.08 0.62
SH3GL2/ ADAMTSL1 rs10963578 9 18338649 0.33 A/G 0.09 0.07 0.20
RORB rs7042950 9 77149837 0.31 A/G 0.04 0.07 0.54
BICC1 rs7084402 10 60265404 0.49 A/G 0.17 0.06 0.010
BICC1 rs4245599 10 60365755 0.46 G/A 0.20 0.06 0.0019
KCNMA1 rs6480859 10 79081948 0.17 T/C −0.07 0.09 0.44
RGR rs745480 10 85986554 0.33 C/G 0.03 0.07 0.65
CYP26A1 rs10882165 10 94924324 0.04 T/A −0.40 0.18 0.023
LRRC4C rs1381566 11 40149607 0.22 G/T −0.16 0.08 0.040
DLG2 rs2155413 11 84634790 0.21 C/A 0.06 0.08 0.46
GRIA4 rs11601239 11 105556598 0.34 G/C 0.06 0.07 0.36
PZP rs6487748 12 9435768 0.34 G/A −0.13 0.07 0.069
RDH5 rs3138142 12 56115585 0.02 T/C 0.30 0.21 0.16
PTPRR rs12229663 12 71249996 0.38 G/A 0.10 0.07 0.14
ZIC2 rs8000973 13 100691367 0.25 C/T −0.11 0.08 0.14
ZIC2 rs4291789 13 100672921 0.27 G/A −0.11 0.08 0.14
PCCA rs2184971 13 100818092 0.29 A/G 0.02 0.07 0.83
BMP4 rs66913363 14 54413001 0.22 C/G 0.08 0.08 0.33
66 rs1254319 14 60903757 0.38 G/A 0.05 0.07 0.44
GJD2 rs524952 15 35005886 0.48 A/T −0.30 0.07 3.7E-06
RASGRF1 rs4778879 15 79372875 0.49 A/G 0.22 0.07 0.00094
RASGRF1 rs28412916 15 79378167 0.48 A/C 0.21 0.07 0.0014
RBFOX1 rs17648524 16 7459683 0.05 C/G −0.19 0.15 0.19
SHISA6 rs2969180 17 11407901 0.46 G/A 0.11 0.07 0.084
SHISA6 rs2908972 17 11407259 0.45 C/A 0.10 0.07 0.12
B4GALNT2 rs9902755 17 47220726 0.16 C/T 0.19 0.09 0.039
KCNJ2 rs4793501 17 68718734 0.44 T/C −0.01 0.07 0.83
CNDP2 rs12971120 18 72174023 0.32 G/A 0.09 0.07 0.20
BMP2 rs235770 20 6761765 0.31 T/C −0.07 0.07 0.32
Table 4
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related Genes by Gene-Based Top-SNP Replication Methods With Bonferroni Corrections by the Number of Each Tagging SNPs
Table 4
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related Genes by Gene-Based Top-SNP Replication Methods With Bonferroni Corrections by the Number of Each Tagging SNPs
Gene Symbol SNP* CHR BP MAF A1/A2 β P Number of Tagging SNPs§ Pcorrected
GPR25 rs91564 1 200893050 0.05 T/C 0.27 0.0044 21 0.093
CD55 rs12116783 1 207556770 0.08 A/G 0.22 0.0045 7 0.031
PABPCP2 rs10202376 2 147315208 0.77 T/C 0.22 0.14 6 0.85
DLX1 rs79886888 2 173004317 0.17 T/C 0.28 0.10 34 1
PDE11A rs13006877 2 178984328 0.32 T/A −0.20 0.0043 32 0.14
PRSS56 rs115279622 2 233375977 0.37 T/C −0.65 0.0065 40 0.26
CHRNG rs12617942 2 233416068 0.02 T/C −0.73 0.017 37 0.63
SETMAR rs79901438 3 4391460 0.15 G/T 0.20 0.015 23 0.34
CACNA1D rs73841203 3 53875801 0.27 G/A 0.39 0.0020 122 0.24
ZBTB38 rs1993904 3 141003354 0.02 T/C 0.32 0.0016 88 0.14
LOC100506035 rs9684343 4 80546040 0.10 G/C 0.21 0.051 10 1
ANTXR2 rs11099009 4 80988658 0.08 A/G −0.24 0.023 35 0.80
BMP3 rs7659948 4 81979993 0.31 C/T 0.17 0.039 19 0.74
KCNQ5 rs6929988 6 73914319 0.44 A/G 0.28 4.7E-05 102 0.0048
LAMA2 rs10080659 6 129817349 0.03 T/C 0.23 0.0016 82 0.13
QKI rs9346961 6 163905968 0.10 T/C −0.89 5.2E-05 32 0.0017
ZMAT4 rs7816960 8 40354396 0.18 A/C −0.29 0.0020 55 0.11
SFRP1 rs148016338 8 41103891 0.04 A/G 1.07 0.00074 19 0.014
TOX rs139199809 8 59755748 0.02 C/T 0.89 0.0031 72 0.22
CHD7 rs6984384 8 61809929 0.21 C/T −0.31 0.0068 40 0.27
SH3GL2/ (ADAMTSL1) rs10963177 9 17639458 0.50 C/T 0.24 0.00042 106 0.044
(SH3GL2) /ADAMTSL1 rs16937047 9 18770943 0.36 T/C −0.26 0.00067 216 0.14
TJP2 rs4515614 9 71742683 0.02 T/C −0.86 0.0091 44 0.40
RORB rs11144053 9 77284559 0.27 G/A −0.25 0.02886 45 1
BICC1 rs893369 10 60360901 0.01 T/A 0.23 0.00052 34 0.018
KCNMA1 rs11001900 10 78606671 0.22 A/G 0.22 0.00086 256 0.22
RGR rs11817115 10 86018811 0.02 G/A −0.31 0.0032 16 0.051
CYP26A1 rs117520829 10 94791300 0.05 G/C −0.51 0.0034 19 0.065
TCF7L2 rs12573128 10 114730797 0.27 A/C 0.16 0.030 120 1
LRRC4C rs58287560 11 40810557 0.38 C/A 0.25 0.00060 168 0.10
EHBP1L1 rs931127 11 65405300 0.12 A/G 0.21 0.0013 19 0.025
DLG2 rs145062356 11 83631501 0.03 A/G −1.00 0.00080 359 0.29
GRIA4 rs78925386 11 105753469 0.05 A/C −0.96 0.0018 27 0.049
PZP rs717180 12 9395807 0.05 A/G 0.20 0.011 17 0.19
RDH5 rs11171667 12 56131052 0.13 A/C −0.20 0.054 23 1
PTPRR rs151294916 12 71325795 0.04 G/A −0.75 0.0062 51 0.32
ZIC2 rs35140645 13 100649321 0.39 G/A −0.18 0.014 23 0.32
PCCA rs9513744 13 100935665 0.01 T/A −0.80 0.0018 44 0.081
LRFN5 rs79467137 14 42096662 0.03 A/T −0.54 0.0068 35 0.24
BMP4 rs7149027 14 54473305 0.50 A/G 0.36 0.00079 18 0.014
66 rs1015119 14 61027510 0.60 C/T −0.19 0.040 2 0.080
GJD2 rs589135 15 35001442 0.27 C/G −0.31 1.8E-06 45 0.000082
RASGRF1 rs57488047 15 79403002 0.51 C/T 0.25 0.00031 81 0.025
RBFOX1 rs79266634 16 7309047 0.54 A/G 0.40 0.00074 649 0.48
SHISA6 rs11651793 17 11267101 0.15 G/A 0.30 0.0083 105 0.88
MYO1D rs117769171 17 30852727 0.45 C/T −0.84 0.0049 71 0.35
B4GALNT2 rs4438351 17 47240493 0.20 C/T 0.21 0.0025 31 0.079
KCNJ2 rs11077480 17 68214161 0.12 A/G 0.45 0.012 15 0.18
NPLOC4 rs76645549 17 79645253 0.12 G/A 0.20 0.0096 42 0.40
CNDP2 rs78754702 18 72155813 0.32 G/A −0.79 0.0054 49 0.27
BMP2 rs12624364 20 6773370 0.49 A/G −0.23 0.00059 36 0.021
Table 5
 
Gene-Based Association Analysis Incorporating all SNPs Within Each Myopia-Related Genetic Region Using VEGAS Software
Table 5
 
Gene-Based Association Analysis Incorporating all SNPs Within Each Myopia-Related Genetic Region Using VEGAS Software
Gene Symbol* CHR Position NCBI37/hg19 nSNPs* P
GPR25 1 200842083 200843306 80 0.59
CD55 1 207494817 207534311 88 0.04995
PABPCP2 2 147344625 147348558 NA NA
DLX1 2 172950208 172954401 58 0.45
PDE11A 2 178487977 178973066 614 0.15
PRSS56 2 233385173 233390425 NA NA
CHRNG 2 233404437 233411038 174 0.13
SETMAR 3 4344988 4358949 134 0.16
CACNA1D 3 53529076 53846492 399 0.19
ZBTB38 3 141043055 141168632 136 0.47
LOC100506035 4 80413747 80497614 NA NA
ANTXR2 4 80822771 80994626 142 0.25
BMP3 4 81952119 81978685 105 0.18
KCNQ5 6 73331571 73908573 650 0.0015
LAMA2 6 129204286 129837710 701 0.37
QKI 6 163835675 163999628 172 0.073
ZMAT4 8 40388111 40755343 435 0.31
SFRP1 8 41119476 41166990 105 0.52
TOX 8 59717977 60031767 502 0.93
CHD7 8 61591324 61780586 240 0.51
SH3GL2/(ADAMTSL1) 9 17578953 17797122 460 0.047
(SH3GL2)/ADAMTSL1 9 18474079 18910947 825 0.12
TJP2 9 71736180 71870124 176 0.72
RORB 9 77112252 77302117 241 0.77
BICC1 10 60272904 60588845 303 0.0060
KCNMA1 10 78629359 79397577 1035 0.074
RGR 10 86004809 86018944 176 0.71
CYP26A1 10 94833232 94837641 55 0.070
TCF7L2 10 114710009 114927436 170 0.95
LRRC4C 11 40135751 41481186 319 0.14
EHBP1L1 11 65343509 65360116 58 0.088
DLG2 11 83166056 85338314 1377 0.32
GRIA4 11 105480800 105852819 433 0.35
PZP 12 9301436 9360966 185 0.76
RDH5 12 56114151 56118526 42 0.27
PTPRR 12 71031853 71314584 384 0.67
ZIC2 13 100634026 100639019 45 0.30
PCCA 13 100741269 101182691 294 0.75
LRFN5 14 42076764 42373752 316 0.59
BMP4 14 54416455 54423554 96 0.013
66 14 60975938 60978525 102 0.11
GJD2 15 35044642 35046782 142 0.00084
RASGRF1 15 79252289 79383215 185 0.014
RBFOX1 16 6069132 7763340 3526 0.30
SHISA6 17 11144740 11467380 NA NA
MYO1D 17 30819628 31203902 266 0.93
B4GALNT2 17 47209822 47247351 94 0.031
KCNJ2 17 68165676 68176183 108 0.56
NPLOC4 17 79523909 79596831 102 0.29
CNDP2 18 72163500 72190689 147 0.30
BMP2 20 6748745 6760910 110 0.052
Table 6
 
Summary of the Three Replication Analyses for the Japanese Cohort That Showed P < 0.05 in at Least One Analysis
Table 6
 
Summary of the Three Replication Analyses for the Japanese Cohort That Showed P < 0.05 in at Least One Analysis
Gene Symbol CHR Position NCBI37/hg19 SNP-Based Gene-Based
Bonferroni VEGAS
CD55 1 207494817 207534311 0.043 0.031 0.04995
KCNQ5 6 73331571 73908573 0.0026 0.0048 0.0015
QKI 6 163835675 163999628 0.87 0.0017 0.073
SFRP1 8 41119476 41166990 0.39 0.014 0.52
SH3GL2/(ADAMTSL1) 9 17578953 17797122 0.20 0.044 0.047
BICC1 10 60272904 60588845 0.0019 0.018 0.0060
CYP26A1 10 94833232 94837641 0.023 0.065 0.070
LRRC4C 11 40135751 41481186 0.040 0.10 0.14
EHBP1L1 11 65343509 65360116 NA 0.025 0.088
GRIA4 11 105480800 105852819 0.36 0.049 0.35
BMP4 14 54416455 54423554 0.33 0.014 0.013
GJD2 15 35044642 35046782 3.7E-06 0.000082 0.00084
RASGRF1 15 79252289 79383215 0.00094 0.025 0.014
B4GALNT2 17 47209822 47247351 0.039 0.079 0.031
BMP2 20 6748745 6760910 0.32 0.021 0.052
Discussion
In the present study, we evaluated the associations between refractive error and myopia-related genes reported previously in two large GWASs for myopia: survival analysis for the onset age of myopia in Caucasians by 23andME, and quantitative trait loci analysis for spherical error using Caucasian and Asian populations by the CREAM. Our per-SNP analysis successfully replicated the associations of eight genes related to myopia, while our gene-based top-SNP and all-SNP analyses further revealed seven genes that were significantly associated with refractive error in the Japanese population. Simpson et al.32 reported the limit of the per-SNP replication method and showed the efficacy of region-based analysis for myopia. While they evaluated only two widely known myopia-susceptible genes in Caucasians, we clearly demonstrated the usefulness of gene-based testing in that the associations of seven genes could be replicated with the gene-based approach out of 15 successfully replicated genes in our study. Considering the heterogeneous traits of refractive error and the different patterns of LD across ethnicities, gene-based analysis would be a useful approach for the present study. 
Of the eight genes that showed significant association with myopia in our per-SNP analysis, six genes had been evaluated in CREAM Asian cohorts and five of the six genes had shown significant association with MSE. Our per-SNP analysis found only one newly replicated gene, CYP26A1, in Asian populations. In the genes reported in the 23andME study that used Caucasian subjects, our per-SNP analysis could replicate only two genes, LRRC4C and B4GALNT2
In contrast to per-SNP analysis, gene-based analysis would be a more powerful tool in replication studies for myopia across ethnicities. Our gene-based analysis found seven newly replicated genes: GRIA4, BMP2, QKI, BMP4, SFRP1, SH3GL2, and EHBP1L1. In the GWAS reported by the CREAM, the per-SNP analysis in the Asian cohort showed nonsignificant P values for BMP2, which may be due to the difference in ethnicity between their Caucasian discovery and Asian replication. Gene-based analysis in their Asian cohort might have been able to show significant P values for this gene. In addition, our gene-based studies confirmed the association of BMP4, SFRP1, SH3GL2, and EHBP1L1 with myopia that failed to be replicated by the 23andMe study. These four genes of newly replicated Asian samples would be susceptibility genes for myopia across ethnicities. 
The advantage of gene-based analysis against per-SNP analysis can be explained in three ways. First, per-SNP analysis is affected by allele frequency. As we have shown in Supplementary Table S1, as many as 13 of 61 reported SNPs showed extremely low MAF in the Japanese population, which consequently would lead to replication failure by per-SNP approach. One example is rs72939141 near EHBP1L1 that showed marginally significant association with myopia in the 23andMe GWAS. We successfully replicated EHBP1L1 by gene-based analysis despite low allele frequencies across ethnicities (MAF was 0 in CEU and JPT populations in the 1000 Genomes dataset released in March 2014) that could have prevented us from examining the true association of the gene by the per-SNP method. The second problem in per-SNP analysis is the narrow genetic regions that could be tested for the associations with phenotype. In our association plots of the eight genes replicated by per-SNP analysis, three genes clearly showed peak association signals with high LD in the reported SNPs (Fig. 2A). However, the other five genes did not show close relationships between peak association signals and the reported SNPs (Fig. 2B). Even though the latter five SNPs also were replicated by per-SNP analysis, investigating wider genetic regions (e.g., region-based analysis shown by Simpson et al.32) would make the associations still more significant. The association strength of a single SNP only reflects signals including nearby SNPs with moderate LD, and is far from reflecting genetic influences of the gene itself. The last problem in per-SNP analysis is the heterogeneity of LD patterns across ethnicities. Figure 3 shows different association signals of GRIA4, BMP2, QKI, BMP4, SFRP1, SH3GL2, and EHBP1L1 between Caucasians and Asians. Reported SNPs of these genes could not be replicated by per-SNP methods, probably due to the different LD patterns. This issue was further evaluated in Supplementary Figure S1 in that more intense association signals of the reported SNPs would be illustrated when considering the variability of LD patterns between Asians and Caucasians. Our successful replication of these genes by gene-based approaches shows the limitations of per-SNP replication for ethnicities with different LD patterns. 
Although LD patterns are different across ethnicities, our findings suggested a similar effect direction of most myopia-related genes across ethnicities. When our per-SNP analysis was compared to the CREAM GWAS results, the evaluated SNPs showed consistent effect direction among Japanese, other Asians, and Caucasians. Supplementary Table S3 shows a comparison of effect size and direction for 24 SNPs that were reported by the CREAM study, which also were included in our dataset. Of the 24 SNPs, 19 (79.2%) have the same effect direction for myopia. However, it was interesting that BMP3 showed the opposite effect for myopia between Caucasians and Japanese, as well as between Caucasians and Asians. Rs1960445/rs4458448 of BMP3 was considered to be nonsignificant for myopia in the CREAM Asian samples. However, the consistent effect direction with our Japanese dataset suggested a different effect of BMP3 on Caucasian and Asian myopia. The minor allele of rs1960445/rs4458448 would have risk effects for myopia in Caucasians, while it has protective effects in Japanese and other Asians. 
For further replication, the following two sets of genes should be considered. First, we successfully replicated CYP26A1 among 11 genes that did not show associations in the CREAM Asian samples. In our previous study, we also showed that ZIC2 was significantly associated with high myopia in Japanese.25 Further replication study with larger Asian cohorts may reveal associations of ZIC2 with myopia. For the remaining nine genes that showed consistently negative results in our cohorts and the CREAM Asian samples, further replications of these genes are necessary using more Asian samples. Second, among the 22 genes that showed associations only in the 23andMe dataset and are yet to be examined in Asian samples, seven genes, LRRC4C, QKI, BMP4, SFRP1, SH3GL2, B4GALNT2, and EHBP1L1 were replicated in our samples. For the remaining 15 genes, further replications are necessary using Asian samples. 
There were three limitations in this study. First, in our dataset, some SNPs were not genotyped directly but had imputed genotypes. Additionally, we could not find all of the reported SNPs in the first analysis; 16 of 61 reported SNPs were not available in our imputed dataset. After screening other SNPs with complete LD to original ones, only rs1960445 became analyzable through rs4458448 (Supplementary Table S2). However, this issue was resolved by gene-based analysis of replicating association signals by using multiple SNPs within the gene. Second, we could not replicate ZIC2 in this study that is incompatible with our previous report.25 We have shown that ZIC2 is significantly associated with high myopia (AL ≥ 26.0 mm) in Japanese, which might be a result of the different genetic contributions to various myopic ocular traits. Thus, further investigation should be carried out to clarify these genetic variations. Third, we confirmed strong associations of four genes, GJD2, RASGRF1, KCNQ5, and BICC1, in the Japanese population, consistent with the previous reports on Asians and Caucasians. However, we could not replicate four genes, PRSS56, LAMA2, TOX, and RDH5, which consistently showed significant associations throughout the two previous GWASs. These genes are highly likely to be strongly associated with myopia in Caucasians and Asians and, thus, these replication failures would be caused by our sample size and/or ethnic differences between Japanese and other Asian ethnicities. 
In conclusion, we selected myopia-related SNPs that had been reported by GWASs and thoroughly replicated these SNPs in a relatively large Japanese cohort. Our results suggested the efficacy of combining gene-based analysis with per-SNP analysis to replicate association signals across ethnicities. We replicated 15 genes and confirmed strong associations of GJD2, RASGRF1, KCNQ5, and BICC1 with myopia across Caucasian, Asian, and Japanese populations, whereas BMP3 might have ethnic specificity to Caucasians for associations with myopia. These analyses would support further replications and investigations regarding the contributions of these genes to myopia across ethnicities. 
Acknowledgments
Supported in part by Grant-in-Aid for scientific research (No. 24592624) from the Japan Society for the Promotion of Science, Tokyo, and the Japan National Society for the Prevention of Blindness, Tokyo, Japan. The authors alone are responsible for the content and writing of the paper. 
Disclosure: M. Yoshikawa, None; K. Yamashiro, None; M. Miyake, None; M. Oishi, None; Y. Akagi-Kurashige, None; K. Kumagai, None; I. Nakata, None; H. Nakanishi, None; A. Oishi, None; N. Gotoh, None; R. Yamada, None; F. Matsuda, None; N. Yoshimura, None 
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Footnotes
 See the appendix for the members of the Nagahama Study Group.
Appendix
The Nagahama Study Group
The following investigators were core members of the Nagahama Cohort Research Group: Takeo Nakayama (Department of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan), Akihiro Sekine (Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan), Shinji Kosugi (Department of Medical Ethics, Kyoto University School of Public Health, Kyoto, Japan), Takahisa Kawaguchi (Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan), Ryo Yamada (Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan), Yasuharu Tabara (Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan), and Fumihiko Matsuda (Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan). 
Figure 1
 
Description and illustration of three replication methods used in our analysis, using BMP2 as an example. (A) Definitions of the three methods are summarized. (B, C) Association plots of the SNPs near BMP2 in our dataset, showing the target SNPs of per-SNP analysis (B) and gene-based top-SNP analysis (C). Genetic regions Image not available 200 kb are shown in each plot. (D) An LD plot within the genetic region Image not available 50 kb of BMP2, comprised of 240 SNPs in our dataset. Totals of 17 haplotype blocks and 19 SNPs were not included in any of the blocks. Thus, the number of tag-SNPs was counted to be 36 ( = 17 + 19). The top SNP of BMP2 that is shown in (C) should be corrected by the number of tag-SNPs and a P value of < 0.0014 ( = 0.05/36) would be significant for gene-based top-SNP analysis.
Figure 1
 
Description and illustration of three replication methods used in our analysis, using BMP2 as an example. (A) Definitions of the three methods are summarized. (B, C) Association plots of the SNPs near BMP2 in our dataset, showing the target SNPs of per-SNP analysis (B) and gene-based top-SNP analysis (C). Genetic regions Image not available 200 kb are shown in each plot. (D) An LD plot within the genetic region Image not available 50 kb of BMP2, comprised of 240 SNPs in our dataset. Totals of 17 haplotype blocks and 19 SNPs were not included in any of the blocks. Thus, the number of tag-SNPs was counted to be 36 ( = 17 + 19). The top SNP of BMP2 that is shown in (C) should be corrected by the number of tag-SNPs and a P value of < 0.0014 ( = 0.05/36) would be significant for gene-based top-SNP analysis.
Figure 2. Continued
 
Association plots of the eight genes that were significantly replicated in our per-SNP analysis. Reported SNPs near BICC1, GJD2, and RASGRF1 showed strong associations with MSE and composed one of the peak signals in our dataset (A, A-C). In contrast, association signals of the reported SNPs of CD55, KCNQ5, CYP26A1, LRRC4C, and B4GALNT2 did not show the highest associations within each genetic region in our dataset (B, A-E). All plots are shown in chromosomal order.
Figure 2. Continued
 
Association plots of the eight genes that were significantly replicated in our per-SNP analysis. Reported SNPs near BICC1, GJD2, and RASGRF1 showed strong associations with MSE and composed one of the peak signals in our dataset (A, A-C). In contrast, association signals of the reported SNPs of CD55, KCNQ5, CYP26A1, LRRC4C, and B4GALNT2 did not show the highest associations within each genetic region in our dataset (B, A-E). All plots are shown in chromosomal order.
Figure 3
 
Association plots of the SNPs within seven genetic regions near QKI, SFRP1, SH3GL2, EHBP1L1, GRIA4, BMP4, and BMP2 that were replicated in our gene-based analyses but failed to be replicated in our per-SNP analysis. Reported SNPs are highlighted in purple and SNPs within high LD to the reported SNPs are colored according to the strength of LD. Reported SNP of EHBP1L1 was not available in our dataset and the top-SNP was shown instead (D). These LD were calculated using the 1000 Genomes dataset of ASN, reported in March 2012 (hg19) using the LocusZoom software. Association signals of the reported SNPs were relatively low and genetic positions of the original SNPs were apart from the peak signals in each association plot (AC, EF).
Figure 3
 
Association plots of the SNPs within seven genetic regions near QKI, SFRP1, SH3GL2, EHBP1L1, GRIA4, BMP4, and BMP2 that were replicated in our gene-based analyses but failed to be replicated in our per-SNP analysis. Reported SNPs are highlighted in purple and SNPs within high LD to the reported SNPs are colored according to the strength of LD. Reported SNP of EHBP1L1 was not available in our dataset and the top-SNP was shown instead (D). These LD were calculated using the 1000 Genomes dataset of ASN, reported in March 2012 (hg19) using the LocusZoom software. Association signals of the reported SNPs were relatively low and genetic positions of the original SNPs were apart from the peak signals in each association plot (AC, EF).
Table 1
 
Characteristics of the Study Population According to Age
Table 1
 
Characteristics of the Study Population According to Age
30–39 y 40–49 y 50–59 y 60–69 y 70–75 y Total
Patients, n 1047 367 518 874 276 3082
Age,* y 34.60 ± 2.76 44.24 ± 2.87 55.17 ± 2.88 64.4 ± 2.93 72.2 ± 1.57 51.02 ± 14.09 (30–5)
Sex, n (%)
 Male 294 (28.1) 124 (33.8) 152 (29.3) 338 (38.7) 121 (43.8) 1029 (33.4)
 Female 753 (71.9) 243 (66.2) 518 (70.7) 536 (61.3) 155 (56.2) 2053 (66.6)
MSE,* D (range) −2.63 ± 2.53 (−13.25–7.44) −2.75 ± 2.82 (−15.38–2.19) −1.84 ± 2.81 (−15.69–6.69) −0.75 ± 2.52 (−14.81–4.38) 0.20 ± 2.28 (−13.31–4.63) −1.72 ± 2.78 (−15.69–7.44)
 Right eyes −2.66 ± 2.58 −2.82 ± 2.90 −1.90 ± 2.89 −0.78 ± 2.60 0.18 ± 2.44 −1.76 ± 2.85
 Left eyes −2.59 ± 2.52 −2.68 ± 2.79 −1.78 ± 2.84 −0.71 ± 2.56 0.22 ± 2.40 −1.68 ± 2.80
AL,* mm (range) 24.51 ± 1.30 (20.47–28.92) 24.54 ± 1.40 (21.92–28.99) 23.98 ± 1.37 (21.03–29.80) 23.70 ± 1.19 (21.07–28.37) 23.41 ± 1.11 (21.29–28.83) 24.10 ± 1.34 (20.47–29.80)
 Right eyes 24.53 ± 1.32 24.57 ± 1.44 24.00 ± 1.38 23.72 ± 1.21 23.42 ± 1.14 24.12 ± 1.36
 Left eyes 24.48 ± 1.30 24.51 ± 1.37 23.96 ± 1.40 23.69 ± 1.20 23.39 ± 1.11 24.08 ± 1.35
Table 2
 
Characteristics of the Study Population According to Sex
Table 2
 
Characteristics of the Study Population According to Sex
Male Female P
Patients, n 1029 2053
Age,* y 53.02 ± 14.24 50.02 ± 13.91 <0.001
MSE,* D (range) −1.56 ± 2.68 (−14.75–7.44) −1.80 ± 2.82 (−15.69–6.69) 0.023
 Right eyes −1.59 ± 2.75 −1.85 ± 2.90 0.020
 Left eyes −1.53 ± 2.71 −1.75 ± 2.83 0.039
AL,* mm (range) 24.37 ± 1.32 (21.06–9.80) 23.96 ± 1.33 (20.47–8.99) <0.001
 Right eyes 24.39 ± 1.35 23.98 ± 1.35 <0.001
 Left eyes 24.34 ± 1.31 23.94 ± 1.34 <0.001
Table 3
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related SNPs by the per-SNP Replication Method
Table 3
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related SNPs by the per-SNP Replication Method
Gene Symbol SNP* CHR BP MAF A1/A2 β SE P
GPR25 rs6702767 1 200844547 0.26 G/A −0.05 0.08 0.54
CD55 rs1652333 1 207470460 0.44 G/A −0.14 0.07 0.043
PABPCP2 rs17412774 2 146773948 0.36 A/C −0.08 0.07 0.23
DLX1 rs17428076 2 172851936 0.03 G/C 0.21 0.21 0.31
PRSS56 rs1656404 2 233379941 0.02 A/G 0.05 0.19 0.78
PRSS56 rs1550094 2 233385396 0.09 G/A −0.05 0.11 0.67
CHRNG rs1881492 2 233406998 0.16 T/G −0.05 0.10 0.62
SETMAR rs1843303 3 4185124 0.46 T/C −0.01 0.07 0.94
LOC100506035 rs9307551 4 80530671 0.34 A/C 0.06 0.07 0.36
BMP3 rs1960445 (rs4458448) 4 81927206 0.03 T/C 0.24 0.18 0.20
BMP3 rs5022942 4 81959966 0.34 A/G 0.14 0.07 0.0496
KCNQ5 rs7744813 6 73643289 0.21 C/A 0.23 0.08 0.0026
QKI rs9365619 6 164251746 0.34 A/C −0.01 0.07 0.87
ZMAT4 rs7829127 8 40726394 0.07 G/A 0.17 0.13 0.20
SFRP1 rs2137277 8 40734662 0.04 G/A 0.14 0.16 0.39
TOX rs7837791 8 60179086 0.46 G/T 0.02 0.07 0.80
TOX rs72621438 8 60178580 0.47 G/C 0.03 0.07 0.65
CHD7 rs4237036 8 61701057 0.20 C/T 0.04 0.08 0.62
SH3GL2/ ADAMTSL1 rs10963578 9 18338649 0.33 A/G 0.09 0.07 0.20
RORB rs7042950 9 77149837 0.31 A/G 0.04 0.07 0.54
BICC1 rs7084402 10 60265404 0.49 A/G 0.17 0.06 0.010
BICC1 rs4245599 10 60365755 0.46 G/A 0.20 0.06 0.0019
KCNMA1 rs6480859 10 79081948 0.17 T/C −0.07 0.09 0.44
RGR rs745480 10 85986554 0.33 C/G 0.03 0.07 0.65
CYP26A1 rs10882165 10 94924324 0.04 T/A −0.40 0.18 0.023
LRRC4C rs1381566 11 40149607 0.22 G/T −0.16 0.08 0.040
DLG2 rs2155413 11 84634790 0.21 C/A 0.06 0.08 0.46
GRIA4 rs11601239 11 105556598 0.34 G/C 0.06 0.07 0.36
PZP rs6487748 12 9435768 0.34 G/A −0.13 0.07 0.069
RDH5 rs3138142 12 56115585 0.02 T/C 0.30 0.21 0.16
PTPRR rs12229663 12 71249996 0.38 G/A 0.10 0.07 0.14
ZIC2 rs8000973 13 100691367 0.25 C/T −0.11 0.08 0.14
ZIC2 rs4291789 13 100672921 0.27 G/A −0.11 0.08 0.14
PCCA rs2184971 13 100818092 0.29 A/G 0.02 0.07 0.83
BMP4 rs66913363 14 54413001 0.22 C/G 0.08 0.08 0.33
66 rs1254319 14 60903757 0.38 G/A 0.05 0.07 0.44
GJD2 rs524952 15 35005886 0.48 A/T −0.30 0.07 3.7E-06
RASGRF1 rs4778879 15 79372875 0.49 A/G 0.22 0.07 0.00094
RASGRF1 rs28412916 15 79378167 0.48 A/C 0.21 0.07 0.0014
RBFOX1 rs17648524 16 7459683 0.05 C/G −0.19 0.15 0.19
SHISA6 rs2969180 17 11407901 0.46 G/A 0.11 0.07 0.084
SHISA6 rs2908972 17 11407259 0.45 C/A 0.10 0.07 0.12
B4GALNT2 rs9902755 17 47220726 0.16 C/T 0.19 0.09 0.039
KCNJ2 rs4793501 17 68718734 0.44 T/C −0.01 0.07 0.83
CNDP2 rs12971120 18 72174023 0.32 G/A 0.09 0.07 0.20
BMP2 rs235770 20 6761765 0.31 T/C −0.07 0.07 0.32
Table 4
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related Genes by Gene-Based Top-SNP Replication Methods With Bonferroni Corrections by the Number of Each Tagging SNPs
Table 4
 
Genome-Wide Association Results of the Nagahama Study for Myopia-Related Genes by Gene-Based Top-SNP Replication Methods With Bonferroni Corrections by the Number of Each Tagging SNPs
Gene Symbol SNP* CHR BP MAF A1/A2 β P Number of Tagging SNPs§ Pcorrected
GPR25 rs91564 1 200893050 0.05 T/C 0.27 0.0044 21 0.093
CD55 rs12116783 1 207556770 0.08 A/G 0.22 0.0045 7 0.031
PABPCP2 rs10202376 2 147315208 0.77 T/C 0.22 0.14 6 0.85
DLX1 rs79886888 2 173004317 0.17 T/C 0.28 0.10 34 1
PDE11A rs13006877 2 178984328 0.32 T/A −0.20 0.0043 32 0.14
PRSS56 rs115279622 2 233375977 0.37 T/C −0.65 0.0065 40 0.26
CHRNG rs12617942 2 233416068 0.02 T/C −0.73 0.017 37 0.63
SETMAR rs79901438 3 4391460 0.15 G/T 0.20 0.015 23 0.34
CACNA1D rs73841203 3 53875801 0.27 G/A 0.39 0.0020 122 0.24
ZBTB38 rs1993904 3 141003354 0.02 T/C 0.32 0.0016 88 0.14
LOC100506035 rs9684343 4 80546040 0.10 G/C 0.21 0.051 10 1
ANTXR2 rs11099009 4 80988658 0.08 A/G −0.24 0.023 35 0.80
BMP3 rs7659948 4 81979993 0.31 C/T 0.17 0.039 19 0.74
KCNQ5 rs6929988 6 73914319 0.44 A/G 0.28 4.7E-05 102 0.0048
LAMA2 rs10080659 6 129817349 0.03 T/C 0.23 0.0016 82 0.13
QKI rs9346961 6 163905968 0.10 T/C −0.89 5.2E-05 32 0.0017
ZMAT4 rs7816960 8 40354396 0.18 A/C −0.29 0.0020 55 0.11
SFRP1 rs148016338 8 41103891 0.04 A/G 1.07 0.00074 19 0.014
TOX rs139199809 8 59755748 0.02 C/T 0.89 0.0031 72 0.22
CHD7 rs6984384 8 61809929 0.21 C/T −0.31 0.0068 40 0.27
SH3GL2/ (ADAMTSL1) rs10963177 9 17639458 0.50 C/T 0.24 0.00042 106 0.044
(SH3GL2) /ADAMTSL1 rs16937047 9 18770943 0.36 T/C −0.26 0.00067 216 0.14
TJP2 rs4515614 9 71742683 0.02 T/C −0.86 0.0091 44 0.40
RORB rs11144053 9 77284559 0.27 G/A −0.25 0.02886 45 1
BICC1 rs893369 10 60360901 0.01 T/A 0.23 0.00052 34 0.018
KCNMA1 rs11001900 10 78606671 0.22 A/G 0.22 0.00086 256 0.22
RGR rs11817115 10 86018811 0.02 G/A −0.31 0.0032 16 0.051
CYP26A1 rs117520829 10 94791300 0.05 G/C −0.51 0.0034 19 0.065
TCF7L2 rs12573128 10 114730797 0.27 A/C 0.16 0.030 120 1
LRRC4C rs58287560 11 40810557 0.38 C/A 0.25 0.00060 168 0.10
EHBP1L1 rs931127 11 65405300 0.12 A/G 0.21 0.0013 19 0.025
DLG2 rs145062356 11 83631501 0.03 A/G −1.00 0.00080 359 0.29
GRIA4 rs78925386 11 105753469 0.05 A/C −0.96 0.0018 27 0.049
PZP rs717180 12 9395807 0.05 A/G 0.20 0.011 17 0.19
RDH5 rs11171667 12 56131052 0.13 A/C −0.20 0.054 23 1
PTPRR rs151294916 12 71325795 0.04 G/A −0.75 0.0062 51 0.32
ZIC2 rs35140645 13 100649321 0.39 G/A −0.18 0.014 23 0.32
PCCA rs9513744 13 100935665 0.01 T/A −0.80 0.0018 44 0.081
LRFN5 rs79467137 14 42096662 0.03 A/T −0.54 0.0068 35 0.24
BMP4 rs7149027 14 54473305 0.50 A/G 0.36 0.00079 18 0.014
66 rs1015119 14 61027510 0.60 C/T −0.19 0.040 2 0.080
GJD2 rs589135 15 35001442 0.27 C/G −0.31 1.8E-06 45 0.000082
RASGRF1 rs57488047 15 79403002 0.51 C/T 0.25 0.00031 81 0.025
RBFOX1 rs79266634 16 7309047 0.54 A/G 0.40 0.00074 649 0.48
SHISA6 rs11651793 17 11267101 0.15 G/A 0.30 0.0083 105 0.88
MYO1D rs117769171 17 30852727 0.45 C/T −0.84 0.0049 71 0.35
B4GALNT2 rs4438351 17 47240493 0.20 C/T 0.21 0.0025 31 0.079
KCNJ2 rs11077480 17 68214161 0.12 A/G 0.45 0.012 15 0.18
NPLOC4 rs76645549 17 79645253 0.12 G/A 0.20 0.0096 42 0.40
CNDP2 rs78754702 18 72155813 0.32 G/A −0.79 0.0054 49 0.27
BMP2 rs12624364 20 6773370 0.49 A/G −0.23 0.00059 36 0.021
Table 5
 
Gene-Based Association Analysis Incorporating all SNPs Within Each Myopia-Related Genetic Region Using VEGAS Software
Table 5
 
Gene-Based Association Analysis Incorporating all SNPs Within Each Myopia-Related Genetic Region Using VEGAS Software
Gene Symbol* CHR Position NCBI37/hg19 nSNPs* P
GPR25 1 200842083 200843306 80 0.59
CD55 1 207494817 207534311 88 0.04995
PABPCP2 2 147344625 147348558 NA NA
DLX1 2 172950208 172954401 58 0.45
PDE11A 2 178487977 178973066 614 0.15
PRSS56 2 233385173 233390425 NA NA
CHRNG 2 233404437 233411038 174 0.13
SETMAR 3 4344988 4358949 134 0.16
CACNA1D 3 53529076 53846492 399 0.19
ZBTB38 3 141043055 141168632 136 0.47
LOC100506035 4 80413747 80497614 NA NA
ANTXR2 4 80822771 80994626 142 0.25
BMP3 4 81952119 81978685 105 0.18
KCNQ5 6 73331571 73908573 650 0.0015
LAMA2 6 129204286 129837710 701 0.37
QKI 6 163835675 163999628 172 0.073
ZMAT4 8 40388111 40755343 435 0.31
SFRP1 8 41119476 41166990 105 0.52
TOX 8 59717977 60031767 502 0.93
CHD7 8 61591324 61780586 240 0.51
SH3GL2/(ADAMTSL1) 9 17578953 17797122 460 0.047
(SH3GL2)/ADAMTSL1 9 18474079 18910947 825 0.12
TJP2 9 71736180 71870124 176 0.72
RORB 9 77112252 77302117 241 0.77
BICC1 10 60272904 60588845 303 0.0060
KCNMA1 10 78629359 79397577 1035 0.074
RGR 10 86004809 86018944 176 0.71
CYP26A1 10 94833232 94837641 55 0.070
TCF7L2 10 114710009 114927436 170 0.95
LRRC4C 11 40135751 41481186 319 0.14
EHBP1L1 11 65343509 65360116 58 0.088
DLG2 11 83166056 85338314 1377 0.32
GRIA4 11 105480800 105852819 433 0.35
PZP 12 9301436 9360966 185 0.76
RDH5 12 56114151 56118526 42 0.27
PTPRR 12 71031853 71314584 384 0.67
ZIC2 13 100634026 100639019 45 0.30
PCCA 13 100741269 101182691 294 0.75
LRFN5 14 42076764 42373752 316 0.59
BMP4 14 54416455 54423554 96 0.013
66 14 60975938 60978525 102 0.11
GJD2 15 35044642 35046782 142 0.00084
RASGRF1 15 79252289 79383215 185 0.014
RBFOX1 16 6069132 7763340 3526 0.30
SHISA6 17 11144740 11467380 NA NA
MYO1D 17 30819628 31203902 266 0.93
B4GALNT2 17 47209822 47247351 94 0.031
KCNJ2 17 68165676 68176183 108 0.56
NPLOC4 17 79523909 79596831 102 0.29
CNDP2 18 72163500 72190689 147 0.30
BMP2 20 6748745 6760910 110 0.052
Table 6
 
Summary of the Three Replication Analyses for the Japanese Cohort That Showed P < 0.05 in at Least One Analysis
Table 6
 
Summary of the Three Replication Analyses for the Japanese Cohort That Showed P < 0.05 in at Least One Analysis
Gene Symbol CHR Position NCBI37/hg19 SNP-Based Gene-Based
Bonferroni VEGAS
CD55 1 207494817 207534311 0.043 0.031 0.04995
KCNQ5 6 73331571 73908573 0.0026 0.0048 0.0015
QKI 6 163835675 163999628 0.87 0.0017 0.073
SFRP1 8 41119476 41166990 0.39 0.014 0.52
SH3GL2/(ADAMTSL1) 9 17578953 17797122 0.20 0.044 0.047
BICC1 10 60272904 60588845 0.0019 0.018 0.0060
CYP26A1 10 94833232 94837641 0.023 0.065 0.070
LRRC4C 11 40135751 41481186 0.040 0.10 0.14
EHBP1L1 11 65343509 65360116 NA 0.025 0.088
GRIA4 11 105480800 105852819 0.36 0.049 0.35
BMP4 14 54416455 54423554 0.33 0.014 0.013
GJD2 15 35044642 35046782 3.7E-06 0.000082 0.00084
RASGRF1 15 79252289 79383215 0.00094 0.025 0.014
B4GALNT2 17 47209822 47247351 0.039 0.079 0.031
BMP2 20 6748745 6760910 0.32 0.021 0.052
Supplementary Figure S1
Supplementary Tables
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