AGENTS FOR USE IN THE THERAPEUTIC OR PROPHYLATIC TREATMENT OF MYOPIA OR HYPEROPIA

Abstract

The present invention relates to agents for use in the prophylactic or therapeutic treatment of myopia in a subject, wherein said agents are capable of decreasing epidermal growth factor receptor (EGFR) signaling and/or signaling of another receptor susceptible for amphiregulin in a subject in a direct or indirect manner. The present invention further relates to agents for use in the prophylactic or therapeutic treatment of hyperopia in a subject, wherein said agents are capable of increasing epidermal growth factor receptor (EGFR) signaling and/or signaling of another receptor susceptible for amphiregulin in a subject. Furthermore, the present invention relates to methods for the diagnosis of myopia or hyperopia in a subject, comprising the steps of (a) providing a biological sample from the subject; (b) determining the amphiregulin level in said sample; (c) comparing the level determined in step (b) to the amphiregulin levels found in emmetropic subjects or subjects going to be emmetropic; and (d) determining that the subject has myopia or is predisposed for the development of myopia in case the level determined in step (b) is higher than the amphiregulin levels found in emmetropic subjects or subjects going to be emmetropic; and determining that the subject has hyperopia or is predisposed for the development of hyperopia in case the level determined in step (b) is lower than the amphiregulin levels found in emmetropic subjects or subjects going to be emmetropic. Finally, the present invention relates to a method for identifying agents which associate with amphiregulin or fragments or variants thereof.

Claims

1-15. (canceled)

16. A method for the therapeutic treatment of myopia in a human subject having myopia, comprising administering to the human subject a therapeutically effective amount of an agent that decreases epidermal growth factor receptor (EGFR) signaling in the subject so as to treat the myopia in the subject, wherein said agent is selected from the group consisting of: (a) an isolated antibody, antibody fragment or antibody mimetic directed against native amphiregulin in said subject; (b) an isolated antibody, antibody fragment or antibody mimetic directed against a native amphiregulin precursor in said subject; (c) an isolated antibody, antibody fragment or antibody mimetic directed against EGFR in a blocking manner in said subject; (d) an EGFR inhibiting agent; and (e) a small interfering RNA (siRNA) agent capable of reducing the expression of amphiregulin in a subject.

17. The method of claim 16, wherein said antibody fragment is selected from the group consisting of Fab fragments, F(ab′)2 fragments and Fab′ fragments.

18. The method of claim 16, wherein said antibody mimetic is selected from the group consisting of single-chain variable fragments (scFv), single-domain antibodies, affibodies, affilins, affimers, affitins, anticalins, DARPins, monobodies, and peptide aptamers.

19. The method of claim 16, wherein said agent is administered intravitreally, epicorneally, transcorneally, transsclerally, transconjunctivally, subconjunctivally, or intraocularly.

Description

[0078] The figures show:

[0079] FIG. 1:

[0080] Gross anatomy of the eye.

[0081] Vertical sagittal section of the adult human eye.

[0082] FIG. 2:

[0083] Microscopical anatomy of the eye.

[0084] Organization of the retina in a schematic vertical section. Interneurons are designates as (B) bipolar cells, (A) amacrine cells, (H) horizontal cells, and (IP) interplexiform cells. In reality, the retina is packed with cells, and there is hardly any extracellular space. The ten layers of the retina are listed on the right-hand side of the figure: (1) Pigment epithelium of retina, (2) layer of rods and cones (outer segments of photoreceptors), (3) outer limiting membrane (end-feet of Müller cells), (4) layer of nuclei of photoreceptors, (5) outer plexiform layer (synapses), (6) inner nuclear layer (somata of interneurons and nuclei of Müller cells), (7) inner plexiform layer (synapses), (8) ganglion cell layer, (9) nerve fiber layer, (10) inner limiting membrane (end-feet of Müller cells). The potential space between the pigment epithelium and the layer of rods and cones is the “optic ventricle”, the remnant of the cavity of the optic vesicle.

[0085] FIG. 3A:

[0086] Manhattan plot of −log.sub.10(P) for the Joint meta-analysis on SNP and SNP×education effects on spherical equivalent in European Ancestry populations. The upper horizontal dashed line indicates the genome-wide significance level of p<5×10.sup.−8. The lower horizontal dashed line indicates the suggestive significance level of p<1×10.sup.−5. Only novel loci reaching genome-wide significance are labeled.

[0087] FIG. 3B:

[0088] Manhattan plot of −log.sub.10(P) for the Joint meta-analysis on SNP and SNP×education effects on spherical equivalent in Asian populations.

[0089] The upper horizontal dashed line indicates the genome-wide significance level of p<5×10.sup.−8. The lower horizontal dashed line indicates the suggestive significance level of p<1×10.sup.−5. Only novel loci reaching genome-wide significance are labeled.

[0090] The present invention discloses the following sequences:

TABLE-US-00001 Human amphiregulin amino acid sequence SEQ ID NO: 1 MRAPLLPPAP VVLSLLILGS GHYAAGLDLN DTYSGKREPF SGDHSADGFE VTSRSEMSSG 60 SEISPVSEMP SSSEPSSGAD YDYSEEYDNE PQIPGYIVDD SVRVEQVVKP PQNKTESENT 120 SDKPKRKKKG GKNGKNRRNR KKKNPCNAEF QNFCIHGECK YIEHLEAVTC KCQQEYFGER 180 CGEKSMKTHS MIDSSLSKIA LAAIAAFMSA VILTAVAVIT VQLRRQYVRK YEGEAEERKK 240 LRQENGNVHA IA 252 siRNA antisense strand targeting human amphiregulin mRNA SEQ ID NO: 2 CGAAC CACAA AUACC UGGCT T siRNA antisense strand targeting human amphiregulin mRNA SEQ ID NO: 3 CCUGG AAGCA GUAAC AUGCT T

[0091] The present invention will be further illustrated by the following examples without being limited thereto.

EXAMPLES

Experimental Procedures

[0092] Study Populations

[0093] From the Consortium of Refractive Error and Myopia (CREAM), a total of 34 studies comprising 40,036 individuals of European ancestry from 25 studies and 10,315 individuals of Asian ancestry from 9 studies were recruited. Individuals aged less than 20 years old were excluded, as well as those who had undergone cataract surgery, laser or other intra-ocular procedures that could alter refraction. Many of these studies were also included in the previous CREAM genome-wide association study (GWAS) on spherical equivalent. All studies adhered to the tenets of the Declaration of Helsinki and were approved by their local research ethics committees. All participants provided a written, informed consent before the start of the study.

[0094] Phenotyping and Education Levels

[0095] Participants in the included studies underwent complete ophthalmological examination. Non-dilated refraction was measured by auto-refraction and/or subjective refraction. Spherical equivalent was calculated as the sphere power plus half of the cylinder power for each eye. The mean spherical equivalent of the right and left eyes was used as a quantitative outcome. When data from only one eye was available, the spherical equivalent of that eye was used. For education, subjects reported the highest level of education achieved, or the years of schooling through a self-reported questionnaire or in an interview.

[0096] Education for all participants was dichotomized into a higher education group consisting of those who had completed at least higher secondary education, polytechnic, or 12 years spent in formal education, and a lower education group including individuals who had only completed lower secondary education or less, or with <12 years of formal education. In four cohorts of relatively young European participants (total sample size of 2,349), almost all had completed 12 or more years of schooling. It was thus chosen to categorize individuals with tertiary or university education as the higher education group. Sensitivity analysis excluding these four cohorts did not appreciably change meta-analysis results.

[0097] Genotyping and Imputation

[0098] Each study applied stringent quality control filters for GWAS. In general, individuals reflecting duplicates, low call rate (<95%), gender mismatch, or population outliers we excluded. SNPs were excluded in cases of low genotyping call rate (>5% missingness), monomorphic SNPs, with MAF<1%, or in Hardy-Weinberg disequilibrium (p-value<10.sup.−6). After quality control (QC) filtering, the array genotypes of each study were imputed using the 1000 Genomes Project data as reference panels (build 37, phase 1 release, March 2012) with the software Minimac or IMPUTE. SNPs which passed imputation quality thresholds (MACH: r.sup.2>0.5 or IMPUTE info score>0.5) and with minor allele frequency 5% were carried forward for the meta-analysis.

[0099] Statistical Models

[0100] For each study, a linear regression model at each genotyped or imputed SNP was constructed, with the mean spherical equivalent as the outcome. An additive genetic model was assumed where the number of risk alleles is an ordinal variable (0, 1 and 2) for directly genotyped SNPs, or a continuous variable of allele dosage probability ranging from 0 to 2 for imputed SNPs. The primary analytic model included SNP, education, a SNP×education interaction term, as well as age and sex as covariates. Additional adjustments for the top principal components of genomic marker variations were performed in individual studies when applicable (i.e., when there was evidence of population stratification).

[0101] The following additive genetic model was used to test for a joint effect of SNP (β.sub.SNP) and SNP×education interaction (β.sub.SNP×education) on mean spherical equivalent:

Y=β.sub.0+β.sub.SNP×SNP+β.sub.education×Education+β.sub.SNP×education×SNP×Education+β.sub.c×Cov+ε  (Model 1)

where Y is the mean spherical equivalent, education is a dichotomous variable (0=lower education group and 1=higher education group); Coy is a set of covariates such as age, sex and first top five principal components when applicable. For family-based studies, the kinship matrix was estimated empirically from the SNP data and included as a random effect in the generalized mixed model. To test an effect of SNP×education interaction, β.sub.SNP×education was assessed from Model 1.

[0102] The linear regression analyses in each study were conducted with Quickest (http://toby.freeshell.org/software/quicktest.shtml) or ProbABEL (http://www.genabel.org/packages/ProbABEL) for the unrelated samples, and MixABEL (http://www.genabel.org/packages/MixABEL) for family-based data. The command ‘robust’ was used in the above software to calculate the robust (‘sandwich’, Huber-White) standard errors of β.sub.SNP and β.sub.SNP×education, and error covariance of βs, to correct the potential inflation of false positive rate for the interaction p-value.

[0103] In addition, each study also tested the main effect of education on spherical equivalent by adjusting for age and gender using the linear regression model:

Y=β.sub.0+β.sub.education×education+β.sub.c×Cov+ε  (Model 2)

where the definition of the variables is the same as in Model 1.

[0104] GWAS Meta-Analyses

[0105] The joint meta-analysis (JMA) approach was adopted to simultaneously test both main SNP effects and SNP×education interactions for spherical equivalent with a fixed-effect model, using SNP and SNP×education regression coefficients and a betas' covariance matrix from each study. A Wald statistic, following a chi-square distribution with two degrees of freedom, was used to test the joint significance of the SNP and SNP×education regression coefficients. The JMA was performed with METAL (http://www.sph.umich.edu/csg/abecasis/metal/), using a script patch. A Cochran's Q test was used to assess heterogeneity of the beta coefficients across studies for the SNP and interaction effects. To test for interaction between the SNP and education, a secondary meta-analysis of the SNP×education interaction effects for spherical equivalent (one degree of freedom) with a fixed-effects model using inverse-variance weighting in METAL was conducted; this is a traditional meta-analysis to investigate SNP×education interactions per se. Effects and standard error of the SNP (β.sub.SNP) on spherical equivalent in the lower education group and higher education (β.sub.SNP+β.sub.SNP×education) were derived from the JMA output.

[0106] A meta-regression was performed to explore sources of heterogeneity in the meta-analysis for three loci showing G×E interactions (R package Thetafor; http://www.rproject.org/). Meta-regression included the following study-specific variables as covariates: study sample size, proportion of individuals in the higher education group, average spherical equivalent, education main effects, ethnicity, study design, study year, and average age.

[0107] The study-specific genomic control inflation factors λ.sub.gc for the joint test for SNP and interaction term ranged from 1.009 to 1.125 with an average of 1.019, calculated by the ratio of the observed median chi-square divided by the expected median of the 2df chi-square distribution (1.382). Genomic control (GC) correction was applied to chi-square statistics in each individual study. For three studies of small sample sizes (N<500) and λ.sub.gc greater than 1, SNPs showing significant joint P value<1×10.sup.−5 were further excluded prior to starting the meta-analysis, but neither the main effects nor the interaction effects supporting such an association. Quantile-quantile (QQ) plots of the p-values showed only modest inflation of the test statistics in the JMA (Europeans: Ameta=1.081; Asians: λ.sub.meta=1.053; Combined: λ.sub.meta=1.092, similar to previous genome-wide JMA studies with comparable sample sizes. A small number of markers in the meta-analysis with P.sub.HET<0.0001 was excluded. The λ.sub.gc for the SNP×education interaction term in the individual studies ranged from 1.01 to 1.08, indicating little evidence of test statistic inflation for each study.

[0108] Annotation of Genetic Variants

[0109] The coordinates and variant identifiers are reported on the NCBI B37 (hg19) genome build, and annotated using UCSC Genome Browser. Variants within each of the linkage disequilibrium (LD) blocks (r.sup.2>0.8) in European and Asian populations of the 1000 Genomes Project (100 Kb flanking the top SNP; hg19) were identified to apply functional annotations with experimental evidence of transcription regulation using HaploReg (http://www.broadinstitute.org/mammals/haploreg/haploreg.php) and Encyclopedia of DNA Elements (ENCODE) data.

[0110] Gene Expression in Human Tissues GWAS Meta-Analyses and SNP Function Annotation

[0111] To assess gene expression in human tissues, the Ocular Tissue Database (https://genome.uiowa.edu/otdb) and the EyeSAGE database were examined. The estimated gene and exome level abundances are available online. Normalization of gene expression used the Probe Logarithmic Intensity Error (PLIER) method with GC-background correction.

Example 1

[0112] Education and its Main Effects on Spherical Equivalent

[0113] Baseline characteristics of 50,351 participants from 34 studies in our meta-analysis show that a total of 40,036 of subjects were of European ancestry and 10,315 were of Asian ancestry; the age of the participants ranged from 20 to 99 years. Among Europeans, the proportions of participants who completed higher secondary education ranged from 16.0% to 94.4% with an average of 50.7%. In Asians, the proportions of individuals who completed higher secondary education ranged from 6.7% to 75.9% with an average of 30.0%. Across all studies, individuals in the higher education group had a spherical equivalent refractive error that was on average 0.59 diopters (D) more myopic, or less hyperopic, compared to those in the lower education group (β=−0.59; 95% CI: −0.64, −0.55). High education level was associated with a two-fold more myopic spherical equivalent in individuals of Asian as compared to European ancestry (Asians: β=−1.09, 95% CI: −1.20, −0.98; Europeans: β=−0.49, 95% CI: −0.54, −0.44.

Example 2

[0114] Joint Meta-Analysis in Europeans

[0115] The genome-wide joint analysis for SNP main effect and SNP×education interaction by JMA in 40,036 European Ancestry individuals showed association with spherical equivalent at 9 previously implicated loci. Further, 4 previously unreported loci associated with spherical equivalent were also identified achieving genome-wide significance (P for JMA<5.0×10.sup.−8; Table 1 and FIG. 3 A): FAM150B, LINC00340, FBN1, and DIS3L-MAP2K1. Two of them (FAM150B and DIS3L-MAP2K1) were replicated in Asians (P for JMA<0.05; refer to the following section). Little evidence of heterogeneity in JMA was noted across studies (Q test: P.sub.het≥0.086). The significant association for JMA at these loci in Europeans was primarily due to SNP effects in both lower and higher education strata (4.40×10.sup.−8≤P≤1.35×10.sup.−6, 7.61×10.sup.−11≤P≤1.75×10.sup.−8, respectively). SNP×education interaction was not significant (P for interaction 0.208). The estimated effect sizes of SNP effects on spherical equivalent were highly similar across education strata.

TABLE-US-00002 TABLE 1 Six genetic loci associated with spherical equivalent from the joint meta-analysis in the European populations and combined analysis. Europeans (n = 40,306) SNP (Chr: BP) Gene Allele FREQ Subgroup β P rs60843830 FAM150B C/G 0.66/0.74 JMA 3.71 × 10.sup.−8 (2: 286756) Lower educaton −0.11 4.73 × 10.sup.−8 Higher education −0.09 1.75 × 10.sup.−6 rs10946507 LINC00340 A/G 0.47/0.36 JMA 3.07 × 10.sup.−8 (6: 22100367) Lower educaton −0.08 7.08 × 10.sup.−7 Higher education −0.09 1.19 × 10.sup.−8 rs8023401 FBN1 G/A 0.83/0.85 JMA 1.66 × 10.sup.−9 (15: 48703823) Lower educaton −0.15 4.40 × 10.sup.−8 Higher education −0.16 .sup. 7.61 × 10.sup.−11 rs16949788 DIS3L-MAP2K1 T/C 0.91/0.94 JMA 1.34 × 10.sup.−8 (15: 66590037) Lower educaton −0.15 1.35 × 10.sup.−6 Higher education −0.17 1.89 × 10.sup.−9 rs10880855 ARID2 T/C 0.51/0.43 JMA 7.83 × 10.sup.−7 (12: 46144855) Lower educaton −0.09 1.26 × 10.sup.−7 Higher education −0.07 1.60 × 10.sup.−8 rs10853531 SLC14A2 G/A 0.70/0.77 JMA 7.82 × 10.sup.−6 (18: 42824449) Lower educaton −0.11 1.27 × 10.sup.−6 Higher education −0.08 2.12 × 10.sup.−6 Europeans Asians All (n = 40,306) (n = 10,315) (n = 50,351) SNP (Chr: BP) P.sub.het β P P.sub.het β P P.sub.het rs60843830 0.086 0.0131 0.980 1.27 × 10.sup.−9 0.395 (2: 286756) −0.09 0.010 −0.10 1.65 × 10.sup.−9 −0.06 0.509 −0.09 9.83 × 10.sup.−7 rs10946507 0.213 0.433 0.396 2.24 × 10.sup.−8 0.249 (6: 22100367) −0.04 0.313 −0.08 6.13 × 10.sup.−7 −0.08 0.450 −0.09 1.20 × 10.sup.−8 rs8023401 0.130 0.572 0.979 2.85 × 10.sup.−9 0.495 (15: 48703823) −0.06 0.304 −0.13 8.17 × 10.sup.−8 −0.03 0.828 −0.14 2.02 × 10.sup.−9 rs16949788 0.721 0.0042 0.219 2.19 × 10.sup.−8 0.245 (15: 66590037) 0.21 0.103 −0.13 4.88 × 10.sup.−6 −0.59 0.014 −0.16 3.90 × 10.sup.−9 rs10880855 0.790 0.019 0.779 4.38 × 10.sup.−8 0.867 (12: 46144855) −0.06 0.067 −0.09 8.42 × 10.sup.−9 −0.16 0.033 −0.07 3.55 × 10.sup.−6 rs10853531 0.052 0.0023 0.812 2.54 × 10.sup.−8 0.111 (18: 42824449) −0.15 9.01 × 10.sup.−4 −0.11 3.38 × 10.sup.−9 −0.11 0.288 −0.09 7.14 × 10.sup.−6 JMA, joint meta-analysis on SNP association and SNP × education on spherical equivalent; the effects estimates presented are derived from the JMA for the lower and higher education group. P.sub.het, p-value for the test of heterogeneity at each SNP; Allele is listed as risk allele/other allele; FREQ, allele frequency of the risk allele in Asian/European cohorts.

Example 3

[0116] Joint Meta-Analysis in Asians

[0117] The JMA for spherical equivalent in 10,315 individuals from the Asians cohorts identified genome-wide significant association for three genes: AREG, GABRR1 and PDE10A (P for JMA<5.0×10.sup.−8; Table 2 and FIG. 3 B). SNP×education interaction effects associated with spherical equivalent were observed at all three loci (P for interaction 8.48×10.sup.−5). The genotype and phenotype associations were highly significant in the higher education stratum (1.97×10.sup.−10 8.16×10.sup.−8) but were considerably weaker in the lower education stratum (0.008≤P≤0.243). There was no evidence of inter-study heterogeneity at index SNPs within AREG, GABRR1 or PDE10A (Q test: P.sub.het≥0.122).

[0118] GABRR1 and PDE10A index SNPs were not associated with spherical equivalent in European samples, for either the JMA joint test, SNP main effect, or SNP×education interaction (Table 2). AREG SNP rs12511037 was excluded in the meta-analysis of European studies after quality control filtering (due to MAF<0.05), hence a proxy SNP, rs1246413, in LD with rs12511037 (r.sup.2=0.67, D′=1) was tested, whereas insignificant association (P for JMA=0.527; Pfor interaction=0.176). The meta-regression including study-level characteristics as covariates in the model confirmed the heterogeneity between populations of European and Asian ancestry (GABRR1 SNP rs13215566: P=0.006; PDE10A SNP rs12206610: P=0.0419). For PDE10A, besides ethnicity, average spherical equivalent of each study also explained the inter-study heterogeneity for the interaction effects (P=0.025).

[0119] It was further examined whether the underlying assumption of G×E independence held at these three G×E interaction loci. A meta-analysis of logistic regression analysis was performed for education level on AREG rs12511037, GABRR1 rs13215566 and PDE10A rs12296610, adjusting for age, gender and population stratification in the Singapore cohorts (n=9,004). The analysis did not reveal any significant associations between these loci and education level (P≥0.200, P.sub.het≥0.118). Furthermore, the three loci were also not associated with educational attainment in a large meta-analysis of GWAS recently conducted in European cohorts. Thus, the G×E results are unlikely to be biased due to dependence between gene and education.

[0120] The association for spherical equivalent in Asian cohorts for four loci identified from European populations was also evaluated. Two of them were replicated (FAM150B: P for JMA=0.013; DIS3L-MAP2K1: P for JMA=0.0042; Table 1). DIS3L-MAP2K1 also showed suggestive SNP×education interaction in Asians (P for interaction=7.95×10.sup.−4), while this was not significant in Europeans (Pfor interaction=0.208).

TABLE-US-00003 TABLE 2 Three genetic loci associated with spherical equivalent with a significant SNP × education interaction in Asian populations, and results in European populations Asians Europeans (n = 10,315) (n = 40,306) SNP (Chr: BP) Gene Allele FREQ Subgroup β P P.sub.het β P P.sub.het rs12511037 AREG C/T 0.91/0.97 Lower educaiton 0.07 0.243 −0.05 0.323 (4: 75334864) Higher education −0.70 .sup. 1.97 × 10.sup.−10 −0.03 0.579 G × E −0.89 .sup. 6.87 × 10.sup.−11 0.704 0.02 0.176 0.284 JMA .sup. 5.55 × 10.sup.−10 0.405 0.527 0.186 rs13215566 GABRR1 C/G 0.94/0.84 Lower educaiton −0.13 0.030 −0.03 0.258 (6: 89918638) Higher education −0.68 1.46 × 10.sup.−8 −0.01 0.817 G × E −0.56 8.48 × 10.sup.−5 0.134 −0.02 0.459 0.457 JMA 3.81 × 10.sup.−8 0.122 0.502 0.630 rs12206610 PDE10A C/T 0.90/0.87 Lower educaiton 0.16 0.008 0.01 0.759 6: 166016800 Higher education −0.59 8.16 × 10.sup.−8 0.01 0.810 G × E −0.72 2.32 × 10.sup.−8 0.920 −0.002 0.421 0.111 JMA 9.21 × 10.sup.−9 0.902 0.954 0.305 JMA, joint meta-analysis on SNP association and SNP × education on spherical equivalent; the effects estimates presented are derived from the JMA for the lower and higher education group. The effect size and p-value for SNP × education interaction were calculated by the meta-analysis of conducting a 1df Wald test of single interaction parameter (SNP × education). P.sub.het, p-value for the test of heterogeneity; Allele is listed as risk allele/other allele; FREQ, allele frequency of the risk allele in Asian/European cohorts. SNP rs12511037 was excluded in met-analysis in Europeans because of low MAF (MAF < 0.05). Here we present the results of a proxy SNP rs1246413 (T/G, FREQ for effect allele T = 0.95) in LD with rs12511037 (r.sup.2 = 0.67, D′ = 1) for Europeans.

Example 4

[0121] Joint Meta-Analysis of all Cohorts

[0122] Subsequently, a combined meta-analysis was conducted, including both the European and Asian subjects of all 34 studies. This analysis revealed two additional SNPs: ARID2 (P for JMA=4.38×10.sup.−8) and SLC14A2 (P for JMA=2.54×10.sup.−8). Both loci showed suggestive association with spherical equivalent in European cohorts, while the association was attenuated in Asian cohorts (Table 1). Genome-wide significant associations were also detected with spherical equivalent for 17 known loci identified in the previous CREAM GWAS.

Example 5

[0123] Gene and Education Interactions for GWAS Known Loci

[0124] For the previously reported genetic association with spherical equivalent at 39 loci identified from recent two large GWAS, interactions with education were evaluated. Two SNP×education interactions were nominally significant: TJP2 in Europeans (rs11145488; P for interaction=6.91×10.sup.−3) and SHISA6-DNAH9 in Asians (rs2969180; P for interaction=4.02×10.sup.−3). In general, the index SNPs tested at 39 loci had larger SNP×education interaction effect on spherical equivalent (meta-regression P for fold changes<0.001). For 20 SNPs with the same direction of the interaction effect, the magnitudes of interaction effects were 4-fold larger on average in Asians than in Europeans (meta-regression P=0.003).

Example 6

[0125] Gene Expression in Human Tissues

[0126] Using Ocular Tissue Database, the expression of the associated genes was examined in 20 normal human donor eyes. The majority of genes identified were expressed in human retina, sclera or retinal pigment epithelium (RPE) (Table 3). Among these genes, GABRR1 had the highest expression in the retina. The PLIER normalized level of expression of GABRR1 in the retina was 121.7 with an expression value of 21.5 in sclera, suggesting the expression of GABRR1 is more prevalent within the retina. FAM150B was found highly present in the choroid/RPE (expression value of 333.3), while expressed at a much lower level in the retina (29.9). MAP2K1 was widely expressed in the retina, sclera and choroid with expression values greater than 85.7.

TABLE-US-00004 TABLE 3 Gene expression of identified loci in human ocular tissues GENE Retina Sclera Choroid/RPE FAM150B 29.94 62.13 333.33 PRL 43.48 24.74 43.64 FBN1 12.88 75.26 47.08 MAP2K1 85.72 91.26 183.61 DIS3L 43.20 32.95 42.16 SLC14A2 29.96 34.87 33.69 AREG 21.31 26.04 29.64 GABRR1 121.66 21.48 31.43 PDE10A 28.19 18.87 21.46 Expression data was obtained from Ocular Tissue Database. The Affymetrix GeneChip Human Exon 1.0 ST (HuEx 1.0) microarrays were used to assess gene expression. Normalization of gene expression was done at both the probe set and metaprobe set level using the Probe Logarithmic Intensity Error (PLIER) method with GC-background correction. The PLIER normalized level of gene expression was presented in the table.

Discussion

[0127] The above data represent the most comprehensive genome-wide analysis to date of gene and education interactions in relation to refractive error. Novel genetic loci associated with refractive error were identified by testing the joint contribution of SNP and SNP×education effects in large multi-ethnic populations. Three genes (AREG, GABRR1 and PDE10A) showed strong interactions with education in populations of Asian descent. Apart from confirming known associations with spherical equivalent with 17 previous published loci, using a combined multiracial cohort, 6 novel loci (FAM150B, LINC00340, FBN1, DIS3L-MAP2K1, ARID2 and SLC14A2) significantly associated with spherical equivalent were identified.

[0128] Of the novel loci, GABRR1 on chromosome 6q15 (53 kb) is an especially interesting functional candidate suggestive of a role in myopia development. Modulation of synaptic plasticity via GABA-mediated inhibition would be well-placed to alter the “gain” of the visually-guided feedback system controlling refractive development. The lead SNP rs12215566 in GABRR1, together with 7 SNPs within the LD block (r.sup.2>0.8), are intronic potentially affecting regulatory motifs (such as zfp128 and gcm1) which may influence transcriptional regulation. As one of the major inhibitory neurotransmitters in the retina, GABA is active in large retinal cells and amacrine cells. It has been reported that antagonists to GABA A, B, and C receptors inhibited form-deprivation myopia in chicks, with greatest effect in the equatorial dimension. GABA receptors also interact with dopamine pathways in the retina. A recent proteomics study has also showed that levels of GABA transporter-1 (GAT-1) are significantly reduced in myopic murine retina after atropine treatment, implying GABA signaling is involved in anti-myopic effects of atropine. Therefore, the present result in humans is in line with animal experiments, supporting the notion that the GABAergic neurotransmitter signaling pathway in the retina could be a potential player in the progression of myopia.

[0129] The rs10889855 on chromosome 6 is an intronic variant within the ARID2 gene (AT Rich Interactive Domain 2) and about 500 kb downstream of SNAT1 (Solute Carrier Family 38, Member; Aliases SLC38A1). SNAT1 is a transporter of glutamine, a precursor of GABA. It is also highly expressed in human retina. In previous meta-analysis in CREAM, variants in another glutamate receptor gene GRIA4 (encoding glutamate receptor, ionotropic) were identified; altogether current evidence supports the notion that retinal neurotransmitters GABA and glutamine may be involved in the refractive development.

[0130] The strongest association signal for gene and environment interactions was from rs12511037, located 14 kb downstream the AREG gene (amphiregulin). AREG is a ligand of the epidermal growth factor receptor (EGFR) promoting the growth of normal epithelial cells, which is critical for cell differentiation and proliferation such as regrowth of the wounded cornea. A link has been found between the muscarinic acetylcholine receptors and the EGFR, as EGFR controls fluid secretion in muscarinic system.

[0131] Another novel association, rs16949788 on chromosome 15, derives from a region that spans DIS3L and MAP2K1. MAP2K1 encodes mitogen-activated protein kinase 1 which binds to muscarinic receptors during proliferation and inhibits the proliferation of human scleral fibroblasts exposed to all-trans retinoic acid. The muscarinic antagonist atropine inhibits the development of myopia in animal models and human intervention studies. All-trans retinoic acid is a modulator of ocular growth, inhibiting the proliferation of human scleral fibroblasts.

[0132] FBN1 (Fibrillin 1) encodes a large extracellular matrix glycoprotein, a member of the fibrillin family. Mutations in FBN1 cause Marfan's syndrome, a disorder of connective tissue affecting the ocular, skeletal and cardiovascular systems. As a candidate gene for myopia, attempts to study its association with myopia previously produced inconclusive results, probably due, in part, to underpowered studies with insufficient sample sizes. Using data from a large multi-ethnic population, the present results support the role of FBN1 in myopia development.

[0133] The genome-wide significant SNPs for the JMA did not exhibit any interactions with education in Europeans, in contrast to the significant interactive effect among Asians. In particular, the interactions of AREG, GABRR1 and PDE10A with education were evident in Asian populations only, but not in Europeans. There are a number of possible reasons. First, the observed heterogeneity may reflect the intense education systems in Asia. The higher education level was associated with myopic shift at an average of a 1.16 D in refraction in Asians, but with only a 0.56 D in Europeans. It is possible that the gene and education interplay may manifest more in such a condition with the strong education effects, as genetic effects are generally modest across the populations. Second, the population distribution of refractive error is more myopic in Asians (−0.60 D versus 0.10 D in Europeans). A high prevalence of myopia is likely to associate with other unmeasured lifestyle exposures, which were not accounted for in the current study. Third, education systems varied widely across studies. We chose to divide education levels into two categories but this cut-off may not reflect the same education intensity or true underlying risk for myopia across Europeans and Asians. Any misclassification in environment measurements may bias the effect towards or away from the null. Last, education in adults may not be an accurate surrogate for cumulative near work activity. The level of education attained may be a crude marker of reading intensity and computer use during the crucial years prior to the onset of myopia. These factors, accompanying with varying allele frequencies at the associated SNPs, might obscure the power to detect the interaction effects in individuals of European ancestry. Whether such G×E interaction is ancestry-specific warrants further evaluation.

[0134] Education level reflects the accumulated effect of near work, such as reading and writing. It was thus examined whether there was evidence for SNP×near work interactions associated with spherical equivalent at the three newly-identified loci (AREG, GABRR1 and PDE10A) in cohorts of children of Asian and European ancestry (combined n=5,835). Tentative support for a SNP×near work interaction was observed for PDE10A SNP rs12206610 (P for interaction=0.032; P.sub.het=0.927). Weaker support for an interaction was noted at GABRR1 SNP rs13215566 (P for interaction=0.109; P.sub.het=0.118) and at the AREG SNP rs12511037 (P for interaction=0.80, P.sub.het=0.224), although the direction of interaction effect was largely consistent across pediatric studies with that observed in adults. A lack of strong SNP×near work associations at these loci leaves open the possibility that environmental risk exposures other than near work might underlie the SNP×education interaction seen in the adult Asian samples.

[0135] In summary, 9 novel loci associated with refractive error were identified in a large multi-ethnic cohort study by a joint meta-analysis approach. The present data provide evidence that specific genetic variants interact with education to influence refractive development, and further support a role for GABA neurotransmitter signaling in myopia development. These findings provide promising candidate genes for follow-up work and may lead to new genetic targets for therapeutic interventions on myopia.