Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error

Abstract

Refractive errors, including myopia, are the most frequent eye disorders worldwide and an increasingly common cause of blindness. This genome-wide association meta-analysis in 160,420 participants and replication in 95,505 participants increased the number of established independent signals from 37 to 161 and showed high genetic correlation between Europeans and Asians (>0.78). Expression experiments and comprehensive in silico analyses identified retinal cell physiology and light processing as prominent mechanisms, and also identified functional contributions to refractive-error development in all cell types of the neurosensory retina, retinal pigment epithelium, vascular endothelium and extracellular matrix. Newly identified genes implicate novel mechanisms such as rod-and-cone bipolar synaptic neurotransmission, anterior-segment morphology and angiogenesis. Thirty-one loci resided in or near regions transcribing small RNAs, thus suggesting a role for post-transcriptional regulation. Our results support the notion that refractive errors are caused by a light-dependent retina-to-sclera signaling cascade and delineate potential pathobiological molecular drivers.

Figure 1. GWAS meta-analysis identifies 140 loci for refractive error (Stage 3)

(a) We conducted a meta-analysis of genome-wide single-variant analyses for >10 million variants in 160,420 participants of CREAM and 23andMe (Stage 3). Shown is the Manhattan plot depicting P for association, highlighting new (P < 5 × 10−8 for the first time; green) and known (dark grey) refractive error loci previously found using HapMap II imputations from Kiefer et al. and Verhoeven et al. (Table 1). The horizontal lines indicate suggestive significance (P=1×10⁻⁵) or genome-wide significance (P=5×10⁻⁸). (b) We compared the minor allele frequencies of the 140 discovered index variants based on 1000G (blue: Europeans; red: Asians) to the minor allele frequencies of the previously found genetic variants based on HapMap II (green: Europeans; purple: Asians). Observed are an increase in genetic variants found across all minor allele frequency bins increase, including the lower minor allele frequency bins. (c) We annotated the 167 loci to genes using wANNOVAR. Shown are the distances between index variants from the nearest gene and its gene on the 5′ and/or 3′ site. The majority of index variants (84%) were at a distance of less than 50 kb up- or downstream from the annotated gene.

Figure 2. Correlation of statistical significance and effect size of SNPs based on spherical equivalent (SphE) in diopters and age of diagnosis of myopia (AODM) in years

(a) P comparison of all genetic variants with P < 1.0 × 10⁻³ (n=7249) between CREAM meta-analysis (Stage 1) and 23andMe (Stage 2) meta-analysis. Shown is the overlap (red) and the difference (green) in P signals per cohort for genetic variants. Green genetic variants are only genome wide significant in either CREAM or 23andMe. Blue: genetic variants with P between 5.0 × 10⁻⁸ and 1.0 × 10⁻³ in both CREAM and 23andMe. (b) Comparison of effects (SphE and logHR of AODM in years; P < 1.0 × 10⁻³; n=7249) between CREAM and 23andMe. Same color code was applied as in (a). The effects were concordant in their direction of effect on refractive error. We performed a simple linear regression between the effects of CREAM and 23andMe; the regression slope is -0.15 diopters per logHR of AODM in years.

Figure 3. Risk of refractive error per decile of polygenic risk score (Rotterdam Study I-III, N=10,792)

Distribution of refractive error in subjects from Rotterdam Study I–III (N=10,792) as a function of the optimal polygenic risk score (including 7,303 variants at P ≤ 0.005 explaining 7.8% of the variance of SphE; Supplementary Table 9). Mean OR of myopia (black line) was calculated per polygenic risk score category using the lowest category as a reference. High myopia (SphE ≤-6 D), moderate myopia (SphE >-6 D & ≤ −3 D), low myopia (SphE > −3 D & <-1.5 D), emmetropia (SphE ≥ −1.5 D and ≤ 1.5 D), low hyperopia (SphE > 1.5 D & < 3 D), moderate hyperopia (SphE ≥ 3 D & 6 D), high hyperopia (SphE ≥ 6 D).

Figure 4. Visualization of the DEPICT gene-set enrichment analysis based on loci associated with refractive error and the correlation between the (meta)gene sets

(a) Shown are the 66 significantly enriched reconstituted gene sets clustered into thirteen meta gene sets based on the gene set enrichment analysis of DEPICT (pairwise Pearson correlations; P < 0.05). All genetic variants with a P < 1 × 10−5 in the GWAS meta-analysis of stage 3 (n=21,073) and an FDR < 0.05 were considered. (b) Visualization of the interconnectivity between gene sets (n=13; pairwise Pearson correlations; P < 0.05) of the meta gene set ‘Detection of Light Stimulus’ (GO:0009583). (c) Visualization of the interconnectivity between gene sets (n=27; pairwise Pearson correlations; P < 0.05) of the largest meta gene set ‘Thin Retinal Outer Nuclear Layer’ (MP:0008515). In all panels, (meta)gene sets are represented by nodes colored according to statistical significance, and similarities between them are indicated by edges scaled according to their correlation; Pearson’s r ≥ 0.2 are shown in panel (a) and Pearson’s r ≥ 0.4 are shown in panel (b,c).

Figure 5. Genes ranked according to biological and statistical evidence

Genes were ranked (orange) based on 10 equal categories which can be divided in four categories: internal replication of genetic variant in more than two cohorts (purple; CREAM-EUR, CREAM-ASN and/or 23andMe), annotation (light blue; genetic variant harboring an exonic protein altering variant or non-protein altering variant, genetic variant residing in a 5′ or 3′ UTR region of a gene or transcribing an RNA structure), expression (yellow; eQTL, expression in adult human ocular tissue, expression in developing ocular tissue), biology (dark yellow; ocular phenotype in mice, ocular phenotype in humans), pathways (green; DEPICT gene-set enrichtment, DEPICT gene prioritization analysis and canonical pathway analysis of IPA). We assessed genes harboring drug targets (salmon red), but did not assign a scoring point to this category. *Only one point can be assigned in the category ‘ANNOTATION’, even though it has four columns (i.e. a genetic variant is located in only 1 of these four categories).

Figure 6. Schematic representation of the human eye, retinal cell types, and functional sites of associated genes

We assessed gene expression sites and/or functional target cells in the eye for all genes using our expression data and literature and data present in the public domain. The genes appear to be distributed across virtually all cell types in the neurosensory retina, in the RPE, vascular endothelium and extracellular matrix; i.e., the route of the myopic retina-to-sclera signalling cascade.