Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2018 Jun;50(6):834-848.
doi: 10.1038/s41588-018-0127-7. Epub 2018 May 28.

Genome-wide Association Meta-Analysis Highlights Light-Induced Signaling as a Driver for Refractive Error

Milly S Tedja  1   2 Robert Wojciechowski  3   4   5 Pirro G Hysi  6 Nicholas Eriksson  7 Nicholas A Furlotte  7 Virginie J M Verhoeven  1   2   8 Adriana I Iglesias  1   2   8 Magda A Meester-Smoor  1   2 Stuart W Tompson  9 Qiao Fan  10 Anthony P Khawaja  11   12 Ching-Yu Cheng  10   13 René Höhn  14   15 Kenji Yamashiro  16 Adam Wenocur  17 Clare Grazal  17 Toomas Haller  18 Andres Metspalu  18 Juho Wedenoja  19   20 Jost B Jonas  21   22 Ya Xing Wang  22 Jing Xie  23 Paul Mitchell  24 Paul J Foster  12 Barbara E K Klein  9 Ronald Klein  9 Andrew D Paterson  25 S Mohsen Hosseini  25 Rupal L Shah  26 Cathy Williams  27 Yik Ying Teo  28   29 Yih Chung Tham  13 Preeti Gupta  30 Wanting Zhao  10   31 Yuan Shi  31 Woei-Yuh Saw  32 E-Shyong Tai  29 Xue Ling Sim  29 Jennifer E Huffman  33 Ozren Polašek  34 Caroline Hayward  33 Goran Bencic  35 Igor Rudan  36 James F Wilson  33   36 CREAM Consortium23andMe Research TeamUK Biobank Eye and Vision ConsortiumPeter K Joshi  36 Akitaka Tsujikawa  16 Fumihiko Matsuda  37 Kristina N Whisenhunt  9 Tanja Zeller  38 Peter J van der Spek  39 Roxanna Haak  39 Hanne Meijers-Heijboer  40   41 Elisabeth M van Leeuwen  1   2 Sudha K Iyengar  42   43   44 Jonathan H Lass  42   43 Albert Hofman  2   45   46 Fernando Rivadeneira  2   46   47 André G Uitterlinden  2   46   47 Johannes R Vingerling  1 Terho Lehtimäki  48   49 Olli T Raitakari  50   51 Ginevra Biino  52 Maria Pina Concas  53 Tae-Hwi Schwantes-An  4   54 Robert P Igo Jr  42 Gabriel Cuellar-Partida  55 Nicholas G Martin  56 Jamie E Craig  57 Puya Gharahkhani  55 Katie M Williams  6 Abhishek Nag  58 Jugnoo S Rahi  12   59   60 Phillippa M Cumberland  59 Cécile Delcourt  61 Céline Bellenguez  62   63   64 Janina S Ried  65 Arthur A Bergen  40   66   67 Thomas Meitinger  68   69 Christian Gieger  65 Tien Yin Wong  70   71 Alex W Hewitt  23   72   73 David A Mackey  23   72   73 Claire L Simpson  4   74 Norbert Pfeiffer  15 Olavi Pärssinen  75   76 Paul N Baird  23 Veronique Vitart  33 Najaf Amin  2 Cornelia M van Duijn  2 Joan E Bailey-Wilson  4 Terri L Young  9 Seang-Mei Saw  29   77 Dwight Stambolian  17 Stuart MacGregor  55 Jeremy A Guggenheim  26 Joyce Y Tung  7 Christopher J Hammond  6 Caroline C W Klaver  78   79   80
Collaborators, Affiliations
Free PMC article
Meta-Analysis

Genome-wide Association Meta-Analysis Highlights Light-Induced Signaling as a Driver for Refractive Error

Milly S Tedja et al. Nat Genet. .
Free PMC article

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.

Conflict of interest statement

Competing interests

N.A.F., N.E., J.Y.T., and the 23andMe Research Team are current or former employees of 23andMe, Inc., and hold stock or stock options in 23andMe. J.B. J. is a patent holder with Biocompatibles UK Ltd. (Franham, Surrey, UK) (Title: Treatment of eye diseases using encapsulated cells encoding and secreting neuroprotective factor and/or anti-angiogenic factor; Patent number: 20120263794), and patent application with University of Heidelberg (Heidelberg, Germany) (Title: Agents for use in the therapeutic or prophylactic treatment of myopia or hyperopia; European Patent Number: 3 070 101). The other authors declare no competing financial interests.

Figures

Figure 1
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
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
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
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
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
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.

Similar articles

  • Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia.
    Verhoeven VJ, Hysi PG, Wojciechowski R, Fan Q, Guggenheim JA, Höhn R, MacGregor S, Hewitt AW, Nag A, Cheng CY, Yonova-Doing E, Zhou X, Ikram MK, Buitendijk GH, McMahon G, Kemp JP, Pourcain BS, Simpson CL, Mäkelä KM, Lehtimäki T, Kähönen M, Paterson AD, Hosseini SM, Wong HS, Xu L, Jonas JB, Pärssinen O, Wedenoja J, Yip SP, Ho DW, Pang CP, Chen LJ, Burdon KP, Craig JE, Klein BE, Klein R, Haller T, Metspalu A, Khor CC, Tai ES, Aung T, Vithana E, Tay WT, Barathi VA; Consortium for Refractive Error and Myopia (CREAM), Chen P, Li R, Liao J, Zheng Y, Ong RT, Döring A; Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Group, Evans DM, Timpson NJ, Verkerk AJ, Meitinger T, Raitakari O, Hawthorne F, Spector TD, Karssen LC, Pirastu M, Murgia F, Ang W; Wellcome Trust Case Control Consortium 2 (WTCCC2), Mishra A, Montgomery GW, Pennell CE, Cumberland PM, Cotlarciuc I, Mitchell P, Wang JJ, Schache M, Janmahasatian S, Igo RP Jr, Lass JH, Chew E, Iyengar SK; Fuchs' Genetics Multi-Center Study Group, Gorgels TG, Rudan I, Hayward C, Wright AF, Polasek O, Vatavuk Z, Wilson JF, Fleck B, Zeller T, Mirshahi A, Müller C, Uitterlinden AG, Rivadeneira F, Vingerling JR, Hofman A, Oostra BA, Amin N, Bergen AA, Teo YY, Rahi JS, Vitart V, Williams C, Baird PN, Wong TY, Oexle K, Pfeiffer N, Mackey DA, Young TL, van Duijn CM, Saw SM, Bailey-Wilson JE, Stambolian D, Klaver CC, Hammond CJ. Verhoeven VJ, et al. Nat Genet. 2013 Mar;45(3):314-8. doi: 10.1038/ng.2554. Epub 2013 Feb 10. Nat Genet. 2013. PMID: 23396134 Free PMC article. Clinical Trial.
  • Childhood gene-environment interactions and age-dependent effects of genetic variants associated with refractive error and myopia: The CREAM Consortium.
    Fan Q, Guo X, Tideman JW, Williams KM, Yazar S, Hosseini SM, Howe LD, Pourcain BS, Evans DM, Timpson NJ, McMahon G, Hysi PG, Krapohl E, Wang YX, Jonas JB, Baird PN, Wang JJ, Cheng CY, Teo YY, Wong TY, Ding X, Wojciechowski R, Young TL, Pärssinen O, Oexle K, Pfeiffer N, Bailey-Wilson JE, Paterson AD, Klaver CC, Plomin R, Hammond CJ, Mackey DA, He M, Saw SM, Williams C, Guggenheim JA; CREAM Consortium. Fan Q, et al. Sci Rep. 2016 May 13;6:25853. doi: 10.1038/srep25853. Sci Rep. 2016. PMID: 27174397 Free PMC article.
  • Nine loci for ocular axial length identified through genome-wide association studies, including shared loci with refractive error.
    Cheng CY, Schache M, Ikram MK, Young TL, Guggenheim JA, Vitart V, MacGregor S, Verhoeven VJ, Barathi VA, Liao J, Hysi PG, Bailey-Wilson JE, St Pourcain B, Kemp JP, McMahon G, Timpson NJ, Evans DM, Montgomery GW, Mishra A, Wang YX, Wang JJ, Rochtchina E, Polasek O, Wright AF, Amin N, van Leeuwen EM, Wilson JF, Pennell CE, van Duijn CM, de Jong PT, Vingerling JR, Zhou X, Chen P, Li R, Tay WT, Zheng Y, Chew M; Consortium for Refractive Error and Myopia, Burdon KP, Craig JE, Iyengar SK, Igo RP Jr, Lass JH Jr; Fuchs' Genetics Multi-Center Study Group, Chew EY, Haller T, Mihailov E, Metspalu A, Wedenoja J, Simpson CL, Wojciechowski R, Höhn R, Mirshahi A, Zeller T, Pfeiffer N, Lackner KJ; Wellcome Trust Case Control Consortium 2, Bettecken T, Meitinger T, Oexle K, Pirastu M, Portas L, Nag A, Williams KM, Yonova-Doing E, Klein R, Klein BE, Hosseini SM, Paterson AD; Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions, and Complications Research Group, Makela KM, Lehtimaki T, Kahonen M, Raitakari O, Yoshimura N, Matsuda F, Chen LJ, Pang CP, Yip SP, Yap MK, Meguro A, Mizuki N, Inoko H, Foster PJ, Zhao JH, Vithana E, Tai ES, Fan Q, Xu L, Campbell H, Fleck B, Rudan I, Aung T, Hofman A, Uitterlinden AG, Bencic G, Khor CC, Forward H, Pärssinen O, Mitchell P, Rivadeneira F, Hewitt AW, Williams C, Oostra BA, Teo YY, Hammond CJ, Stambolian D, Mackey DA, Klaver CC, Wong TY, Saw SM, Baird PN. Cheng CY, et al. Am J Hum Genet. 2013 Aug 8;93(2):264-77. doi: 10.1016/j.ajhg.2013.06.016. Am J Hum Genet. 2013. PMID: 24144296 Free PMC article.
  • [Advances in genome-wide association study of myopia].
    Liao X, Lan CJ. Liao X, et al. Zhonghua Yan Ke Za Zhi. 2016 Oct 11;52(10):794-800. doi: 10.3760/cma.j.issn.0412-4081.2016.10.019. Zhonghua Yan Ke Za Zhi. 2016. PMID: 27760653 Review. Chinese.
  • Genome-wide association studies of refractive error and myopia, lessons learned, and implications for the future.
    Hysi PG, Wojciechowski R, Rahi JS, Hammond CJ. Hysi PG, et al. Invest Ophthalmol Vis Sci. 2014 May 29;55(5):3344-51. doi: 10.1167/iovs.14-14149. Invest Ophthalmol Vis Sci. 2014. PMID: 24876304 Free PMC article. Review.
See all similar articles

Cited by 32 articles

See all "Cited by" articles

References

    1. Pan CW, Ramamurthy D, Saw SM. Worldwide prevalence and risk factors for myopia. Ophthalmic Physiol Opt. 2012;32:3–16. - PubMed
    1. Morgan IG. What Public Policies Should Be Developed to Deal with the Epidemic of Myopia? Optom Vis Sci. 2016;93:1058–60. - PubMed
    1. Morgan I, Rose K. How genetic is school myopia? Prog Retin Eye Res. 2005;24:1–38. - PubMed
    1. Morgan IG, Ohno-Matsui K, Saw SM. Myopia. Lancet. 2012;379:1739–48. - PubMed
    1. Williams KM, et al. Increasing Prevalence of Myopia in Europe and the Impact of Education. Ophthalmology. 2015;122:1489–97. - PMC - PubMed

Publication types

Feedback