Genome-wide analyses identify 68 new loci associated with intraocular pressure and improve risk prediction for primary open-angle glaucoma

Anthony P Khawaja, Jessica N Cooke Bailey, Nicholas J Wareham, Robert A Scott, Mark Simcoe, Robert P Igo Jr, Yeunjoo E Song, Robert Wojciechowski, Ching-Yu Cheng, Peng T Khaw, Louis R Pasquale, Jonathan L Haines, Paul J Foster, Janey L Wiggs, Chris J Hammond, Pirro G Hysi, UK Biobank Eye and Vision Consortium, NEIGHBORHOOD Consortium, Anthony P Khawaja, Jessica N Cooke Bailey, Nicholas J Wareham, Robert A Scott, Mark Simcoe, Robert P Igo Jr, Yeunjoo E Song, Robert Wojciechowski, Ching-Yu Cheng, Peng T Khaw, Louis R Pasquale, Jonathan L Haines, Paul J Foster, Janey L Wiggs, Chris J Hammond, Pirro G Hysi, UK Biobank Eye and Vision Consortium, NEIGHBORHOOD Consortium

Abstract

Glaucoma is the leading cause of irreversible blindness globally 1 . Despite its gravity, the disease is frequently undiagnosed in the community 2 . Raised intraocular pressure (IOP) is the most important risk factor for primary open-angle glaucoma (POAG)3,4. Here we present a meta-analysis of 139,555 European participants, which identified 112 genomic loci associated with IOP, 68 of which are novel. These loci suggest a strong role for angiopoietin-receptor tyrosine kinase signaling, lipid metabolism, mitochondrial function and developmental processes underlying risk for elevated IOP. In addition, 48 of these loci were nominally associated with glaucoma in an independent cohort, 14 of which were significant at a Bonferroni-corrected threshold. Regression-based glaucoma-prediction models had an area under the receiver operating characteristic curve (AUROC) of 0.76 in US NEIGHBORHOOD study participants and 0.74 in independent glaucoma cases from the UK Biobank. Genetic-prediction models for POAG offer an opportunity to target screening and timely therapy to individuals most at risk.

Conflict of interest statement

Competing Financial Interests

A.P.K. has received a lecturing honorarium from Grafton Optical.

P.J.F. reports personal fees from Allergan, Carl Zeiss, Google/DeepMind and Santen, a grant from Alcon, outside the submitted work

Figures

Figure 1
Figure 1
Scatter plot demonstrating the correlation of effect estimates for SNP associations with IOP in our GWAS meta-analysis with effect estimates for SNP associations with POAG in the NEIGHBORHOOD study. Each point represents one SNP from the 120 independent IOP-associated SNPs (derived from the conditional analysis of our IOP GWAS meta-analysis; 13 of 133 SNPs were not available in NEIGHBORHOOD). The color of each point represents the statistical significance of the SNP association with IOP (see key). Effect estimates are per risk allele.
Figure 2
Figure 2
ROC curves for performance of the POAG-predictive model in HTG (left; n=1,298) and NTG (right; n=561) subsets versus controls (n = 2,606) from a subset of the NEIGHBORHOOD study with individual level genotype data available.

References

    1. Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012;96:614–618.
    1. Topouzis F, et al. Prevalence of open-angle glaucoma in Greece: the Thessaloniki Eye Study. Am J Ophthalmol. 2007;144:511–519.
    1. de Voogd S, et al. Incidence of open-angle glaucoma in a general elderly population: the Rotterdam Study. Ophthalmology. 2005;112:1487–93.
    1. Leske MC, et al. Predictors of long-term progression in the early manifest glaucoma trial. Ophthalmology. 2007;114:1965–72.
    1. Garway-Heath DF, et al. Latanoprost for open-angle glaucoma (UKGTS): a randomised, multicentre, placebo-controlled trial. Lancet (London, England) 2015;385:1295–304.
    1. Sanfilippo PG, Hewitt AW, Hammond CJ, Mackey DA. The heritability of ocular traits. Surv Ophthalmol. 2010;55:561–83.
    1. Hysi PG, et al. Genome-wide analysis of multi-ancestry cohorts identifies new loci influencing intraocular pressure and susceptibility to glaucoma. Nat Genet. 2014;46:1126–30.
    1. Springelkamp H, et al. New insights into the genetics of primary open-angle glaucoma based on meta-analyses of intraocular pressure and optic disc characteristics. Hum Mol Genet. 2017;26:438–453.
    1. Choquet H, et al. A large multi-ethnic genome-wide association study identifies novel genetic loci for intraocular pressure. Nat Commun. 2017;8:2108.
    1. Bailey JNC, et al. Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma. Nat Genet. 2016;48:189–94.
    1. Gharahkhani P, et al. Common variants near ABCA1, AFAP1 and GMDS confer risk of primary open-angle glaucoma. Nat Genet. 2014;46:1120–1125.
    1. Chen Y, et al. Common variants near ABCA1 and in PMM2 are associated with primary open-angle glaucoma. Nat Genet. 2014;46:1115–1119.
    1. Chan MPY, et al. Associations with Intraocular Pressure in a Large Cohort: Results from the UK Biobank. Ophthalmology. 2016;123:771–82.
    1. Khawaja AP, et al. The EPIC-Norfolk Eye Study: rationale, methods and a cross-sectional analysis of visual impairment in a population-based cohort. BMJ Open. 2013;3:1–10.
    1. Bulik-Sullivan BK, et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47:291–295.
    1. Jiang Z, et al. Hepatocyte Growth Factor Genetic Variations and Primary Angle-Closure Glaucoma in the Han Chinese Population. PLoS One. 2013;8:8–12.
    1. Khor CC, et al. Genome-wide association study identifies five new susceptibility loci for primary angle closure glaucoma. Nat Genet. 2016;48:556–562.
    1. Agarwal R, Agarwal P. Newer targets for modulation of intraocular pressure: focus on adenosine receptor signaling pathways. Expert Opin Ther Targets. 2014;18:527–39.
    1. Wiggs JL, Pasquale LR. Genetics of glaucoma. Hum Mol Genet. 2017;26:R21–R27.
    1. Souma T, et al. Angiopoietin receptor TEK mutations underlie primary congenital glaucoma with variable expressivity. J Clin Invest. 2016;126:2575–2587.
    1. Eklund L, Kangas J, Saharinen P. Angiopoietin–Tie signalling in the cardiovascular and lymphatic systems. Clin Sci. 2016;131:87–103.
    1. Kizhatil K, Ryan M, Marchant JK, Henrich S, John SWM. Schlemm’s canal is a unique vessel with a combination of blood vascular and lymphatic phenotypes that forms by a novel developmental process. PLoS Biol. 2014;12:e1001912.
    1. Thomson BR, et al. A lymphatic defect causes ocular hypertension and glaucoma in mice. J Clin Invest. 2014;124:4320–4324.
    1. Aspelund A, et al. The Schlemm’s canal is a VEGF-C/VEGFR-3-responsive lymphatic-like vessel. J Clin Invest. 2014;124:3975–86.
    1. Romero P, Sanhueza F, Lopez P, Reyes L, Herrera L. c.194 A>C (Q65P) mutation in the LMX1B gene in patients with nail-patella syndrome associated with glaucoma. Mol Vis. 2011;17:1929–39.
    1. Ali M, et al. Null Mutations in LTBP2 Cause Primary Congenital Glaucoma. Am J Hum Genet. 2009;84:664–671.
    1. Marcos S, et al. Meis1 coordinates a network of genes implicated in eye development and microphthalmia. Development. 2015;142:3009–20.
    1. Hsieh Y-W, Zhang X-M, Lin E, Oliver G, Yang X-J. The homeobox gene Six3 is a potential regulator of anterior segment formation in the chick eye. Dev Biol. 2002;248:265–80.
    1. Aldahmesh MA, et al. The syndrome of microcornea, myopic chorioretinal atrophy, and telecanthus (MMCAT) is caused by mutations in ADAMTS18. Hum Mutat. 2013;34:1195–1199.
    1. Cheng CY, et al. Nine loci for ocular axial length identified through genome-wide association studies, including shared loci with refractive error. Am J Hum Genet. 2013;93:264–277.
    1. Larsson M, et al. GWAS findings for human iris patterns: Associations with variants in genes that influence normal neuronal pattern development. Am J Hum Genet. 2011;89:334–343.
    1. Khawaja AP, et al. Assessing the Association of Mitochondrial Genetic Variation With Primary Open-Angle Glaucoma Using Gene-Set Analyses. Invest Ophthalmol Vis Sic. 2016;57:5046–5052.
    1. MacArthur J, et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog) Nucleic Acids Res. 2017;45:D896–D901.
    1. Marcus DM, et al. Sleep disorders: a risk factor for normal-tension glaucoma? J Glaucoma. 2001;10:177–83.
    1. Carnes MU, Allingham RR, Ashley-Koch A, Hauser MA. Transcriptome analysis of adult and fetal trabecular meshwork, cornea, and ciliary body tissues by RNA sequencing. Exp Eye Res. 2018;167:91–99.
    1. Momont AC, Mills RP. Glaucoma Screening: Current Perspectives and Future Directions. Semin Ophthalmol. 2013;28:185–190.
    1. Luce DA. Determining in vivo biomechanical properties of the cornea with an ocular response analyzer. J Cataract Refract Surg. 2005;31:156–62.
    1. Luce D. Methodology for Corneal Compensated IOP and Corneal Resistance Factor for An Ocular Response Analyzer. Invest Ophthalmol Vis Sci. 2006;47:2266.
    1. van der Valk R, et al. Intraocular pressure-lowering effects of all commonly used glaucoma drugs: a meta-analysis of randomized clinical trials. Ophthalmology. 2005;112:1177–85.
    1. van Koolwijk LME, et al. Common genetic determinants of intraocular pressure and primary open-angle glaucoma. PLoS Genet. 2012;8:e1002611.
    1. Loh PR, et al. Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nat Genet. 2015;47:284–290.
    1. Riboli E, Kaaks R. The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int J Epidemiol. 1997;26(Suppl 1):S6–14.
    1. Day N, et al. EPIC-Norfolk: study design and characteristics of the cohort. European Prospective Investigation of Cancer. Br J Cancer. 1999;80(Suppl 1):95–103.
    1. Hayat SA, et al. Cohort Profile: A prospective cohort study of objective physical and cognitive capability and visual health in an ageing population of men and women in Norfolk (EPIC-Norfolk 3) Int J Epidemiol. 2013 doi: 10.1093/ije/dyt086.
    1. Wiggs JL, et al. The NEIGHBOR consortium primary open-angle glaucoma genome-wide association study: rationale, study design, and clinical variables. J Glaucoma. 2013;22:517–25.
    1. Wiggs JL, et al. Common variants at 9p21 and 8q22 are associated with increased susceptibility to optic nerve degeneration in glaucoma. PLoS Genet. 2012;8:e1002654.
    1. Feuer WJ, et al. The Ocular Hypertension Treatment Study: reproducibility of cup/disk ratio measurements over time at an optic disc reading center. Am J Ophthalmol. 2002;133:19–28.
    1. Price AL, et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–909.
    1. Aulchenko YS, Struchalin MV, van Duijn CM. ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics. 2010;11
    1. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26:2190–1.
    1. Mägi R, Morris AP. GWAMA: Software for genome-wide association meta-analysis. BMC Bioinformatics. 2010;11
    1. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88:76–82.
    1. Yang J, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet. 2012;44:369–75. S1–3.
    1. Yang J, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42:565–9.
    1. Devlin B, Roeder K. Genomic control for association studies. Biometrics. 1999;55:997–1004.
    1. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc Ser B. 1995;57:289–300.
    1. Bulik-Sullivan B, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet. 2015;47:1236–1241.
    1. Dayem Ullah AZ, Lemoine NR, Chelala C. SNPnexus: A web server for functional annotation of novel and publicly known genetic variants (2012 update) Nucleic Acids Res. 2012;40:65–70.
    1. Lonsdale J, et al. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45:580–585.
    1. Barbeira A, et al. Integrating tissue specific mechanisms into GWAS summary results. bioRxiv. 2017 doi: 10.1101/045260. 45260.
    1. Gamazon ER, et al. A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. 2015;47:1091–1098.
    1. Ayellet VS, Groop L, Mootha VK, Daly MJ, Altshuler D. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 2010;6

Source: PubMed

Sponsoren und Mitarbeiter

Krankheiten

Drogeninterventionen

3
Abonnieren